jfa journal

AND option

OR option

INTRINSIC CAPACITIY MONITORING BY DIGITAL BIOMARKERS IN INTEGRATED CARE FOR OLDER PEOPLE (ICOPE)

 

A. Piau1,2, Z. Steinmeyer1, M. Cesari3, J. Kornfeld4, Z. Beattie4, J. Kaye4, B. Vellas1,2, F. Nourhashemi1,2

 
1. Gerontopole, Toulouse University Hospital, 31059 Toulouse, France; 2. UPS/INSERM, UMR1027, F-31073 Toulouse, France; 3. Department of Clinical Sciences and Community Health, University of Milan, 20122 Milan, Italy; 4. Oregon Center for Aging & Technology (ORCATECH), Oregon Health & Science University, Portland, USA.
Corresponding author: Antoine Piau, La Cité de la Santé, Bâtiment Ex-Biochimie, Hôpital La Grave, Place Lange, TSA 60033, 31059 Toulouse Cedex 9, France, E-mail address: piau.a@chu-toulouse.fr, Phone number: +335 61 32 30 10, Fax number: +335 61 77 64 75

J Frailty Aging 2020;in press
Published online October 5, 2020, http://dx.doi.org/10.14283/jfa.2020.51

 


Abstract

The WHO action plan on aging expects to change current clinical practices by promoting a more personalized model of medicine. To widely promote this initiative and achieve this goal, healthcare professionals need innovative monitoring tools. Use of conventional biomarkers (clinical, biological or imaging) provides a health status assessment at a given time once a capacity has declined. As a complement, continuous monitoring thanks to digital biomarkers makes it possible to remotely collect and analyze real life, ecologically valid, and continuous health related data. A seamless assessment of the patient’s health status potentially enables early diagnosis of IC decline (e.g. sub-clinical or transient events not detectable by episodic evaluations) and investigation of its probable causes. This narrative review aims to develop the concept of digital biomarkers and its implementation in IC monitoring.

Key words: ICOPE program, digital biomarkers, technology, remote monitoring, intrinsic capacity.


 

The ICOPE program and the necessary but difficult monitoring of intrinsic capacity over time

The WHO defines Intrinsic Capacity (IC) as a “composite of all physical and mental capacities that an individual can draw on”, and functional ability as “health-related attributes that enable people to be and to do what they have reason to value” determined by the interaction of a person’s IC with their environment (1). The ‘Integrated care for older people’ (ICOPE) report translates this strategy into clinical recommendations (WHO ICOPE), from assessment of individual needs and preferences to the development of a comprehensive care plan and coordinated services. ICOPE defines older adult’s health status with five domains of intrinsic capacity: locomotor, vitality, sensory, cognition and psychological capacity. WHO ICOPE recommended an overall clinical approach from large-scale screening to the proposal of an individualized intervention if IC declines.
IC evaluation should be based on longitudinal multiple observations of an individual’s trajectory over time (1), but real-life implementation raises serious issues. Previous primary care initiatives have shown the possibility to screen and assess older people presenting a high risk of IC impairment and to implement a personalized care plan as necessary (2, 3). Ideally, this close follow-up would occur in a person’s home and community setting with minimal intrusion. However, promotion of this outpatient care follow-up remains sparse. Despite being challenging, continuous monitoring of health-related real-life data (not reliant on clinician-mediation), persists as among the most critical issues faced by modern medicine (4, 5) for a number of reasons:
(i) Increasing numbers of patients with limited health resources, constrains the possibility of in-person assessment (self-management is increasingly necessary);
(ii) For implementation of proactive or preventive personalized interventions, early negative trends in IC must be detected in order to investigate underlying causes;
(iii) Continuous monitoring of IC dimensions is needed to measure an individual’s longitudinal trajectories over time after an intervention;
(iv) Functional abilities assessment – explained by the interaction of a person’s IC with its environment – must be unobtrusively measured in one’s own environment (achieving ecological validity).

In this narrative review, we propose to illustrate, through examples from basic research and clinical initiatives, the potential contribution of the so-called «digital biomarker» to this need for intrinsic capacity monitoring.

Why Digital Medicine can be useful for ICOPE implementation

How is a digital biomarker different from a ‘conventional’ biomarker?

Early detection of health transitions by physicians is often difficult (4, 5). Thus, identifying sensitive and clinically relevant biomarkers to detect subtle but meaningful changes is a challenge. Most conventional biomarkers (6) do not fit a long-term monitoring strategy. Indeed, clinical biomarkers such as questionnaires are time consuming, performed at a given point in time, which affects sensitivity, and are based on patients’ recall of prior events (7). Biological biomarkers are often invasive and do not lend themselves to high throughput collection. Finally, imaging biomarkers are costly, require specialized facilities and personnel, and inappropriate for a continuous data collection model (5).
Relatively new terms and concepts have been developed in Information and Communication Technologies (ICT) in particular with regard to innovative clinical endpoints emerging from digital medicine (8-12). We have chosen to use the widespread term ‘digital biomarkers’ (DB). The proposed definition of ‘digital biomarkers’ is : objective, quantifiable, physiological and behavioral data that are collected and measured by means of digital devices such as embedded environmental sensors or wearables, which opens up opportunities for remote data collection and processing of large amounts of ecologically valid, real-life, continuous and long-term health-related data. Table 1. illustrates the difference between conventional compared to digital biomarkers.

Table 1
Key points underling the uniqueness of digital biomarkers and opportunities for ICOPE

*IC, Intrinsic Capacity.

 

What do digital biomarkers have to offer for ICOPE?

The use of conventional biomarkers proposes an in-depth clinical, biological or imaging assessment when a decline in capacity is diagnosed. Conversely, continuous monitoring with digital biomarkers make it possible to prospectively detect transitory or short-term variation over time or sub-clinical decline in IC (see Figure 1 for practical examples). For example, the evolution of ultradian (e.g. variation in body temperature) or circadian (e.g. sleep-wake cycle) rhythms is poorly explored and exploited in clinical practice due to the lack of simple and acceptable measurement tools. DB can capture short-term intra-individual fluctuations in IC and functional abilities. Intra-individual variability in performance (e.g. day-to-day gait speed variability) may also be among the earliest indicators of a negative trend in one’s IC (13-18) (figure 2). DBs enable the differentiation of short-term fluctuations (i.e. a good day vs. a bad day) from more persistent, long-term changes and provides a means to objectify the speed of recovery of an individual after an acute event (e.g. fall). Lastly, DB could measure subclinical events, which are associated with poor prognosis that are not detectable by episodic assessments. For example, ‘silent falls’ are falls which are unnoticed by healthcare professionals but lead nevertheless to impaired walking ability and an increased the risk of loss of autonomy in the future (19).
DB can thus provide health care professionals with information about negative trends in IC by timely checking the patient’s status and investigating the underlying causes. This measurement of variations in IC gives us access to information that was previously inaccessible and allows us to understand why and when a person remains stable, recovers quickly after an event or continues to lose autonomy despite interventions.

Figure 1
Monitoring the activity dimension of intrinsic capacity through digital biomarkers

Note: The monitoring of physical activity through digital biomarkers (e.g. gait speed as measured by wearables or embedded sensors) could detect: (i) early negative trends or subclinical declines not detected by episodic clinical assessments due to lack of sensitivity ( scenario A); (ii) a transient decline between two face-to-face visits ( scenario B); (iii) a change in intra-individual variability that may precede a decline or herald recovery ( scenario C).

 

Figure 2
Intra-individual variability in performance over time

Note: one hypothesis, supported by several authors (15, 40), is an increased variability of health-related parameter in a situation of early pre-symptomatic impairment followed by a decreased variability before a clinically perceptible impairment occur (scenario A). If we stick to that hypothesis, an increased variability in performance (physiological reaction) and then a return to a normal variability could announce an early recovery in IC and thus a favorable prognosis (scenario B).

 
 

How can we design a digital health program for ICOPE

The implementation of ICOPE is divided into several steps: a remote first line screening of the domains of intrinsic capacity as defined by WHO (STEP 1); follow-up over time and, if necessary, an in-depth assessment carried out at home or in a health care facility (STEP 2). The latter would occur if a decline is detected. Once the underlying causes are investigated, an individualized intervention program can be proposed (STEPS 3-5). Digital biomarkers can be implemented in the first step (STEP 1) and carried through to later steps for long-term patient monitoring.

First-line Screening (STEP 1)

It is possible to propose different digital tools depending on the healthcare context, specific use case and end-users. Large-scale evaluation (e.g. text messaging) may be implemented by the use of existing technologies such as smartphones which are low-cost and widely available tools. For specific scenarios, other tools may be developed and integrated (e. g. dedicated smartphone apps, embedded sensors). Examples of tools are proposed in Table 2: from the simplest use of online surveys to complex multi-domain, sensor-based measurements. A personalized and increasing level of digital assistance can be offered to the user. The level of assistance required and its evolution over time may by itself indicate the user’s capabilities.
Digital technologies offer us numerous possibilities of remote screening and assessment, as shown in Table 2, However, by definition, digital biomarkers are more related to continuous monitoring or high frequency collection, and not to the occasional use of a digital tool for one-time screening.. Ideally, DBs allow us to uncover (figure 1):
– a transient decline in an IC during a minor clinical event;
– a negative and sustained subclinical trend in one or several IC subdomains;
– an abnormal intra-individual fluctuation in IC and/or in functional abilities.

This will also be used to objectify the recovery rate during the proposed intervention.

Table 2
Examples of digital solution for STEP 1 implementation

*Abbreviations: SPPB, Short Physical Performance Battery; GP, General Practitioner; MOCA, Montreal Cognitive Assessment; GDS, Geriatric depression Scale; MNA-SF, Mini Nutritional Assessment Short-Form; § Note. Most of the examples of simple digital solutions (STEP 1, column 3) are already implemented in the ICOPE-CARE program, whereas the example of advanced digital solutions (STEP 1, column 4) are ideas for future improvements.

 

DB for remote continuous follow-up of IC

Several research teams have confirmed both the relationship between real life sensor-based DB and IC dimensions (5, 10, 11, 20, 21) and the possibility of tracking subclinical events (19). Sensor-based real life in-home walking speeds (15), activity patterns (18), routine driving (22), variability in medication taking (17), sleep activity (23), and daily computer use (14) have been correlated to functional autonomy and cognitive status. Continuous monitoring of IC-related parameters provides relevant information under free-living conditions. Given the importance of acceptability and adherence issues in this population, use of passive unobtrusive solutions are preferred (e.g. smart home environments) rather than wearables that require more active engagement (24). However, wearables (and their related apps) rely on self-management and thus can actively involve patients in their care.
Remote follow-up may be performed in different ways:
– End-user centered active solutions (self-assessment) providing feedback to the patient in order to drive him/her to a healthier lifestyle without any professional support.
– A solution focused on healthcare professionals through regular teleconsultations with connected objects (e.g. actimeter) to provide continuous objective data.

In between, the intervention of a third party, will be required in many cases. The range of solutions is wide, from a family care partner to a health professional’s support (e.g. nurse), at home or in a dedicated place (e.g. pharmacy, public office). The tool chosen and the complexity of the assessment must obviously be adapted to the patient’s socio-economic context (e.g. highly educated urban dwellers vs low income, rural, socially isolated). Many variables must be taken into account before designing a monitoring solution (Table 3). Using tools that are familiar to the target audience (e.g. email, text messaging) allows a better implementation at a lower cost. One simple solution for continuous follow-up of IC is to repeat ‘STEP 1’ over time through a text-messaging questionnaire coupled to connected objects or sensors.

Table 3
Different variables illustrating the possible monitoring modalities depending on available resources

 

Moving forward, the digital part of the INSPIRE project

To better illustrate how DB could be implemented in daily clinical practice, here is the practical example of the Inspire project, which includes a digital part focusing on IC monitoring.

The INSPIRE-T cohort

A vast research program dedicated to healthy aging was launched in the Occitania region (France), called the INSPIRE initiative (25-27). The INSPIRE Human Research Translational cohort (called INSPIRE-T) is part of this program. The specific aim is to explore and identify biomarkers of aging and IC evolution through annual biological, clinical, and digital data over 10 years, and therefore through both so-called conventional biomarkers and digital biomarkers. 1000 subjects ages 20 to 100+ years old are being enrolled. An important part of the project is to better understand the evolution of IC over time, followed by a web-application for IC self-monitoring, the ICOPE MONITOR Smartphone-app. This application can be easily used by the population and, beyond this research initiative, will be implemented on a large scale through the INSPIRE ICOPE-CARE program (28-34).
This free, open-access application allows the patient to self-assess quickly every 4 months (Step 1, about 6 minutes) through simple, validated tests. For example, he is asked to perform a self-timed chair-raising test. A team of nurses receives the results remotely on a dashboard. When a decline is detected between two self-assessments, the patient is offered a face-to-face evaluation (Step 2). If the time gap between two self-assessments is relatively long (4 months) and if the measurement is not yet sensor-mediated, this type of organization paves the way for the wider use of digital biomarkers for IC monitoring (e.g. automatic and unobtrusive measurement of transfers from sitting to standing by an accelerometer throughout the day). It is with this in mind that we launched the ancillary study CART France to anticipate this transition.

The CART-France digital biomarkers cohort

To further explore the field of IC digital biomarkers, we launched the CART-France cohort (an ancillary study of INSPIRE-T). It consists of a subgroup of 100 INSPIRE-T participants monitored by ambient and wearable sensors at home (e.g. infrared sensors on the ceiling, bed mat) over a long period of time. This will allow remote and continuous monitoring of IC trajectories and detect subtle changes that are not readily detected with conventional methods. For this purpose, INSPIRE has initiated a partnership with the ORCATECH team at Oregon Health & Science University in Portland (OHSU, OR, USA), a leading center in the field of smart homes and digital biomarkers in the field of advanced age and the coordinating center of the Collaborative Aging (in Place) Research Using Technology (CART) research project. The ORCATECH CART program supports an infrastructure for rapid and effective conduct of research utilizing technology (35). As such, we will be the first center outside the USA and Canada to join this research network. The collaboration between INSPIRE and CART is an important step in facilitating a more global view of digital health technology methodology and data sharing. These digital biomarkers will be correlated with clinical data but also biological and imaging -hallmarks of aging gathered through the INSPIRE-T cohort (36). This will be the most original part of the project, which will allow a better understanding of the complementary aspects of each type of biomarker. If we take the example of the ‘locomotion’ domain of intrinsic capacity (figure 1 and 2), continuous real-life measurements such as: room transitions, walking speed and its variability over time, number of steps, activity time and sleep time, etc. will be correlated with the annual biological, imaging and clinical evaluations. They are all digital biomarker candidates to be confirmed or discovered.

 

Challenges and opportunities

Integration of digital health in a pre-existing care network and a given socio-economic context is challenging. Beyond technical and regulatory requirements (e.g. health data security, interoperability with the existing IT ecosystem), raw collected data needs to be analyzed before it can be used in decision-making in clinical practice (e.g. establishing thresholds, critical scores). A clinician’s involvement in technical solutions specification is necessary to develop tools which are easily implemented in routine clinical practice. Up until now, most of the literature dealing with digital monitoring has been limited to small samples assessed in specially designed test-homes or bioengineering laboratories (21). These latter results are difficult to extrapolate to real life settings, and less selected, wider populations. Furthermore, as with any change in clinical practice, we need a combination of specific initial and continuing training in addition to political and public awareness to achieve widespread implementation of digital innovations in this area.
As fully discussed elsewhere, technological tools, as a medical intervention, comprises potential risks and thus security, ethical and regulatory concerns (37). As an example, both health data security and regulatory policy issues (e.g. medical device regulation) remain unsettled areas, highly dependent on national regulations despite the effort to develop international health data security standards (e.g. HIPAA, GDPR). Another point of concern is access to care. Paradoxically, new technologies have the potential to both increase and decrease health inequalities. On one hand, digital devices may increase social inequalities due to limited access. For example, an older age, lower income, lower education, living alone, and living in rural areas were found to be associated with lower eHealth use (38); On the other hand, certain studies suggest that digital technologies may reduce disparity in healthcare access regardless of social or economic status and geographical considerations (39, 40).
The clinical validation of DBs also remains a fundamental issue (8-15). It can be done through comparison to clinical gold standard. For example, walking speed as measured by infrared sensors versus walking speed as measured by a stopwatch. However, this example illustrates the paradoxical aspect of such an approach since the precision of these measurements are in no way comparable. The use of a handheld chronometer only gives a measurement that is far from the desired accuracy, which can approach 0.1cm/sec (41). It is also possible to validate these measurements by direct correlations with clinical events (41), when possible and appropriate. Finally, although the first large-scale continuous monitoring initiatives are now more than 10 years old, and have demonstrated valid associations with clinical evaluations using gold standards, there is little cross-reference of these DB with biological or imaging biomarkers. The INSPIRE-T cohort aligns with this need (26, 28).

 

Conclusion and perspectives

Digital technologies offer opportunities to support new models of healthcare through telehealth initiatives enriched by digital biomarkers data. The ICOPE initiative provides a framework to capture the potential contribution of these technologies to the field of aging. DB provide the opportunity to enhance ‘conventional’ biomarkers by adding continuous data flow to discrete and focused in depth analysis. They do not substitute but complement each other. Moreover, DBs uniquely assess a person’s IC interaction with their own environment and thus their functional abilities. Implementing digital medicine in routine clinical practice has the great advantage of integrating overall medical care from screening to treatment. ICTs may also promote other recommendations such as self-management encouragement and remote support for a healthy lifestyle. (http://www.who.int/ageing/health-systems/mAgeing/en/).

 

Funding: The Inspire Program was supported by grants from the Region Occitanie/Pyrénées-Méditerranée (Reference number: 1901175), the European Regional Development Fund (ERDF) (Project number: MP0022856), and the Inspire Chairs of Excellence funded by: Alzheimer Prevention in Occitania and Catalonia (APOC), EDENIS, KORIAN, Pfizer, Pierre-Fabre, Fondation Avenir Cogfrail Grant.
Acknowledgements: The authors thank all the health professionals participating in the INSPIRE ICOPE CARE Program. We would also like to thank Zachary Beattie and Judith Kornfeld (OHSU, OR, Portland) for their careful rereading of the first drafts of the article.
Potential Conflicts of Interest: All authors declare to have no support from any organization for the submitted work (except the French Ministry of Health which supported the study by a grant), no financial relationships with any organisations that might have an interest in the submitted work, no other relationships or activities that could appear to have influenced the submitted work.
Ethical Standards: There were no patients included in this study, therefore we did not obtain consent and were not reviewed by an ethics committee.

 

References

1. Cesari M, Araujo de Carvalho I, Amuthavalli Thiyagarajan J, Cooper C, Martin FC, Reginster JY, et al. Evidence for the Domains Supporting the Construct of Intrinsic Capacity. J Gerontol A Biol Sci Med Sci. 2018;73:1653-1660. doi: 10.1093/gerona/gly011.
2. de Kerimel J, Tavassoli N, Lafont C, Soto M, Pedra M, Nourhashemi F, et al. How to Manage Frail Older Adults in the Community? Proposal of a Health Promotion Program Experienced in a City of 16,638 Inhabitants in France. J Frailty Aging. 2018;7:120-126. https://doi.org/10.14283/jfa.2017.47.
3. Piau A, Sourdet S, Toulza O, Bernon C, Tavassoli N, Nourhashemi F. Frailty Management in Community-Dwelling Older Adults: Initial Results of a Trained Nurses Program. J Am Med Dir Assoc. 2019;20:642-643. doi: 10.1016/j.jamda.2018.11.011.
4. Insel T. Digital phenotyping: technology for a new science of behavior. JAMA 2017;318:1215–6
5. Seelye A, Mattek N, Sharma N, Riley T, Austin J, Wild K, et al. Weekly observations of online survey metadata obtained through home computer use allow for detection of changes in everyday cognition before transition to mild cognitive impairment. Alzheimers Dement. 2018;14:187-194. doi: 10.1016/j.jalz.2017.07.756.
6. FDA-NIH. Biomarker Working Group. BEST (Biomarkers, EndpointS, and other Tools) Resource. US: Silver Spring (MD), Food and Drug Administration, 2016. PMID:27010052
7. Wild KV, Mattek N, Austin D, Kaye JA. “Are You Sure?”: Lapses in Self-Reported Activities Among Healthy Older Adults Reporting Online. J Appl Gerontol. 2016;35:627-41. doi: 10.1177/0733464815570667.
8. Kramer F, Sabbah HN, Januzzi JJ, Zannad F, Peter van Tintelen J, Schelbert EB, et al. Redefining the role of biomarkers in heart failure trials: expert consensus document. Heart Fail Rev. 2017;22:263-277. doi: 10.1007/s10741-017-9608-5. PMID:28332132
9. Gold M, Amatniek J, Carrillo MC, Cedarbaum JM, Hendrix JA, Miller BB, et al. Digital technologies as biomarkers, clinical outcomes assessment, and recruitment tools in Alzheimer’s disease clinical trials. Alzheimers Dement (N Y). 2018;4:234-242. doi: 10.1016/j.trci.2018.04.003.
10. Faurholt-Jepsen M, Vinberg M, Frost M, Christensen EM, Bardram JE, Kessing LV. Smartphone data as an elec¬tronic biomarker of illness activity in bipolar disorder. Bipolar Disord 2015; 17: 715–728.
11. Saeb S, Zhang M, Karr CJ, Schueller SM, Corden ME, Kording KP, et al. Mobile phone sensor correlates of depressive symptom severity in daily-life behavior: an exploratory study. J Med Internet Res 2015; 17:e175.
12. Arnerić SP, Cedarbaum JM, Khozin S, Papapetropoulos S, Hill DL, Ropacki M, et al. Biometric monitoring devices for assessing end points in clinical trials: developing an ecosystem. Nat Rev Drug Discov. 2017;16:736. doi: 10.1038/nrd.2017.153.
13. Kaye J. Home-based technologies: a new paradigm for conducting dementia prevention trials. Alzheimers Dement 2008;4(1 Suppl 1):S60-6.
14. Kaye J, Mattek N, Dodge HH, Campbell I, Hayes T, Austin D, et al. Unobtrusive measurement of daily computer use to detect mild cognitive impairment. Alzheimers Dement. 2014;10:10-7. doi: 10.1016/j.jalz.2013.01.011.
15. Dodge HH, Mattek NC, Austin D, Hayes TL, Kaye JA. In-home walking speeds and variability trajectories associated with mild cognitive impairment. Neurology. 2012;78:1946-52. doi: 10.1212/WNL.0b013e318259e1de.
16. Leach JM, Mancini M, Kaye JA, Hayes TL, Horak FB. Day-to-Day Variability of Postural Sway and Its Association With Cognitive Function in Older Adults: A Pilot Study. Front Aging Neurosci. 2018;10:126. doi: 10.3389/fnagi.2018.00126.
17. Austin J, Klein K, Mattek N, Kaye J. Variability in medication taking is associated with cognitive performance in nondemented older adults. Alzheimers Dement (Amst). 2017;6:210-213. doi: 10.1016/j.dadm.2017.02.003.
18. Hayes TL, Abendroth F, Adami A, Pavel M, Zitzelberger TA, Kaye JA. Unobtrusive assessment of activity patterns associated with mild cognitive impairment. Alzheimers Dement, 2008;4:395–405. doi: 10.1016/j.jalz.2008.07.004.
19. Piau A, Mattek M, Duncan C, Sharma N, Riley T, Kaye J. The five W’s of falls – weekly online health survey of community-dwelling older adults: analysis of four years prospective follow-up. J Gerontol A Biol Sci Med Sci. 2019. doi: 10.1093/gerona/glz114.
20. Kaye JA, Maxwell SA, Mattek N, Hayes TL, Dodge H, Pavel M, et al. Intelligent systems for assessing aging changes: home-based, unobtrusive, and continuous assessment of aging. J Gerontol B Psychol Sci Soc Sci 2011;66B:i180–90.
21. Piau A, Wild K, Mattek N, Kaye J. Current State of Digital Biomarker Technologies for Real-Life, Home-Based Monitoring of Cognitive Function for Mild Cognitive Impairment to Mild Alzheimer Disease and Implications for Clinical Care: Systematic Review. J Med Internet Res. 2019;21:e12785. doi: 10.2196/12785.
22. Seelye A, Mattek N, Sharma N, Witter P, Brenner A, Wild K, et al. Passive Assessment of Routine Driving with Unobtrusive Sensors: A New Approach for Identifying and Monitoring Functional Level in Normal Aging and Mild Cognitive Impairment. J Alzheimers Dis 2017;59:1427-1437. PMID:28731434.
23. Westerberg CE, Lundgren EM, Florczak SM, Mesulam MM, Weintraub S, Zee PC, et al. Sleep influences the severity of memory disruption in amnestic mild cognitive impairment: results from sleep self-assessment and continuous activity monitoring. Alzheimer Dis Assoc Disord 2010;24:325-33. PMID:20592579.
24. Piau A, Wild K. Performance of eHealth devices for frailty evaluation in real life settings is far from being demonstrated. Gerontology. 2019;65:309-310. doi: 10.1159/000495208.
25. Vellas B, Scrase D, Rosenberg GA, Andrieu S, Araujo de Carvalho I, Middleton LT. Editorial: WHO Guidelines on Community-Level Interventions to Manage Declines in Intrinsic Capacity: The Road for Preventing Cognitive Declines in Older Age? J Prev Alzheimers Dis. 2018;5:165-167.
26. De Souto Barreto P, Guyonnet S, Ader GI, Andrieu S, Casteilla L, Davezac N, et al. The INSPIRE research initiative: A program for geroscience and healthy aging research going from animal models to humans and the healthcare system. J Frailty Aging 2020. doi: 10.14283/ jfa.2020.18.
27. Beard JR. Linking Geroscience and Integrated Care to Reinforce Prevention. J Prev Alz Dis 2020;2:68-69.
28. Takeda C, Guyonnet S, Sumi Y, Vellas B, Araujo de Carvalho I. Integrated Care for Older People and the Implementation in the INSPIRE Care Cohort. J Prev Alzheimers Dis. 2020;7:70-74.
29. Dent E, Morley JE, Cruz-Jentoft AJ, Woodhouse L, Rodríguez-Mañas L, Fried LP, et al. Physical Frailty: ICFSR International Clinical Practice Guidelines for Identification and Management. J Nutr Health Aging. 2019;23:771-787. doi: 10.1007/s12603-019-1273-z.
30. Guralnik J, Bandeen-Roche K, Bhasin SAR, Eremenco S, Landi F, Muscedere J, et al. Clinically Meaningful Change for Physical Performance: Perspectives of the ICFSR Task Force. J Frailty Aging.2020;9:9-13. doi: 10.14283/jfa.2019.33.
31. Rodriguez-Mañas L, Araujo de Carvalho I, Bhasin S, Bischoff-Ferrari HA, Cesari M, Evans W, et al. ICFSR Task Force Perspective on Biomarkers for Sarcopenia and Frailty. J Frailty Aging. 2020;9:4-8. doi: 10.14283/jfa.2019.32.
32. Morley JE. Editorial: The Future of Geriatrics. J Nutr Health Aging.2020;24:1-2. doi: 10.1007/s12603-019-1308-5.
33. Marengoni A. Letter to the editor: Reply to: The Future of Geriatrics. J Nutr Health Aging. 2020;24:242. doi: 10.1007/s12603-020-1321-8.
34. Muscedere J. Editorial: The Need to Implement Frailty in the International Classification of Disease (ICD). J Frailty Aging. 2020;9:2-3. doi:10.14283/jfa.2020.2.
35. Kaye J, Reynolds C, Bowman M, Sharma N, Riley T, Golonka O, et al. Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data. J Vis Exp. 2018;(137). doi: 10.3791/56942.
36. Guerville F, De Souto Barreto P, Ader I, Andrieu S, Casteilla L, Dray C, et al. Revisiting the Hallmarks of Aging to Identify Markers of Biological Age. J Prev Alzheimers Dis. 2020;7:56-64.
37. Mahoney DF, Purtilo RB, Webbe FM, Alwan M, Bharucha AJ, Adlam TD, Working Group on Technology of the Alzheimer’s Association. In-home monitoring of persons with dementia: Ethical guidelines for technology research and development. Alzheimers Dement 2007 Jul;3(3):217-226. doi: 10.1016/j.jalz.2007.04.388.
38. Reiners F, Sturm J, Bouw LJW, Wouters EJM. Sociodemographic Factors Influencing the Use of eHealth in People with Chronic Diseases. Int J Environ Res Public Health. 2019;16. pii: E645. doi: 10.3390/ijerph16040645.
39. Kamis K, Janevic MR, Marinec N, Jantz R, Valverde H, Piette JD. A study of mobile phone use among patients with noncommunicable diseases in La Paz, Bolivia: implications for mHealth research and development. Global Health. 2015;11:30. doi: 10.1186/s12992-015-0115-y.
40. Maurizi N, Faragli A, Imberti J, Briante N, Targetti M, Baldini K, et al. Cardiovascular screening in low-income settings using a novel 4-lead smartphone-based electrocardiograph (D-Heart®). Int J Cardiol. 2017;236:249-252. doi: 10.1016/j.ijcard.2017.02.027.
41. Piau A, Mattek M, Crissey R, Beattie Z, Dodge H, Kaye J. When will my patient fall? Sensor-based in-home walking speed identifies future falls in older adults. J Gerontol A Biol Sci Med Sci. 2020;75:968-973. doi: 10.1093/gerona/glz128.

FREQUENCY OF CONDITIONS ASSOCIATED WITH DECLINES IN INTRINSIC CAPACITY ACCORDING TO A SCREENING TOOL IN THE CONTEXT OF INTEGRATED CARE FOR OLDER PEOPLE

 

E. González-Bautista1, P. de Souto Barreto1,2, K. Virecoulon Giudici1, S. Andrieu1,2, Y. Rolland1,2, B. Vellas1,2, for the MAPT/DSA group*

 

1. Gerontopole of Toulouse, Institute of Aging, Toulouse University Hospital (CHU Toulouse), Toulouse, France; 2. UPS/Inserm UMR1027, University of Toulouse III, Toulouse, France; *The members are listed at the end of the manuscript.
Corresponding author: Emmanuel González-Bautista. Gerontopole of Toulouse, Institute of Ageing, Toulouse University Hospital (CHU Toulouse), 37 Allée Jules Guesde, 31000 Toulouse, France. Mobile 06 22 10 14 96 emmanuel.scout@gmail.com

J Frailty Aging 2020;in press
Published online August 7, 2020, http://dx.doi.org/10.14283/jfa.2020.42

 


Abstract

Background: The screening tool of the Integrated Care for Older People (ICOPE Step 1), designed to detect declines in the domains of intrinsic capacity, has been incipiently investigated in older adult populations. Objectives: To retrospectively estimate the frequency of priority conditions associated with declines in intrinsic capacity according to an adaptation of the screening tool ICOPE Step 1 among participants of the Multidomain Alzheimer Preventive Trial (MAPT). Design: A cross-sectional retrospective analysis from the baseline assessment of the MAPT. Setting: The data was gathered during a preventive consultation for cardiovascular risk factors in memory clinics in France. Participants : Seven hundred fifty-nine older adults aged 70-89 years with memory complaints, allocated to the multidomain groups of the MAPT study. Measurements: Five domains of intrinsic capacity (cognition, locomotion, nutrition, sensorial, and psychological) were assessed using a screening tool similar to the ICOPE Step 1 (MAPT Step 1). The frequency of six conditions associated with declines in intrinsic capacity (cognitive decline, limited mobility, malnutrition, visual impairment, hearing loss, and depressive symptoms) was obtained for older adults with memory complaints participating in the MAPT study. Results: Overall, 89.3% of the participants had one or more conditions associated with declines in intrinsic capacity. The overall frequency of each condition was: 52.2% for cognitive decline, 20.2% for limited mobility, 6.6% for malnutrition, 18.1% for visual impairment, 56.2% for hearing loss, and 39% for depressive symptoms. Conclusion: After being screened with an adaptation of the ICOPE step 1 (MAPT step 1) tool, 9/10 older adults had one or more conditions associated with declines in intrinsic capacity. The relative frequency differs across conditions and could probably be lower in a population without memory complaints. The frequency of screened conditions associated with declines in IC highlights how relevant it is to develop function-centered care modalities to promote healthy aging.

Key words: Intrinsic capacity, screening, physical functions, integrated care, older adults.

Abbreviations: CCHA: Clinical Consortium for Healthy Ageing; COPD: Chronic obstructive pulmonary disease; FA: Functional ability; IC: Intrinsic capacity; ICOPE: Integrated Care for Older People; MAPT: Multidomain Alzheimer Preventive Trial; NCD: Non-communicable disease; OA: Older adults; WHO: World Health Organization.


 

Background

Screening for early declines of intrinsic capacity (IC) is crucial for the implementation of the Integrated Care for Older People (ICOPE)(1). The World Health Organization (WHO) Clinical Consortium for Healthy Ageing (CCHA) and other public health and aging experts developed the ICOPE guidelines. The objective of the ICOPE guidelines is to help key stakeholders in the health and social care arenas to design and implement integrated person-centered models of care (1–3).
The ICOPE approach might prevent care-dependency by timely detecting and managing conditions associated with declines in intrinsic capacity (IC). IC is the composite of all physical and mental capacities of an individual, organized in five domains: cognition, mobility, nutrition, sensorial, and psychological. The interaction between the IC and the environment determines functional ability and healthy aging (4,5). The WHO ICOPE approach has, thus, the goal of helping health systems support healthy aging (4) through the maintenance of optimal functional ability levels during aging.
The clinical care pathways proposed by the ICOPE (1) start with a screening process (ICOPE Step 1). The purpose of the screening is to detect conditions associated with declines in IC at the community level, namely cognitive decline, limited mobility, malnutrition, visual impairment, hearing loss, and depressive symptoms. People identified as having normal IC levels will receive general health advice (i.e., physical activity, nutrition). In contrast, those with IC declines will receive an in-depth assessment (ICOPE Step 2) to confirm or rule such declines. Afterward, they will follow the next steps in the care pathway (i.e., searching the causes of low IC levels, designing a person-centered care plan).
For health service providers, ICOPE Step 1 has a strategic role because it opens the door for the subsequent steps in the healthcare pathway. By managing the adequate «filter» to identify the individuals who can benefit the most from health and social interventions, the healthcare system could enhance the effective use of the available resources.
We have recently reviewed the literature on the topic (in press) and observed only ten original studies on the topic. None of those studies investigated the frequency of low levels of IC according to the screening tool. To our knowledge, measurements of conditions associated with declines in intrinsic capacity, according to ICOPE Step 1 have not been reported so far. Therefore, this study aimed to retrospectively estimate the frequency of conditions associated with declines in intrinsic capacity according to an adaptation of the screening tool ICOPE Step 1 among participants of the Multidomain Alzheimer Preventive Trial (MAPT).

 

Methods

This study uses cross-sectional data to describe the baseline frequency of conditions associated with IC declines among the participants of the Multidomain Alzheimer Preventive Trial (MAPT). The MAPT was not designed to assess the ICOPE screening; thus, we used a retrospective approach to define the variables of interest according to the availability of data. The detailed methodology of MAPT has been described elsewhere(6, 7). Briefly, MAPT was a 3-year randomized controlled trial on the effect of a multidomain intervention (nutritional and physical activity counseling, cognitive training, and annual preventive consultations for the management of cardiovascular risk factors and the detection of functional impairments) with and without supplementation of omega-3 polyunsaturated fatty acids (PUFA) on the prevention of cognitive decline among community-dwelling adults aged 70 years and older. The trial protocol (ClinicalTrials.gov identifier: NCT00672685) was approved by the French Ethical Committee located in Toulouse (CPP SOOM II) and was authorized by the French Health Authority. All participants signed their consent before any study assessment.

Participants

Inclusion criteria for the MAPT study were meeting at least one of three conditions: a) spontaneous memory complaint expressed to their physician, b) limitation in one instrumental activity of daily living (IADL), or c) slow gait speed (≤0.8 m/s). Exclusion criteria comprised participants with a Mini-Mental State Examination (MMSE) score < 24, diagnosis of dementia, the limitation for any of the basic activities of daily living, and those taking PUFA supplements at baseline.
The 759 subjects allocated to the multidomain intervention groups of MAPT constitute our study sample. Data on the five domains of IC was available only for them because they underwent a preventive consultation with a physician who assessed for the hearing and vision capacities. The rest of the 1,679 participants initially enrolled in MAPT were lacking data on the sensorial domain.

IC domains assessment – Step 1 (screening)

We followed the recommendations from the WHO ICOPE Handbook to operationalize the ICOPE Step 1 tool(1). To be consistent with the terms used in the Handbook, we used «cognitive decline,» «limited mobility,» «malnutrition,» «visual impairment,» «hearing loss» and «depressive symptoms» to refer to the conditions associated with declines in IC. These terms are not equivalent to clinical diagnoses.
The same items recommended by the WHO were used to evaluate three domains: cognition, locomotion, and vitality/nutrition. Nevertheless, due to data availability, we adapted the operationalization of the following conditions associated with declines in IC: visual impairment: was assessed by self-reported visual acuity items; hearing loss: was measured with item number 3 of the screening version of the hearing handicap inventory for the elderly (HHSE-S(8,9)); depressive symptoms: were defined according to items 2 and 7 of the Geriatric Depression Scale (GDS-15) (10), which were judged by three experts (one geriatrician, one general practitioner, and one researcher in clinical gerontology) as being the most similar items compared to those recommended by WHO. This resulting adapted screening tool was then called «MAPT Step 1» (Table 1).
Specifically, for hearing loss, we used the validated HHIE-S(8) because studies have validated this instrument against pure tone audiometry. Sindhusake et al. (11) concluded that HHIE-S has adequate sensitivity and specificity for detecting moderate hearing loss (audiometry hearing threshold of >40 dB). The HHIE-S cut-off >8 points is established in the guidelines of the American Speech-Language-Hearing Association(12) as a criterion for a referral to further audiological testing.
More sophisticated measurements of IC have been published but are not feasible in a clinical routine setting(13,14). A screening procedure like ICOPE Step 1 may help to target an at-risk population that would, then, receive in-depth assessments and a closer follow-up.

Table 1
Comparison of the operationalization of the conditions associated with declines in IC between the ICOPE handbook and the definitions applied in MAPT study

*Participants were explicitly asked for each of the items in the time and spatial orientation, and not only an open-ended question. The participant was recorded as with cognitive decline if he/she was wrong to tell the date (number and name of the day, month, year), or wrong to tell the name of the hospital, the level of the building, department and region.
†We used item number 3 of the HHIE-S because of its similarity with the whisper test.

 

IC domains in-depth assessment

The following tests were performed for an in-depth assessment of the IC domains:
• Cognition: Mini-Mental State Examination (MMSE) (15).
• Locomotion: Short Performance Physical Battery (SPPB) (16)
• Vitality/nutrition: Mini Nutritional Assessment (full version MNA)(17).
• Vision: Monoyer vision chart (18).
• Hearing: Hearing Handicap Inventory for the Elderly – Screening version (HHIE-S) (8).
• Psychological: 15-item Geriatric Depression Scale (GDS-15) (10).

Statistical Analysis

We used percentages to report the frequency of the declines in IC in our study population and by age and sex subgroups. Scores of the in-depth assessments were described using means and standard deviation (SD). Data were analyzed using STATA 14®.

 

Results

The mean age of our study population was 75.2 years (SD=4.3), 63.6% of them were women, and 28.9% reported 12 years or more of formal education (Table 2). Overall, 89.3% of the population presented one or more conditions associated with declines in IC (87.4% among females, 92.8% among males). Table 3 shows the frequency of conditions associated with declines in IC by domain. Relative frequency of the conditions of interest and mean scores of the tests used for in-depth assessment for sex and age-groups are reported in Supplementary Table S1.

Table 2
Sex, frailty status, number of instrumental activities impaired and mean values of functional performance tests by age group among participants of the MAPT Study

MMSE= mini-mental state examination. SPPB= short performance physical battery. MNA= mini nutritional assessment full version. HHIE-S= Hearing Handicap Inventory for the Elderly – Screening version. GDS= Geriatric Depression Scale; * provided in decimal acuity. For reference, 0.8 decimal = 20/25 imperial= 6/7.5 metric = 0.1 LogMAR.

Table 3
Frequency of conditions associated with declines in IC according to the ICOPE step 1 screening tool by age group among participants of the MAPT Study

*Maximum of possible conditions is six because the sensorial domain includes visual impairment and hearing loss

 

Cognitive domain

Half of the studied population presented signs of cognitive decline. Table 4 shows the details of the cognitive items of MAPT Step 1. Failing in the word recall section of the MMSE was three times more frequent than failing in the orientation section. In all age groups, the most frequently mistaken word recall was for the last word in the list given to the participants (i.e., cigarette, flower, door – participants less often recalled the word «door»).

Table 4
Prevalence of cognitive sub-domains and mistaken item from the Mini-Mental State Examination (MMSE) including alternative definitions for cognitive decline by age group among participants of the MAPT Study

* Areas of political division. †MAPT participants used the French version during the study.

 

Mobility domain

Overall, the mean of the time to perform five chair rises was 11.9 seconds (SD=4.5), with age-specific averages ranging from 11.0 (70-74 years) to 16.0 seconds (85-89 years). For the group aged 85-89 years (n=22), the cut-off of 14 seconds proposed by ICOPE Step 1 was at the percentile 52. Further details about the distribution of the sex- and age-specific chair rise times are provided in Supplementary Table S1.

Vitality/Nutrition domain

The mean score in the MNA was 27.6 points, ranging from 27.7 in the youngest group to 26.8 in the oldest group. The frequency of self-reported weight loss or appetite loss was lower than 5% for all the age groups, except for the appetite loss in those aged 80-84 years (7.3%).

Sensorial domain

Vision. In our study population, 92.1% of participants used glasses, contact glasses, implants, or magnifiers at the time of the interview. Even with their supportive devices, up to 14.5% of the participants found it hard to read a newspaper or watch television.
Hearing. Among the participants, 18.2% were using a hearing assistive device at the time of the interview. The screening question for hearing loss identified 55% of those aged 70-74 years and 68% of those aged 85-89 years as positive for hearing loss.

 

Discussion

Our study is the first to describe the frequency of the IC declines according to an adaptation of the ICOPE Step 1 screening tool (MAPT step 1) in a selected cohort of memory clinic attendees. Overall, 89.3% of the participants had one or more conditions associated with declines in IC, according to MAPT Step 1 (87.4% among females, 92.8% among males). Nine in every ten screened older adults would be referred to a specialized, in-depth evaluation. It should be noted, however, that MAPT participants expressed memory complaints at recruitment.
We found a high demand for an in-depth assessment. Consider that the MAPT population is more fit than others reported in French studies (except perhaps for cognitive function due to the inclusion criteria). Compared to a random sample used in the French Three-City Study published by Avila-Funes et al. (19), our population was slightly older (mean age 74.1, SD=5.2 vs. 75.2 years, SD=4.3), reported higher levels of educational attainment (>12 years: 17.0% vs. 28.9%) and a lower frequency of frailty (7.0% vs. 3.2%). Therefore, our findings might be underestimating the frequency of IC declines detected by MAPT Step 1 in a real-world population of users of the healthcare system (except for cognitive decline). Our results highlight the need for adapting our health care system to improve the assessment of functions to prevent functional decline. For example, people detected with signs of cognitive decline using the screening tool ICOPE Step 1 could benefit from multidomain interventions (20–22).
Half of the study population showed signs of cognitive decline. Interestingly, participants more frequently failed in selected items (i.e., recalling the name of the day or the last word in a list of three). Therefore, it will be interesting to explore the domain and item’s capacity to predict health events such as frailty incidence in future studies.
Regarding locomotion, the cut-off time to perform five chair rises deserves further investigation (the ICOPE handbook suggests 14 seconds). A cut-off of 15 sec was used in a study measuring the time to complete ten rather than five chair-rises (23). A meta-analysis by Bohannon concluded that 11.4 and 12.7 seconds are suitable cut-off values among subjects aged 60-69 and 80-89, respectively (24). In the SPPB validation study, Guralnik et al. (16) found that 13.7 sec corresponded to the 50th percentile of performance in the chair rise test in a population of more than 5,000 American people aged 71 years or older in 1981. However, current generations might have a better physical performance than those assessed 30 years ago. Establishing age- tailored cut-offs for the chair rise test would allow for a better classification of the performance levels. They would not add difficulty to the implementation of the ICOPE care pathway.
Malnutrition was the least frequent condition. The average score for the full MNA was 27.6, which is higher than the cut-off often used to define the risk of malnutrition (23.5) (17). We think that clinicians should address anorexia and weight loss even if the MNA test if above the cut-off designed for malnutrition. According to the Global Leadership Initiative on Malnutrition (GLIM) criteria for malnutrition in adults (25), reduced food intake/assimilation and weight loss are sufficient to integrate the diagnosis of malnutrition. Also, the Beck depression inventory (26) and by the Center for Epidemiologic Studies Depression (CES-D) scale (27) consider the loss of appetite as a depressive symptom. Moreover, those who leave alone are at higher nutritional risk (28).
For the psychological domain, we did not use the exact questions suggested in the ICOPE screening tool Step 1 because they were not available in MAPT Study. Therefore, we selected from the GDS-15 the two items that more closely matched the ICOPE definition (Table 1). The frequency of depressive symptoms in our study was high (39%), compared to a previous investigation among French older adults (13.8% evaluated with the CES-D in people aged 75 years; SD=6.8) (29). Shared risk factors for cognitive decline and depressive symptoms can explain this difference. Due to MAPT inclusion criteria, participants were at increased risk for cognitive decline, and more than 40% presented mild cognitive impairment (MCI). For instance, using the MAPT Step 1 tool resulted in an overlap of 72% of the participants according to their cognitive decline and depressive symptoms status (7 out of 10 were simultaneously free from or afflicted by both conditions). The connexions across the IC domains are a hallmark of the ICOPE approach (30, 31). Timely interventions targeting these interactions can prevent further losses of ADL ADLs (32).
In the visual domain, we used three questions related to self-reported problems for vision, even when using correction devices (Table 1). Of note, the frequency of visual impairment in our study may have been underestimated because the questions used in MAPT are more specific than the general question proposed in ICOPE Step 1. Furthermore, we did not consider if the person had hypertension or diabetes, as suggested in the ICOPE tool. Evidence suggests that more than half of the cases of visual impairment in older ages are due to cataract and refractive errors, with less than 5% due to diabetic retinopathy (33–35). Perceived difficulty in reading a journal or watching television was reported in 15% of the population wearing vision aids. We consider this ratio as an indicator of unsatisfied demand for visual correction adjustment.
Our hearing loss estimates show that the age-specific frequency of hearing handicap was higher than the ones reported in the study of Wiley et al. performed with 3,471 non-Hispanic whites in Wisconsin, USA. Our figures were similar to those reported by Tomioka et al. (36), with 1,731 community-dwelling older adults from Nara and Osaka, Japan. The different age distribution could explain the dissimilarities.
Our study has strengths, such as being among the first to report the frequency of conditions associated with declines in the five IC domains in a selected cohort of memory clinic attendees. Moreover, the MAPT Step 1 and the ICOPE Step 1 use the same items for most of the IC domains. Therefore, the frequency of declines on visual, hearing, and psychological domains might have been different from our findings if the WHO ICOPE screening tool had been used. On the other hand, some limitations should be mentioned. There was a potential selection bias towards cognitive decline, given that having a spontaneous memory complaint was one of the inclusion criteria in MAPT. However, in a sensitivity analysis removing participants with a cognitive decline in the MAPT Step 1, 78% of the remaining population still had one or more conditions associated with declines in IC (Supplementary Table S2). Our data should not be generalized to other populations. Compared to the age and sex distribution of French older adults, our population overrepresented women (57.1% vs. 63.6%) and adults aged 70-79 years (39.1% vs. 49.8%) (37).
In summary, almost 90% of adults aged 70 years and older in a selected cohort of memory clinic attendees had at least one condition associated with declines in IC. Frequencies varied from 52.2% in the cognitive domain to 6.2% in the nutrition domain. These findings suggest that implementing the ICOPE Step 1 at the community level will help screen for conditions associated with declines in intrinsic capacity. The frequency of declines in IC can provide health systems managers with an estimation of the amount and the type of resources needed to implement the ICOPE clinical pathways. For example, satisfying the demand for visual aids adjustment, or recruitment of health workforce with psychological training. Interesting questions emerged from this descriptive study. For example, should some items be changed to increase the chances of detecting most of the people at risk? Also, are age-specific cut-offs the most suitable approach for some IC domains in the ICOPE screening tool (notably, locomotion)?

 

MAPT/DSA group: Principal investigator: Bruno Vellas (Toulouse); Coordination: Sophie Guyonnet; Project leader: Isabelle Carrié; CRA: Lauréane Brigitte; Investigators: Catherine Faisant, Françoise Lala, Julien Delrieu, Hélène Villars; Psychologists: Emeline Combrouze, Carole Badufle, Audrey Zueras; Methodology, statistical analysis and data management: Sandrine Andrieu, Christelle Cantet, Christophe Morin; Multidomain group: Gabor Abellan Van Kan, Charlotte Dupuy, Yves Rolland (physical and nutritional components), Céline Caillaud, Pierre-Jean Ousset (cognitive component), Françoise Lala (preventive consultation) (Toulouse). The cognitive component was designed in collaboration with Sherry Willis from the University of Seattle, and Sylvie Belleville, Brigitte Gilbert and Francine Fontaine from the University of Montreal. Co-Investigators in associated centres: Jean-François Dartigues, Isabelle Marcet, Fleur Delva, Alexandra Foubert, Sandrine Cerda (Bordeaux); Marie-Noëlle-Cuffi, Corinne Costes (Castres); Olivier Rouaud, Patrick Manckoundia, Valérie Quipourt, Sophie Marilier, Evelyne Franon (Dijon); Lawrence Bories, Marie-Laure Pader, Marie-France Basset, Bruno Lapoujade, Valérie Faure, Michael Li Yung Tong, Christine Malick-Loiseau, Evelyne Cazaban-Campistron (Foix); Françoise Desclaux, Colette Blatge (Lavaur); Thierry Dantoine, Cécile Laubarie-Mouret, Isabelle Saulnier, Jean-Pierre Clément, Marie-Agnès Picat, Laurence Bernard-Bourzeix, Stéphanie Willebois, Iléana Désormais, Noëlle Cardinaud (Limoges); Marc Bonnefoy, Pierre Livet, Pascale Rebaudet, Claire Gédéon, Catherine Burdet, Flavien Terracol (Lyon), Alain Pesce, Stéphanie Roth, Sylvie Chaillou, Sandrine Louchart (Monaco); Kristelle Sudres, Nicolas Lebrun, Nadège Barro-Belaygues (Montauban); Jacques Touchon, Karim Bennys, Audrey Gabelle, Aurélia Romano, Lynda Touati, Cécilia Marelli, Cécile Pays (Montpellier); Philippe Robert, Franck Le Duff, Claire Gervais, Sébastien Gonfrier (Nice); Yannick Gasnier and Serge Bordes, Danièle Begorre, Christian Carpuat, Khaled Khales, Jean-François Lefebvre, Samira Misbah El Idrissi, Pierre Skolil, Jean-Pierre Salles (Tarbes). MRI group: Carole Dufouil (Bordeaux), Stéphane Lehéricy, Marie Chupin, Jean-François Mangin, Ali Bouhayia (Paris); Michèle Allard (Bordeaux); Frédéric Ricolfi (Dijon); Dominique Dubois (Foix); Marie Paule Bonceour Martel (Limoges); François Cotton (Lyon); Alain Bonafé (Montpellier); Stéphane Chanalet (Nice); Françoise Hugon (Tarbes); Fabrice Bonneville, Christophe Cognard, François Chollet (Toulouse). PET scans group: Pierre Payoux, Thierry Voisin, Julien Delrieu, Sophie Peiffer, Anne Hitzel, (Toulouse); Michèle Allard (Bordeaux); Michel Zanca (Montpellier); Jacques Monteil (Limoges); Jacques Darcourt (Nice). Medico-economics group: Laurent Molinier, Hélène Derumeaux, Nadège Costa (Toulouse). Biological sample collection: Bertrand Perret, Claire Vinel, Sylvie Caspar-Bauguil (Toulouse). Safety management: Pascale Olivier-Abbal. DSA Group: Sandrine Andrieu, Christelle Cantet, Nicola Coley.
Funding: The present work was performed in the context of the Inspire Program, a research platform supported by grants from the Region Occitanie/Pyrénées-Méditerranée (Reference number: 1901175) and the European Regional Development Fund (ERDF) (Project number: MP0022856). The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript.
Acknowledgements: NA
Authors contributions: PB, BV and EG conceived the study. EG, statistics and manuscript writing. KV, PB, LM, BV and SA provided inputs and reviewed the manuscript. BV and SA are PIs in MAPT.
Funding section: The present work was performed in the context of the Inspire Program, a research platform supported by grants from the Region Occitanie/Pyrénées-Méditerranée (Reference number: 1901175) and the European Regional Development Fund (ERDF) (Project number: MP0022856). The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript. “This study received funds from Alzheimer Prevention in Occitania and Catalonia (APOC Chair of Excellence – Inspire Program). The MAPT study was supported by grants from the Gérontopôle of Toulouse, the French Ministry of Health (PHRC 2008, 2009), Pierre Fabre Research Institute (manufacturer of the omega-3 supplement), ExonHit Therapeutics SA, and Avid Radiopharmaceuticals Inc. The promotion of this study was supported by the University Hospital Center of Toulouse. The data sharing activity was supported by the Association Monegasque pour la Recherche sur la maladie d’Alzheimer (AMPA) and the INSERM-University of Toulouse III UMR 1027 Unit».
Conflict of interest: The authors declare no competing interest relevant to this article.
Ethical standard: This study did not include any experiments involving humans or other animals.

 

SUPPLEMENTARY MATERIAL

 

References

1. World Health Organization. Integrated care for older people (ICOPE): Guidance for person-centred assessment and pathways in primary care. [Internet]. Geneva: WHO; 2019 [cited 2019 Nov 14]. 87 p. Available from: https://apps.who.int/iris/bitstream/handle/10665/326843/WHO-FWC-ALC-19.1-eng.pdf?sequence=17
2. Thiyagarajan JA, Araujo de Carvalho I, Peña-Rosas JP, Chadha S, Mariotti SP, Dua T, et al. Redesigning care for older people to preserve physical and mental capacity: WHO guidelines on community-level interventions in integrated care. PLOS Med [Internet]. 2019 Oct 18 [cited 2020 Jan 8];16(10):e1002948. Available from: http://dx.plos.org/10.1371/journal.pmed.1002948
3. World Health Organisation. WHO Clinical Consortium on Healthy Ageing. Report of consortium meeting 1-2 December 2016 in Geneva, Switzerland. 2017;(December).
4. World Health Organization. World Report on Ageing and Health. Geneva: WHO Press; 2015.
5. Cesari M, De Carvalho IA, Thiyagarajan JA, Cooper C, Martin FC, Reginster JY, et al. Evidence for the domains supporting the construct of intrinsic capacity. Vol. 73, Journals of Gerontology – Series A Biological Sciences and Medical Sciences. Oxford University Press; 2018. p. 1653–60.
6. Vellas B, Carrie I, Gillette-Guyonnet S, Touchon J, Dantoine T, Dartigues JF, et al. MAPT study: A multidomain approach for preventing Alzheimer’s disease: design and baseline data. J Prev Alzheimer’s Dis [Internet]. 2014 Jun [cited 2020 Feb 5];1(1):13–22. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26594639
7. Andrieu S, Guyonnet S, Coley N, Cantet C, Bonnefoy M, Bordes S, et al. Effect of long-term omega 3 polyunsaturated fatty acid supplementation with or without multidomain intervention on cognitive function in elderly adults with memory complaints (MAPT): a randomised, placebo-controlled trial. Lancet Neurol. 2017 May 1;16(5):377–89.
8. Ventry IM, Weinstein BE. The hearing handicap inventory for the elderly: A new tool. Ear Hear. 1982;3(3):128–34.
9. Bagai A. Does This Patient Have Hearing Impairment ? JAMA. 2008;295(4):416–28.
10. Yesavage JA, Sheikh JI. Geriatric Depression Scale (GDS). Clin Gerontol [Internet]. 1986 Nov 18;5(1–2):165–73. Available from: https://doi.org/10.1300/J018v05n01_09
11. Sindhusake D, Mitchell P, Smith W, Golding M, Newall P, Hartley D, et al. Validation of self-reported hearing loss. The blue mountainshearing study. Int J Epidemiol. 2001;30(6):1371–8.
12. Association AS-L-H. Guidelines for Audiologic Screening. www.asha.org/policy [Internet]. 1997 [cited 2020 Feb 7];1–64. Available from: http://www.asha.org/policy/GL1997-00199/
13. Beard JR, Jotheeswaran AT, Cesari M, Araujo de Carvalho I. The structure and predictive value of intrinsic capacity in a longitudinal study of ageing. BMJ Open [Internet]. 2019 Nov 2 [cited 2019 Nov 7];9(11):e026119. Available from: http://www.ncbi.nlm.nih.gov/pubmed/31678933
14. Gutiérrez-Robledo LM, García-Chanes RE, Pérez-Zepeda MU. Allostatic Load as a Biological Substrate to Intrinsic Capacity: A Secondary Analysis of CRELES. J Nutr Health Aging [Internet]. 2019 [cited 2019 Nov 5];23(9):788–95. Available from: http://www.ncbi.nlm.nih.gov/pubmed/31641727
15. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–98.
16. Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, et al. A short physical performance battery assessing lower extremity function: Association with self-reported disability and prediction of mortality and nursing home admission. Journals Gerontol. 1994;49(2).
17. Vellas B, Guigoz Y, Garry PJ, Nourhashemi F, Bennahum D, Lauque S, et al. The mini nutritional assessment (MNA) and its use in grading the nutritional state of elderly patients. Nutrition. 1999 Feb;15(2):116–22.
18. World Health Organization. World report on vision. Vol. 214, World report on vision. Geneva: WHO Press; 2019. 180–235 p.
19. Ávila-Funes JA, Helmer C, Amieva H, Barberger-Gateau P, Le Goff M, Ritchie K, et al. Frailty among community-dwelling elderly people in france: The three-city study. Journals Gerontol – Ser A Biol Sci Med Sci. 2008;63(10):1089–96.
20. Rosenberg A, Mangialasche F, Ngandu T, Solomon A, Kivipelto M. Multidomain Interventions to Prevent Cognitive Impairment, Alzheimer’s Disease, and Dementia: From FINGER to World-Wide FINGERS. J Prev Alzheimer’s Dis [Internet]. 2020 [cited 2020 Mar 23];7(1):29–36. Available from: http://www.ncbi.nlm.nih.gov/pubmed/32010923
21. Cherian L, Wang Y, Fakuda K, Leurgans S, Aggarwal N, Morris M. Mediterranean-Dash Intervention for Neurodegenerative Delay (MIND) Diet Slows Cognitive Decline After Stroke. J Prev Alzheimer’s Dis [Internet]. 2019 [cited 2020 Mar 23];6(4):267–73. Available from: http://www.ncbi.nlm.nih.gov/pubmed/31686099
22. Udeh-Momoh C, Price G, Ropacki MT, Ketter N, Andrews T, Arrighi HM, et al. Prospective Evaluation of Cognitive Health and Related Factors in Elderly at Risk for Developing Alzheimer’s Dementia: A Longitudinal Cohort Study. J Prev Alzheimer’s Dis [Internet]. 2019 [cited 2020 Mar 23];6(4):256–66. Available from: http://www.ncbi.nlm.nih.gov/pubmed/31686098
23. Hardy R, Cooper R, Shah I, Harridge S, Guralnik J, Kuh D. Is chair rise performance a useful measure of leg power? Aging Clin Exp Res. 2010;22(5–6):412–8.
24. BOHANNON RW. Reference Values for the Five-Repetition Sit-To-Stand Test: a Descriptive Meta-Analysis of Data From Elders. Percept Mot Skills. 2006;103(5):215.
25. Cederholm T, Jensen GL, Correia MITD, Gonzalez MC, Fukushima R, Higashiguchi T, et al. GLIM criteria for the diagnosis of malnutrition – A consensus report from the global clinical nutrition community. J Cachexia Sarcopenia Muscle [Internet]. 2019 Feb 1 [cited 2020 Feb 27];10(1):207–17. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1002/jcsm.12383
26. Beck AT, Ward CH, Mendelson M, Mock J, Erbaugh J. An Inventory for Measuring Depression. Arch Gen Psychiatry. 1961;4(6):561–71.
27. Radloff LS. The CES-D scale: A self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1(3):385–401.
28. Suthutvoravut U, Tanaka T, Takahashi K, Akishita M, Iijima K. Living with Family yet Eating Alone is Associated with Frailty in Community-Dwelling Older Adults: The Kashiwa Study. J frailty aging [Internet]. 2019 [cited 2020 Mar 23];8(4):198–204. Available from: http://www.ncbi.nlm.nih.gov/pubmed/31637406
29. Montagnier D, Barberger-Gateau P, Jacqmin-Gadda H, Dartigues JF, Rainfray M, Pérès K, et al. Evolution of prevalence of depressive symptoms and antidepressant use between 1988 and 1999 in a large sample of older French people: Results from the personnes agées quid study. J Am Geriatr Soc [Internet]. 2006 Dec [cited 2020 Feb 13];54(12):1839–45. Available from: http://www.ncbi.nlm.nih.gov/pubmed/17198488
30. Kiiti Borges M, Oiring de Castro Cezar N, Silva Santos Siqueira A, Yassuda M, Cesari M, Aprahamian I. The Relationship between Physical Frailty and Mild Cognitive Impairment in the Elderly: A Systematic Review. J frailty aging [Internet]. 2019 [cited 2020 Mar 23];8(4):192–7. Available from: http://www.ncbi.nlm.nih.gov/pubmed/31637405
31. Kwan RYC, Leung AYM, Yee A, Lau LT, Xu XY, Dai DLK. Cognitive Frailty and Its Association with Nutrition and Depression in Community-Dwelling Older People. J Nutr Health Aging [Internet]. 2019 Dec 1 [cited 2020 Mar 23];23(10):943–8. Available from: http://www.ncbi.nlm.nih.gov/pubmed/31781723
32. McGrath R, Erlandson KM, Vincent BM, Hackney KJ, Herrmann SD, Clark BC. Decreased Handgrip Strength is Associated With Impairments in Each Autonomous Living Task for Aging Adults in the United States. J frailty aging. 2019;8(3):141–5.
33. Zhu RR, Shi J, Yang M, Guan HJ. Prevalences and causes of vision impairment in elderly chinese: A socioeconomic perspective of a comparative report nested in Jiangsu Eye Study. Int J Ophthalmol. 2016 Jul 18;9(7):1051–6.
34. Murthy GVS, Vashist P, John N, Pokharel G, Ellwein LB. Prevalence and causes of visual impairment and blindness in older adults in an area of India with a high cataract surgical rate. Ophthalmic Epidemiol. 2010 Aug;17(4):185–95.
35. Bourne RRA, Jonas JB, Bron AM, Cicinelli MV, Das A, Flaxman SR, et al. Prevalence and causes of vision loss in high-income countries and in Eastern and Central Europe in 2015: Magnitude, temporal trends and projections. Br J Ophthalmol. 2018 May 1;102(5):575–85.
36. Tomioka K, Ikeda H, Hanaie K, Morikawa M, Iwamoto J, Okamoto N, et al. The Hearing Handicap Inventory for Elderly-Screening (HHIE-S) versus a single question: reliability, validity, and relations with quality of life measures in the elderly community, Japan. Qual Life Res [Internet]. 2013 Jun [cited 2020 Feb 12];22(5):1151–9. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22833152
37. United Nations Department of Economic and Social Affairs. Population Division. Ageing Profiles [Internet]. Ageing Profiles. 2019 [cited 2020 Feb 13]. Available from: https://population.un.org/ProfilesOfAgeing2019/index.html

THE INSPIRE BIO-RESOURCE RESEARCH PLATFORM FOR HEALTHY AGING AND GEROSCIENCE: FOCUS ON THE HUMAN TRANSLATIONAL RESEARCH COHORT (THE INSPIRE-T COHORT)

 

S. Guyonnet1,*, Y. Rolland1,*, C. Takeda2, P.-J. Ousset2, I. Ader3, N. Davezac4, C. Dray5, N. Fazilleau6, P. Gourdy5, R. Liblau6, A. Parini5, P. Payoux7, L. Pénicaud3, C. Rampon4, P. Valet5, N. Vergnolle8, S. Andrieu9, P. de Souto Barreto10, L. Casteilla3, B. Vellas1 for the INSPIRE Platform group

 

1. Inserm UMR 1027, Toulouse, France; University of Toulouse III, Toulouse, France; Gérontopôle, Department of Geriatrics, CHU Toulouse, Toulouse, France; 2. Gérontopôle, Department of Geriatrics, CHU Toulouse, Toulouse, France; 3. STROMALab, Etablissement Français du Sang-Occitanie (EFS), Inserm 1031, University of Toulouse, National Veterinary School of Toulouse (ENVT), ERL5311 CNRS, Toulouse, France; 4. Centre de Recherches sur la Cognition Animale (CRCA), Centre de Biologie Intégrative (CBI), Université de Toulouse, CNRS, UPS, Toulouse, France; 5. Institut des Maladies Métaboliques et Cardiovasculaires, Inserm/Université Paul Sabatier UMR 1048 – I2MC 1 avenue Jean Poulhès BP 84225 31432 Toulouse Cedex 4 – France; 6. Centre de Physiopathologie Toulouse Purpan, INSERM/CNRS/UPS UMR 1043, University of Toulouse III, Toulouse, France; 7. ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France; 8. IRSD, Université de Toulouse, INSERM, INRA, ENVT, UPS, U1220, CHU Purpan, CS60039, 31024, Toulouse, France; 9. Inserm UMR 1027, Toulouse, France; University of Toulouse III, Toulouse, France; Department of Epidemiology and Public Health, CHU Toulouse, Toulouse, France; 10. Inserm UMR 1027, Toulouse, France; University of Toulouse III, Toulouse, France; Gérontopôle, Institute of Aging, CHU Toulouse, Toulouse, France; *These authors contributed equally to this work.
Corresponding author: Sophie Guyonnet, Inserm UMR 1027, Toulouse, France; University of Toulouse III, Toulouse, France; Gérontopôle, Department of Geriatrics, CHU Toulouse, Toulouse, France, guyonnet.s@chu-toulouse.fr

J Frailty Aging 2020;in press
Published online July 10, 2020, http://dx.doi.org/10.14283/jfa.2020.38

 


Abstract

Background: The Geroscience field focuses on the core biological mechanisms of aging, which are involved in the onset of age-related diseases, as well as declines in intrinsic capacity (IC) (body functions) leading to dependency. A better understanding on how to measure the true age of an individual or biological aging is an essential step that may lead to the definition of putative markers capable of predicting healthy aging. Objectives: The main objective of the INStitute for Prevention healthy agIng and medicine Rejuvenative (INSPIRE) Platform initiative is to build a program for Geroscience and healthy aging research going from animal models to humans and the health care system. The specific aim of the INSPIRE human translational cohort (INSPIRE-T cohort) is to gather clinical, digital and imaging data, and perform relevant and extensive biobanking to allow basic and translational research on humans. Methods: The INSPIRE-T cohort consists in a population study comprising 1000 individuals in Toulouse and surrounding areas (France) of different ages (20 years or over – no upper limit for age) and functional capacity levels (from robustness to frailty, and even dependency) with follow-up over 10 years. Diversified data are collected annually in research facilities or at home according to standardized procedures. Between two annual visits, IC domains are monitored every 4-month by using the ICOPE Monitor app developed in collaboration with WHO. Once IC decline is confirmed, participants will have a clinical assessment and blood sampling to investigate markers of aging at the time IC declines are detected. Biospecimens include blood, urine, saliva, and dental plaque that are collected from all subjects at baseline and then, annually. Nasopharyngeal swabs and cutaneous surface samples are collected in a large subgroup of subjects every two years. Feces, hair bulb and skin biopsy are collected optionally at the baseline visit and will be performed again during the longitudinal follow up. Expected Results: Recruitment started on October 2019 and is expected to last for two years. Bio-resources collected and explored in the INSPIRE-T cohort will be available for academic and industry partners aiming to identify robust (set of) markers of aging, age-related diseases and IC evolution that could be pharmacologically or non-pharmacologically targetable. The INSPIRE-T will also aim to develop an integrative approach to explore the use of innovative technologies and a new, function and person-centered health care pathway that will promote a healthy aging.

Key words: Gerosciences, integrated care, biological aging, intrinsic capacity, biology of aging, translational research on aging.


 

Introduction

Aging is an important risk factor for several adverse health outcomes, particularly chronic and metabolic diseases and intrinsic capacity (IC) decline. Since chronological age differs from biological aging, operationally defining biological aging is an essential aspect to understand the interplay between aging and health outcomes. Individuals progress differently in the aging process (“normal” aging vs “accelerated” aging), which means, biological aging is a heterogeneous process. In this context, we need to develop researches to identify biomarkers of aging and healthy aging, and know how to measure biological aging. According to the Geroscience field, understanding aging and the links with age-related diseases would contribute to prevent and/or delay the onset of various diseases and the decline in IC domains, in particular in the six operational IC domains crucial for independent living defined by the World Health Organization (WHO) (mobility, cognition, psychological, vitality, hearing and vision capacities) (1-3).
The WHO has recently published the Integrated Care for Older People, ICOPE handbook Guidance, to support Healthy Aging and to propose to health-care providers appropriate approaches to detect and manage declines in IC. With this integrated and individualized approach, WHO aims to reduce the number of dependent people by 15 million Worldwide by 2025 (4-7).
Studying concomitantly biomarkers of aging and the natural history of IC evolution in people of different ages and functional status is to date very challenging to understand the relation between biological aging and health outcomes. In this context, the INSPIRE program was built to foster research in the field of Geroscience and healthy aging. INSPIRE is a research program dedicated to biological and healthy aging, aimed at constituting a bio-resource platform going from animals to humans, from cells to individuals, from research to clinical care. INSPIRE will provide clinical, biological and technological resources for research and development on aging. The resources will be open to both academic and industry worlds in order to promote healthy aging and prevent dependency. It is a public-private initiative that brings together internationally recognized experts from basic and translational science (in particular, in the fields of immunology, metabolism, neurosciences and mesenchymal stem/stroma cells), clinical gerontology (i.e., researchers, but also physicians and nurses involved in clinical care), primary care and public health (8).
One of the main challenges of INSPIRE is to identify markers capable of determining biological aging with the implementation of human and animal cohorts. The INSPIRE Human Translational Cohort (INSPIRE-T cohort) will recruit about 1000 individuals of several chronological ages (from 20 years to 100+) and functional capacity levels (from robust to frail, and even disabled) with baseline and follow-up biological, clinical, imaging and digital data over 10 years. These data should allow us to explore and identify a set of biomarkers of aging, age-related diseases and IC evolution. In addition, the INSPIRE-T cohort aims: i/ to test the feasibility and acceptability of a new app for smartphone and tablet developed to monitor the six IC domains (locomotion, cognition, vision, hearing, vitality/nutrition, psychological status) according to the WHO recommendations; and ii/ to explore the development of digital markers of aging. This paper describes the study design of the INSPIRE-T cohort.

 

Material and Methods

Study design

The INSPIRE-T cohort, started in October 2019, is a 10-year observational study. The study population will consist of 1000 subjects recruited in the city of Toulouse and surrounding areas, South-Western France, and covering the age range of 20 years and over (no upper limit for age). Several follow-up visits will be regularly scheduled during the 10-year period of this study. Additional visits will be conditioned by the remote monitoring of IC and the onset of other major clinical conditions.
At baseline, and then once a year, diversified data (clinical, digital, imaging) and biospecimens (blood, urine, saliva and dental plaques) are collected following standardized procedures. Data collection is performed in the Clinical Research Center (CRC) of the Gerontopole – CHU Toulouse. It can also be performed in participants’ home (for more frail and disabled volunteers), or in selected Gerontopole’s collaborating centers by a mobile research team trained by the CRC. Participants are assessed by appropriately trained clinical research members.
Between yearly waves of data collection, participants are asked to record major clinical information, including adverse events (e.g. new diagnosis, SARS COV-2 diagnosis, influenza, fracture…), medical consultations, hospitalizations, and changes in the drug prescription every 4-months. They also have the six IC domains monitored (with or without the help of a caregiver) (ICOPE program Step 1) (4,7) in either the application developed in collaboration with WHO (ICOPE Monitor app) or a web platform; or through a phone call by a Gerontopole’s trained research nurse. When declines are detected in the ICOPE Step 1, a phone call is organized by the research nurse within one week to confirm this decline and to investigate the causes in collaboration with the medical research team. Once an IC decline is confirmed, participants have a thorough clinical assessment following the recommendations of the ICOPE Step 2 (4,7) and blood sampling (data are collected by research nurses in a home visit or at the research facility). Such information will enable us to investigate the response of some markers of aging at the time declines are detected. The clinical assessments and biomarkers’ exploration also allow us to propose a personalized prevention care plan to maintain function according to the recommendations from the WHO ICOPE program for usual care (ICOPE Step 3) (4,7).
Participants are trained to monitor their IC during the baseline visit by the Gerontopole’ research team. The remote monitoring of IC will last the whole length of this research study, i.e., up to ten years. The figure 1 shows schematically the study procedures over one year. Table 1 describes the study flow chart with all data collected at each time point during the follow-up.
To ensure quality of data collected, standard operating procedures are implemented covering subject’s recruitment, biobanking, remote monitoring of IC, clinical assessments and digital data collection. All data are collected in the INSPIRE-T database. Preventive strategies to limit errors like miscoding, missing values, are applied before data entry to ensure the validity and quality of the performed data analysis. Tools will be implemented for data exploration and data sharing between INSPIRE consortium researches and later on with external scientists.

Table 1
The INSPIRE Human Translational Research cohort flow-chart

a. The cognitive composite score will be realized only in people lower than 70 years; b. Other examinations are proposed to a limited number of participants in a volunteer basis

Figure 1
INSPIRE-T study procedures over one year. The remote monitoring of intrinsic capacity will last the whole length of this research study, i.e., up to ten years

 

Objectives

The main objective of the INSPIRE-T cohort is the appropriate data collection of key variables and biospecimens for at least 1000 people at baseline and 800 people with at least four years of follow-up (i.e. four yearly post-baseline assessments) over the 10-year study. The key variables are clinical data on all six IC domains (locomotion, cognition, vision, hearing, vitality/nutrition, psychological status), and the collection of blood, urine, saliva and dental plaque samples. Secondary objectives include: i/the identification of (a set of) biomarkers of aging through the constitution of a comprehensive biobank; ii/the assessment of the feasibility and acceptability of the ICOPE Monitor app used to measure and monitor intrinsic capacity; iii/ the study of the evolution of IC domains over time and its association with health outcomes; and finally, iv/ the study of the correlation between digital biomarkers to biological/imaging biomarkers and IC domains (Figure 1, online consultation).
A mouse cohort in mirror of the human INSPIRE-T cohort is being built in order to cross the results of translational research found in humans on aging animal models, and vice versa (8). The main objective of the INSPIRE Animal cohort is to define the relationship between the molecular mechanisms of cell premature senescence and frailty/accelerated aging (8).

Study population

We will recruit about 1000 subjects, men and women, aged 20 years-old or over (no upper limit for age), and affiliated to a social security scheme. People having a severe disease compromising life expectancy at 5 years (or at 1 year for subjects living in nursing homes) and people deprived of their liberty by administrative or judicial decision, or under guardianship, are excluded. Recruitment is stratified per 10-year age groups, oversampling older people in order to be able to investigate major clinical events (e.g., declines on IC, onset of age-related diseases).
Due to the heterogeneity of biological aging, we opted for no too stringent eligibility criteria. By diversifying our recruitment sources and monitoring key risk factors for accelerated aging (e.g., age, obesity, frailty, and activities of daily living), we will be able to recruit participants with different trajectories of aging.
Sample size calculation was not relevant as many objectives of the INSPIRE-T cohort are exploratory. We therefore considered an approach based more on the potential of the INSPIRE-T cohort in terms of the ability to obtain parameter estimates with sufficient precision with a recruitment of 1000 subjects that corresponds to the maximum number of subjects that can be recruited and monitored with the funding provided. In case of evident underpowered population (for a particular subgroup of subjects), a reasoned additional recruitment of subjects may be considered in a second phase. To limit the attrition rate, subjects will be monitored by both active (visits, telephone calls) and passive ways (monitoring of several functions using new technologies via mobile phones or other connected devices).

Data collection

From all subjects enrolled, investigations include data collection at baseline and during follow-up visits (annual visits and additional visits planed in case of decline in IC). Upon written informed consent, the following set of information is obtained by using a standardized questionnaire:
• Demographic information: marital status, education, occupation and housing conditions, use of healthcare services;
• Physical examination comprising measurement of the following classical markers: medical history, medication, vaccination, current diseases, body mass index, waist and hip circumference, heart rate, blood pressure, self-reported visceral pain, skin elasticity (cutometer measurement), cutaneous itching/pruritus;
• Lifestyle information: physical activity, sedentarity time, smoking, alcohol consumption, solar exposure;
• Fried frailty phenotype (9);
• Functional status: Activities of Daily Living (ADL) (10) and Instrumental Activities of Daily Living (IADL)(11);
• Cognitive status: Mini Mental State Examination (MMSE) (12) and for people lower than 70 years, neuropsychological tests including free and total recall of the Free and Cued Selective Reminding Test (13), ten MMSE (12) orientation items, the Digit Symbol Substitution Test score from the Wechsler Adult Intelligence Scale—Revised (14), and the Category Naming Test (15) (2-minute category fluency in animals);
• Nutritional status: Mini Nutritional Assessment (MNA) (16), food frequency questionnaire (17);
• Oral status: Oral Health Assessment Tool (OHAT) (18);
• Depressive symptoms: Patient Health Questionnaire (PHQ-9) (19);
• Physical performance: Short Physical performance battery (20) and chair rise test (30 seconds)(21-22);
• Participant-reported outcome for cognition (CFI) (23) and mobility, fatigue, and social isolation (PROMIS) (24);
• Objective physical activity and sleep parameters (parameters are collected for one week using activPAL accelerometer);
• Vision: WHO simple eye chart, and the AMSLER Grid;
• IC domains (ICOPE Step 1) by using the ICOPE Monitor app. This app will be used throughout the study for the remote (at-distance) evaluation and monitoring (self-monitoring). All cut-offs operationalizing a deficit in IC comes from the WHO ICOPE program (4,7). At the first visit, the research team explains to the participants how to use the ICOPE Monitor app and monitor their IC domains over time. At each annual regular visit, the research team will confirm participants apply the correct evaluation procedures for assessing their IC. The 6 domains of IC evaluated by the ICOPE Monitor app are:
o Mobility measured by the time (in sec) spent to raise from a chair, at 5-repetition at a maximum speed. Declines will be considered when the time needed to complete the test is higher than 14 sec.,
o Cognitive measured by the 3-word remember test of the MMSE (12) and the following questions: Do you have problems with memory or orientation (such as not knowing where one is or what day it is)? Did you notice a worsening of these disorders in the last 4 months or since the last evaluation? What is the full date today? (day, month, year, day of the week). For the 3-word remember test, three different sets of words will be used to avoid memory bias between two close assessments. Declines are present if the individual is unable to remember at least one word or if he/she provide a wrong response to the orientation question,
o Psychological measured by the following two questions: Over the past two weeks, have you been bothered by: 1. Feeling down, depressed or hopeless? 2. Little interest or pleasure in doing things? One “YES” response determines a decline,
o Vitality/nutrition measured by the following two questions: Have you unintentionally lost more than 3 kg over the last 3 months? Have you experienced loss of appetite? One “YES” response determines a decline. One further question will be asked: what is your actual weight (in kilograms)?
o Sensorial-hearing measured by the Whisper test according to the following procedures: the evaluator must 1/stand about an arm’s length away behind and to one side of the person; 2/ ask the person or an assistant to close off the opposite ear by pressing on the tragus (the tragus is the projection in front of and partly covering the opening of the ear); 3/ Breathe out and then softly whisper a word with two syllables (a set of words will be selected by the Inspire research team), use a common word; 4/Ask the person to repeat the word; and 5/ Move to the other side of the person and test the other ear, use a different word. Not repeating the correct words determines a decline. If the Whisper test can’t be realized, two questions are asked: Did you notice a worsening of these disorders in the last 4 months or since the last evaluation? Does your family complain an acute recent hearing loss?
o Sensorial-vision measured by the following questions: Do you have any problems with your eyes: difficulties in seeing far, reading, eye diseases or currently under medical treatment (e.g. diabetes, high blood pressure)? Declines are considered present when a person responds «yes» to this question and if she did not recently consult an ophthalmologist.

Other examinations are proposed to a limited number of participants (all age ranges and functional status) in a volunteer basis: Dual energy X-ray absorptiometry (DXA) for body composition assessment; Whole body and brain magnetic resonance (MRI); cardiorespiratory fitness (maximum oxygen consumption (V02 max) with blood sampling before and after the effort, and maximal aerobic power), and isokinetic muscle strength. These examinations are proposed annually for the DXA and, every two years for the other tests (MRI, VO2 max, Isokinetic muscle strength). Participant-reported outcome for sarcopenia (SARQoL) (25) is completed for volunteers who perform cardiorespiratory fitness exploration.

Digital assessments

Innovative digital assessments are also planned to be tested, such as home sensors (e.g., for measuring walking speed and its variability in daily environment), automated video analysis of mobility, and 3D facial images for the detection of digital markers of aging. A subgroup of 100 patients monitored by ambient sensors at home or sensors worn on the wrist over the long term will allow to remote and continuous monitoring of the trajectories of the IC domains (especially mobility, sleep parameters and nutrition) (CART/SmartHome research ancillary study, legal authorizations in process). This sub-study, developed in partnership with the CART research project team in United States (ORCATECH Team, Oregon Health and Science University, OR, USA; PI, Jeffrey Kaye; www.ohsu.edu) will allow us to detect subtle changes that are not clinically perceptible, well before the appearance of signs and symptoms and therefore determine innovative digital biomarkers and decision thresholds. These digital biomarkers will be correlated with clinical data but also biological and imaging biomarkers.

Biobank

Biospecimens are collected during the INSPIRE-T cohort for the creation of a biobank.
Biospecimens, including blood, urine, saliva, dental biofilm, are collected from all subjects at baseline and then, annually (the genotyping sample will be collected only at the baseline visit). Nasopharyngeal swabs and cutaneous surface samples are collected from all subjects every two years. Feces, hair bulb, and skin biopsy, are collected optionally at baseline visit (see Table 2).
Aliquots of biological material are stored at -80°C (dental biofilm, saliva, serum, plasma and urine) or at -196° C liquid nitrogen (PBMC) at the central lab (CRB TBR, CHU Toulouse/IFB PURPAN, Toulouse, France). Analysis will be either performed in Toulouse by the local biological teams involved in the INSPIRE project or by any third party not yet determined. The modality of Laboratory Data Transfer from the central lab to other parties will be defined at a later stage. Samples from the biobank may be moved to other US and European countries if required.
The INSPIRE-T biobank is supervised by the CRB TBR where all measures are taken to ensure a quality service based on appropriate resources and adequate safety procedures: observance of Good Laboratory Practice guidelines (the CRB TBR is certified AFNOR since 2015), fully-equipped premises, appropriate, approved and safe equipment (17 freezers -80°C Eppendorf Cryocube, 2 liquid nitrogen tanks with manual and documented filling, Vigitemp probes provide metrological tracking), qualified personnel, safety test and system implementation, sample traceability (all of biological collections are tracked in a specific software (TD Biobank), and CHU servers are daily backed up). All freezers are equipped with an alarm system. Equipments are monitored three times per day. Every failure is reported in the Kalilab software as non-compliance statements.
All the participants will be tested for SARS COV-2 infection via serological tests from blood collection when these latter will be available.
All biological samples are processed within 110 min following a protocol elaborated for INSPIRE purpose and split into smaller aliquots at the INSPIRE-T biobank (Figures 2 &3, online consultation).

Table 2
Samplings proposed to the INSPIRE Human Translational Research Cohort participants for the creation of the biobank

 

Blood collection

For blood collection, all subjects are asked to donate blood (60 ml) by venipuncture after overnight fasting. The blood sample is processed to obtain whole blood, plasma, red blood cells, serum and peripheral blood mononuclear cells (PBMC).
For whole blood and serum, samples are immediately shipped after collection at room temperature to the CRB TBR for the preparation of whole-blood and serum aliquots for freezing at -80° in the INSPIRE-T biobank.
For PBMC, blood samples are immediately transported to the CRB TBR at room temperature and treated within 24 hours from time of collection. PBMC are collected after density gradient-based separation, counted and frozen at 8-14 millions/cells per vial. Frozen vials will be stored in liquid nitrogen.
For plasma and RBC (EDTA/Lithium Heparin/BDP100 Blood), aliquots are immediately prepared after collection in the CRC and stored at -80°C until their shipment to the INSPIRE-T biobank.
When visits are organized by the mobile research team, some blood samples are not performed to limit quality procedures deviations (it concerns the Lithium Heparin tube, the 2 whole blood EDTA tubes and the BD P100 blood tube).

Urine collection

Participants are asked to collect at least 20 ml urine in a sterile screw-top container. The obtained volume is transferred into two vacutainer tubes of 10 ml each and directly shipped at room temperature to the CRB TBR where urine aliquots of 1 ml are prepared and stored at -80°C in the INSPIRE-T biobank.

Saliva

Participants are asked to collect 10 ml saliva in 50 ml Falcon tube (at least 30 min after a meal). The Falcon tube is immediately shipped at room temperature to the CRB TBR where saliva aliquots of 1 ml are prepared and stored at -80°C in the INSPIRE-T.

Dental biofilm collection

Biofilm sampling consists in recovering the biofilm from the external surfaces of the teeth (from natural teeth in priority, from prosthetic teeth if not possible), at the juxta-gingival level by curettage at 4 sites distributed over the dental arches: a sample from the upper anterior teeth, a sample from the upper posterior teeth, a sample from the lower anterior teeth, a sample from the lower posterior teeth. The product of each curettage is individualized in a sterile 1 ml cryotube. The four cryotubes are frozen at -80° in the CRC after the collection and regularly shipped to the CRB TBR.

Nasopharyngeal swabs

Nasopharyngeal swab will be addressed to the Institute of Biology of the CHU Toulouse within 4 hours from time of collection for their analysis (detection and identification of multiple respiratory viral and bacterial nucleic acids). Residuals samples will be stored at -80° to the CRB TBR in the INSPIRE-T biobank.

Skin swab and stripping

Swab samples are done on a skin exposed area (posterior face of the forearm) and a non-exposed area (lower back). Specimens are stored immediately at -80°C in the CRC. Frozen tubes are regularly shipped to the CRB and stored at -80°C in the INSPIRE-T biobank.
In addition, two 14 mm diameter D-squames are applied successively on the exact same area of the posterior face of the forearm: the first one is discarded and the second one is stored in a 2 ml tube. The same procedure is performed on the lower back. Both tubes are regularly shipped to the CRB and stored at -80°C in the INSPIRE-T biobank.

Feces collection (optional)

Feces are collected at the first visit and immediately stored at -80°C. If it is not possible, the participant can return to the research facility within one week with its frozen sample in a coproculture pot, placed in a cool box. The frozen feces samples are regularly shipped to the CRB TBR and stored at -80°C in the INSPIRE-T biobank.

Hair bulb collection (optional)

Twenty hairs are taken with the bulb and immediately stored after the collection in a sterile 2 ml cryotube in the CRC until their shipment to the INSPIRE-T biobank.

Skin biopsy (optional)

A 4 mm skin biopsy is obtained by using a punch. Skin samples are prepared according two different procedures: half of the samples are immediately rinsed, dried and stored at -80°C until its shipment to the CRB TBR; the other are immediately placed in a cryotube with PBS for cells cultures to organize a biobank of skin fibroblasts.
A biobank scientific committee will be set up, in the aim of determining the scientific directions and research priorities, of evaluating ongoing projects and their state of progress, and of resolving any methodological and ethical concerns raised by the studies. It shall i/examine the relevance, feasibility and conditions of implementation of the propositions concerning any analyses; ii/ ensure that national and international partnerships are made formal; iii/ control use of data, especially sample use, and iv/ ensure that participants rights are protected. The data disclosed will be made anonymous (coded, traceable data).

Statistical methods

Since the primary outcome measure of the INSPIRE-T cohort is related to reaching prespecified numbers for recruitment and retention, we will use numbers and percentages. Hypothesis-testing statistics will be employed for some of the secondary outcome measures and the new hypothesis arising through the 10 year duration of the INSPIRE program. Specific statistical analysis plan (SAP) will be written to answer each research question. Big data methods of analysis will be considered when examining the large and diversified amount of data that will be gathered from clinical and para-clinical evaluations, biospecimens, and digital assessments.
Significance will be set at p ≤ 0.05. Analyses will be performed using Stata (v14, StataCorp), SAS (v9.4, Cary, NC, USA), and R (v3.5.2). Statistical analyses will be done by researchers of the Inspire program and professional statisticians. Analyses by gender will be conducted.

Ethical and regulatory considerations

The INSPIRE-T cohort is carried out in accordance with the declaration of Helsinki, which is the accepted basis for clinical study ethics, and must be fully followed and respected by all engaged in research on human beings. The INSPIRE-T cohort protocol has been approved by the French Ethical Committee located in Rennes (CPP Ouest V) in October 2019. This research has been registered on the site http://clinicaltrials.gov (ID NCT04224038).

 

Current progress of the INSPIRE -T cohort

Recruitment status

The first participant was recruited on October 16 2019. Our objective is to recruit at least, 1000 people at baseline (500 during the first year and 500 during the second year of the project) from 20 onwards, including robust, prefrail and frail older adults, as well as disabled people, to be able to better understand the biology of aging across age-ranges and functional status. All the recruiting work is currently carried out by the Toulouse Gerontopole research team on a single site; a mobile clinical research team is also currently active to recruit frailer population (e.g. people unable to come to research facilities) in Toulouse and surrounding areas. Current inclusion rates are 4 participants per day. This rate will allow us to reach our objective of 1000 inclusions in 2 years. Two hundred and forty participants have been included by March 13 2020 (137 women / 103 men; mean age: 74.6 years), and 400 new inclusions are planed until September 2020. Among the 240 enrolled participants, 168 are robust, 60 prefrail and 6 frail with Fried criteria (9). All participants gave their consent for the complete biobanking, 112 participants have accepted the skin biopsy, 231 hair bulb collection and 216 feces collection. All subjects have accepted the DXA, and 211 VO2 max and muscle strength assessment. The sub-study on MRI is planned to start on September 2020. However, recruitment has been temporarily suspended during the COVID-19 pandemic.

Recruitment strategies

Our first plans were to recruit a representative sample of users of primary care services, by inviting people to participate using patients’ list of several family physicians in different areas (with different deprivation levels) of Toulouse (all patients aged 20 years or over being invited to be screened for participation). However, this recruitment approach proved to be unfeasible, mainly because many physicians have been very busy taking care of several viral pathologies during winter 2019-2020 (including COVID-19 from February 2020) (26, 27). Consequently, we decided to diversify the sources of recruitment.
Current recruitment relies mainly on the following strategies: flyers, community outreach strategies, media coverage, newspaper advertising, posters, online promotion, mass mailing, presentations at public events, conferences, study website, dissemination through institution newsletters, identification of participants from previous studies or existing registries, onsite recruitment /medical records review (by investigators/clinical research assistants), dissemination through health care providers : coordination with primary care, memory centers, hospital outpatient clinics, medical centers, physicians (site investigators, primary care physicians), specialists, hospital inpatient lists, private clinics, and finally, dissemination through residential homes, and nursing homes. The recruitment channels of the participant included (and planed over the next 6 months) is detailed in Table 3. Applied strategies are constantly followed and adapted if necessary throughout the recruitment study period (weekly meeting with investigators and study staff).

Table 3
Recruitment strategies implemented in the INSPIRE Human Translational Cohort

 

A mobile research team was implemented in January 2020 to recruit frailer population by collaborating with residential homes, long-term care facilities and post-acute and rehabilitation facilities. Next collaborations are considered with the CRCT in Oncopole-Toulouse (an institution dedicated to cancer research and care) and a private clinic focused on the management of obese people.
Retention strategies are implemented in parallel. It consists of participant-centered values and strategies including (but not limited to) identify proxy contacts, minimize waiting time during study visits, facilitate transportation from and to research facilities, adapt comfortable waiting room facilities, build relationships with study participants; remind nonresponsive participants (contact via phone or email, make phone calls during optimal hours; offering regular feed-back during the follow-up (mailing study updates); offering regular gadgets during the follow up and postcards.

Perspectives

The INSPIRE-T cohort will gather clinical, biological (including imaging), and digital data for subjects of several chronological ages and functional capacity status regularly followed over up to 10 years. One of the most innovative aspects of the INSPIRE-T cohort is that, through a close monitoring of participants with the ICOPE Monitor app, we will obtain clinical and biological data at the moment declines in IC come up. The cohort will provide us the needed resources to improve our understanding of the biological mechanisms of aging and the natural history of loss of IC leading to dependency during aging. By following and monitoring the IC of participants over time, this study will provide information about a new, function-centered healthcare pathway, which would agree with WHO recommendations for an integrated care for older people. At the medium term, this data may inform the development of a pragmatically interventional study testing the effects of this new healthcare pathway on clinical outcomes in older people; this healthcare pathway may be integrated in daily practice in healthcare systems, becoming thus the usual care. Innovative digital solutions (including sensors) proposed in the INSPIRE-T cohort are a promising way to remotely collect and analyze real-life and continuous health related data and thus longitudinal trajectories over time. It makes it possible to detect subtle variation in the IC before a clinical event.
The INSPIRE-T cohort will also perform relevant and extensive bio banking to allow basic and translational research in humans in the field of Geroscience and Healthy Aging. The INSPIRE-T biobank might lead to improving our understanding about molecular and physiological mechanisms involved in healthy aging, interacting with changes linked to specific chronic diseases. This may contribute to establish a set of biomarkers, that could be pharmacologically or non-pharmacologically targetable, and that would characterize biological aging and, then, permit to identify an accelerated aging phenotype. In their recent paper, Ahadi S et al (28) have defined different types of aging patterns in different individuals, termed “ageotypes”, on the basis of the types of molecular pathways that changed over time in a given individual. According to the authors, “ageotypes” may provide a molecular assessment of personal aging, reflective of personal lifestyle and medical history that may ultimately be useful in monitoring and intervening in the aging process”. One of the main objectives of the INSPIRE-T cohort is to identify biological markers that could detect the inter-individual variability of biological processes before it becomes clinically perceptible (29). The identification of biomarkers of aging may help us to identify individuals who are with a high risk of developing age-associated diseases, decline in IC or disability, and to propose personalized strategies, including innovative therapeutics, to prevent or restore impaired functions. Our clinical and biological data will give the opportunity to explore the interaction between changes with aging on inflammation, metabolism, gerosciences in general, and neurodegenerative process leading to Alzheimer’s disease (30, 31) or physical frailty (32), two major causes of loss of functions. The INSPIRE-T cohort will benefit from the availability of plasma neurodegenerative biomarkers (plasma amyloid beta 42/40, neurofilaments, plasma phospho tau) (31). The development of biological markers of frailty is also required to improve the treatment of frail individuals. The etiology of frailty is complex. Proposed biomarkers of frailty include markers of inflammation. As recently proposed by the ICSFR Task Force perspective on biomarkers for sarcopenia and frailty, «machine learning and information technology innovation could thus be used to develop risk scores that could be used in clinical and research settings. Other technologies, such as induced pluripotent stem cells (iPSCs) or skin fibroblasts, could be used to study markers of senescence and could also enable a move towards personalized medicine» (32). Interventions to promote healthy aging will be more effective in people with a risk of decline (29). Hallmarks of aging are under scrutiny in particular DNA alteration, epigenetics, unusual protein production, senescent cells secreting pro-inflammatory factors and others. New therapies aim to target senescent cells or their secretory proteins (the senolytic molecules) and therefore promote healthy ageing are presently under development (33-36).
Finally, the INSPIRE-T cohort gives us the opportunity to federate clinical and biological research teams in Toulouse and Occitania Region to build a research platform of gerosciences discovery to explore mechanisms of aging, and to implement comprehensive translational projects towards the goal of preventing the consequences of aging for a healthy, and long-lived society (37). The animal cohort, generated to “mirror” the human translational cohort, will facilitate the translation of results from basic research to humans and to the clinics. The identification of markers of aging will take advantage of three complimentary approaches to look for the best markers of aging: without a priori approaches (transcriptomics, proteomics, metabolomics); semi a priori approach (metabolism, inflammation, cell cycle, mitochondrial network…); and targeted approach (pre-identified targets such as (but not limited to) Growth Differentiating Factor 15 (GDF-15), apelin, senescent cells, amyloid protein in plasma) (38). From a biological viewpoint, the function-centred approach recommended by WHO represents a challenge due to the multidimensionality that characterizes IC’ trajectories during aging. We will develop an integrative view of biological aging (Figure 2). Three classes of parameters transversal to the whole organism, present in all organs, strongly interrelated and crucial in tissue homeostasis have been selected: i) inflammation and immunity that represents both a warning signals and the house keeping guard of tissue integrity, ii) mesenchymal stem/stroma cells (MSC) allowing support for all function and their adaptation and iii) metabolism that controls any cell decision and the fate of most of them. For all these transversal components, senescence mechanisms will be carefully investigated.

Figure 2
The INSPIRE approach: an integrative view of biological aging

 

Due to the Covid19, teleconsultation has been added for the pre-inclusion and some of the assessment, we will be able also to assess the” stay at home order” on the INSPIRE-T cohort subjects (39).
In conclusion, the INSPIRE-T cohort, nested in the INSPIRE Platform, will contribute to healthy aging and dependency prevention. The INSPIRE-T cohort will foster discoveries of human markers (i.e., biological, clinical, digital) of healthy aging capable of predicting functioning and resilience.

 

Acknowledgments: The Inspire Program is supported by grants from the Region Occitanie/Pyrénées-Méditerranée (Reference number: 1901175), the European Regional Development Fund (ERDF) (Project number: MP0022856), MSD Avenir and the Inspire Chairs of Excellence funded by: Alzheimer Prevention in Occitania and Catalonia (APOC), EDENIS, KORIAN, Pfizer, Pierre-Fabre.
Conflict of interest: All authors of the paper “The INSPIRE research initiative: a program for GeroScience and healthy aging research going from animal models to humans and the healthcare system” declare no Conflicts of Interest related to this manuscript.
Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

 

SUPPLEMENTARY MATERIAL

 

References

1. Gill TM. Translational Geroscience: Challenges and Opportunities for Geriatric Medicine. J Am Geriatr Soc. 2019 Sep;67(9):1779-1781.
2. Ferrucci L, Gonzalez-Freire M, Fabbri E, Simonsick E? Tanaka T, Moore Z, Salimi S, Sierra F and de Cabo R. Measring biological aging in humans : a quest. Aging Cell 2020 Feb; 19(2): e13080.
3. Beard JR. Editorial: Linking Geroscience and Integrated Care to Reinforce Prevention. J Prev Alzheimers Dis. 2020;7(2):68-69
4. WHO | WHO Guidelines on Integrated Care for Older People (ICOPE) [Internet]. WHO. [cited 2019 Jan 25]. Available from: http://www.who.int/ageing/publications/guidelines-icope/en/
5. Geneva: World Health Organization; 2017. Integrated Care for Older People: Guidelines on Community-Level Interventions to Manage Declines in Intrinsic Capacity.
6. Vellas B, Scrase D, Rosenberg GA, Andrieu S, Araujo de Carvalho I, Middleton LT. Editorial: WHO Guidelines on Community-Level Interventions to Manage Declines in Intrinsic Capacity: The Road for Preventing Cognitive Declines in Older Age? J Prev Alzheimers Dis. 2018;5(3):165-167.
7. Takeda C, Guyonnet S, Sumi Y, Vellas B, Araujo de Carvalho I. Integrated Care for Older People and the Implementation in the INSPIRE Care Cohort. J Prev Alzheimers Dis. 2020;7(2):70-74
8. de Souto Barreto P, Guyonnet S, Ader GI, Andrieu S et al for the INSPIRE Program Group. The INSPIRE research initiative: a program for GeroScience and healthy aging research going from animal models to humans and the healthcare system. J of Frailty and Ageing. 2020 Doi: 10.14283/jfa.2020.18
9. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001 Mar;56(3):M146-156.
10. Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. Studies of illness in the aged. The index of ADL : a standardized measure of biological and psychosocial function. JAMA. 1963 Sep 21;185:914–9.
11. Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. The Gerontologist. 1969;9(3):179–86.
12. Folstein MF, Folstein SE, McHugh PR. ‘Mini-mental state’. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975 Nov;12(3):189–98
13. Grober E, Buschke H, Crystal H, Bang S, Dresner R. Screening for dementia by memory testing. Neurology. 1988 Jun;38(6):900–3.
14. Wechsler D. Wechsler adult intelligence scale—revised. New York: New York: Psychological Corp; 1981.
15. Cardebat D, Doyon B, Puel M, Goulet P, Joanette Y. [Formal and semantic lexical evocation in normal subjects. Performance and dynamics of production as a function of sex, age and educational level]. Acta Neurol Belg. 1990;90(4):207–17.
16. Guigoz Y, Vellas B, Garry PJ. Assessing the nutritional status of the elderly: The Mini Nutritional Assessment as part of the geriatric evaluation. Nutr Rev. 1996 Jan;54(1 Pt 2):S59-65.
17. Estaquio C, Kesse-Guyot E, Deschamps V, Bertrais S, Dauchet L, Galan P, et al. Adherence to the French Programme National Nutrition Santé Guideline Score is associated with better nutrient intake and nutritional status. J Am Diet Assoc. 2009 Jun;109(6):1031–41.
18. Chalmers J, Johnson V, Tang JH, Titler MG.Evidence-based protocol: oral hygiene care for functionally dependent and cognitively impaired older adults. J Gerontol Nurs. 2004 Nov;30(11):5-12.
19. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001 Sep;16(9):606–13.
20. Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, et al. A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol. 1994 Mar;49(2):M85-94.
21. Rikli RE, Jones CJ. Development and validation of criterion-referenced clinically relevant fitness standards for maintaining physical independence in later years. The Gerontologist. 2013 Apr;53(2):255–67.
22. Beaudart C, Rolland Y, Cruz-Jentoft AJ, Bauer JM, Sieber C, Cooper C, et al. Assessment of Muscle Function and Physical Performance in Daily Clinical Practice : A position paper endorsed by the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO). Calcif Tissue Int. 2019 Apr 10;
23. Li C, Neugroschl J, Luo X, Zhu C, Aisen P, Ferris S, et al. The Utility of the Cognitive Function Instrument (CFI) to Detect Cognitive Decline in Non-Demented Older Adults. J Alzheimers Dis JAD. 2017;60(2):427–37.
24. (PROMIS: http://www.healthmeasures.net/index.php?option=com_content&view=category&layout=blog&id=147&Itemid=806).
25. Beaudart C, Biver E, Reginster J-Y, Rizzoli R, Rolland Y, Bautmans I, et al. Validation of the SarQoL®, a specific health-related quality of life questionnaire for Sarcopenia. J Cachexia Sarcopenia Muscle. 2017 Apr;8(2):238–44.
26. Morley JE, Vellas B. Editorial : COVID-19 and older adults. J Nutr Health Aging 2020; 24(4): 364-365
27. Cesari M, Proietti M. Editorial : Geriatric medicine in Italy in the time of COVID-19. J Nutr Health Aging 2020; 24(5):459–460.
28. Ahadi S, Zhou W, Schüssler-Fiorenza Rose SM, Sailani MR, Contrepois K, Avina M, Ashland M, Brunet A, Snyder M . Personal aging markers and ageotypes revealed by deep longitudinal profiling. Nat Med. 2020 Jan;26(1):83-9
29. Guerville F, De Souto Barreto P, Ader I, Andrieu S, Casteilla L, Dray C, Fazilleau N, Guyonnet S, Langin D, Liblau R, Parini A, Valet P, Vergnolle N, Rolland Y, Vellas B. Revisiting the Hallmarks of Aging to Identify Markers of Biological Age. J Prev Alzheimers Dis. 2020;7(1):56-64
30. Sierra F.Editorial: Geroscience and the Role of Aging in the Etiology and Management of Alzheimer’s Disease. J Prev Alzheimers Dis. 2020;7(1):2-3
31. Bateman RJ, Blennow K, Doody R, Hendrix S, Lovestone S, Salloway S, Schindler R, Weiner M, Zetterberg H, Aisen P, Vellas B. Plasma Biomarkers of AD Emerging as Essential Tools for Drug Development: An EU/US CTAD Task Force Report. J PrevAlzheimers Dis. 2019;6(3):169-173. doi: 10.14283/jpad.2019.21.
32. Rodriguez-Mañas L, Araujo de Carvalho I, Bhasin S, Bischoff-Ferrari HA, Cesari M, Evans W, Hare JM, Pahor M, Parini A, Rolland Y, Fielding RA, Walston J, Vellas B. ICFSR Task Force Perspective on Biomarkers for Sarcopenia and Frailty. J Frailty Aging. 2020;9(1):4-8. doi: 10.14283/jfa.2019.32.
33. Childs BG, Gluscevic M, Baker DJ, Laberge R-M, Marquess D, Dananberg J, et al. Senescent cells: an emerging target for diseases of ageing. Nature Reviews Drug Discovery. 2017;16(10):718-35
34. Zimmer K. https://www.the-scientist.com/features/can-destroying-senescent-cells-treat-age-related-disease–67136.
35. Paez-Ribes M, González-Gualda E, Doherty GJ, Muñoz-Espín D. Targeting senescent cells in translational medicine.EMBO Mol Med. 2019 Dec;11(12):e10234. doi: 10.15252/emmm.201810234. Epub 2019 Nov 19. Review.
36. Khosla S, Farr JN, Tchkonia T, Kirkland JL. The role of cellular senescence in ageing and endocrine disease. Nat Rev Endocrinol. 2020 Mar 11. doi: 10.1038/s41574-020-0335-y. [Epub ahead of print] Review
37. Newman JC, Sokoloski JL, Robbins PD, Niedernhofer LJ, Reed MJ, Wei J, Austad SN, Barzilai N, Cohen HJ, Kuchel GA, Kirkland JL, Pignolo RJ. Creating the Next Generation of Translational Geroscientists. J Am Geriatr Soc. 2019 Sep;67(9):1934-1939
38. Justice JN, Ferrucci L, Newman AB, Aroda VR, Bahnson JL, Divers J, Espeland MA, Marcovina S, Pollak MN, Kritchevsky SB, Barzilai N, Kuchel GA. A framework for selection of blood-based biomarkers for geroscience-guided clinical trials: report from the TAME Biomarkers Workgroup. Geroscience. 2018 Dec;40(5-6):419-436. doi: 10.1007/s11357-018-0042-y. Epub 2018 Aug 27.
39. Ousset PJ, Vellas B. Impact of the Covid-19 Outbreak on the Clinical and Research Activities of Memory Clinics: An Alzheimer’s Disease Center Facing the Covid-19 Crisis. J Prev Alzheimers Dis (2020). https://doi.org/10.14283/jpad.2020.17

FRAMEWORK IMPLEMENTATION OF THE INSPIRE ICOPE-CARE PROGRAM IN COLLABORATION WITH THE WORLD HEALTH ORGANIZATION (WHO) IN THE OCCITANIA REGION

 

N. Tavassoli1, A. Piau1,2, C. Berbon1, J. De Kerimel1, C. Lafont1, P. De Souto Barreto1,2, S. Guyonnet1,2, C. Takeda1, I. Carrie1, D. Angioni1, F. Paris1, C. Mathieu1, P.J. Ousset1, L. Balardy1, T. Voisin1, S. Sourdet1, J. Delrieu1, V. Bezombes1, V. Pons-Pretre1, S. Andrieu1,2, F. Nourhashemi1,2, Y. Rolland1,2, M.E. Soto1,2, J. Beard3, Y. Sumi4, I. Araujo Carvalho4, B. Vellas1,2

 

1. Gerontopole, W.H.O Collaborative Center for Frailty, Clinical Research and Geriatric Training, Toulouse University Hospital, 31059 Toulouse, France; 2. UPS/INSERM, UMR1027, F-31073 Toulouse, France; 3. ARC Centre of Excellence in Population Ageing Research, University of New South Wales, Sydney, Australia; 4. Department of Maternal, Newborn, Child, Adolescent Health and Ageing, World Health Organization, Geneva, Switzerland.

Corresponding author: Neda Tavassoli, Équipe Régionale Vieillissement et Prévention de la Dépendance (ERVPD), La Cité de la Santé, Bâtiment Ex-Biochimie, Hôpital La Grave, Place Lange, TSA 60033, 31059 Toulouse Cedex 9, France, Phone number: +335 61 77 70 13, Fax number: +335 61 77 64 75, E-mail address: tavassoli.n@chu-toulouse.fr

J Frailty Aging 2020;in press
Published online May 19, 2020, http://dx.doi.org/10.14283/jfa.2020.26

 


Abstract

Introduction: Limiting the number of dependent older people in coming years will be a major economic and human challenge. In response, the World Health Organization (WHO) has developed the «Integrated Care for Older People (ICOPE)» approach. The aim of the ICOPE program is to enable as many people as possible to age in good health. To reach this objective, the WHO proposes to follow the trajectory of an individual’s intrinsic capacity, which is the composite of all their physical and mental capacities and comprised of multiple domains including mobility, cognition, vitality / nutrition, psychological state, vision, hearing. Objective: The main objective of the INSPIRE ICOPE-CARE program is to implement, in clinical practice at a large scale, the WHO ICOPE program in the Occitania region, in France, to promote healthy aging and maintain the autonomy of seniors using digital medicine. Method: The target population is independent seniors aged 60 years and over. To follow this population, the 6 domains of intrinsic capacity are systematically monitored with pre-established tools proposed by WHO especially STEP 1 which has been adapted in digital form to make remote and large-scale monitoring possible. Two tools were developed: the ICOPE MONITOR, an application, and the BOTFRAIL, a conversational robot. Both are connected to the Gerontopole frailty database. STEP 1 is performed every 4-6 months by professionals or seniors themselves. If a deterioration in one or more domains of intrinsic capacity is identified, an alert is generated by an algorithm which allows health professionals to quickly intervene. The operational implementation of the INSPIRE ICOPE-CARE program in Occitania is done by the network of Territorial Teams of Aging and Prevention of Dependency (ETVPD) which have more than 2,200 members composed of professionals in the medical, medico-social and social sectors. Targeted actions have started to deploy the use of STEP 1 by healthcare professionals (physicians, nurses, pharmacists,…) or different institutions like French National old age insurance fund (CNAV), complementary pension funds (CEDIP), Departmental Council of Haute Garonne, etc. Perspective: The INSPIRE ICOPE-CARE program draws significantly on numeric tools, e-health and digital medicine to facilitate communication and coordination between professionals and seniors. It seeks to screen and monitor 200,000 older people in Occitania region within 3 to 5 years and promote preventive actions. The French Presidential Plan Grand Age aims to largely implement the WHO ICOPE program in France following the experience of the INSPIRE ICOPE-CARE program in Occitania.

Key words: ICOPE program, older people, dependency, remote monitoring, STEP, intrinsic capacity, INSPIRE, Occitania, care implementation, clinical practice.


 

Introduction

The INSPIRE program was recently funded in Toulouse, France, which aims to identify the hallmarks of biological aging and allows us to propose, in the future, innovative therapeutics to prevent or restore impaired function (1). To achieve this objective, a Human Translational Cohort as well as an Animal cohort will be created to discover biomarkers of aging. The INSPIRE ICOPE-CARE program is a part of the INSPIRE program. Its main objective is to implement, at a large scale in the Occitania region, South-Western France, the WHO ICOPE program in the daily clinical routine. The ambition of INSPIRE ICOPE-CARE is to evaluate and follow about 200,000 older adults by 2025.
WHO defines the notion of healthy aging (2), not as having no pathology since diseases happen throughout life, but as being able to keep doing what we have reason to value for as long as possible. Healthy aging partly depends on the maintenance of optimal levels of intrinsic capacity during aging, intrinsic capacity being a combination of all mental and physical capacities. WHO has developed the Integrated Care for Older People (ICOPE) program, a function- and person-centered care pathway during aging (3); as WHO Collaborative center for frailty, clinical research and geriatric training, the Gerontopole of Toulouse University Hospital played an important role in its elaboration. This program was created based on the analysis of more than 500 major original publications and the recommendations of a committee on aging including experts from WHO and almost 50 international experts from research, care and the academic world.
The ICOPE program is a care pathway, which consists of a participative and integrated healthcare approach that takes into account the individuals’ capacities, their associated pathologies, the environment, their lifestyle, but also their wishes and aspirations. Emphasis is placed on the fact that the patient must be involved in his/her care and monitoring (4). In the ICOPE program, there are 5 steps in the care of the subject: STEP 1: Screen for declines in intrinsic capacity; STEP 2: Undertake a person-centered assessment in primary care; STEP 3: Define the goal of care and develop a personalized care plan; STEP 4: Ensure a referral pathway and monitoring of the care plan with links to specialized geriatric care; STEP 5: Engage community and support caregivers (Figure 1). The focus of the ICOPE program is on three important points: 1- the patient is centrally involved in his/her care and monitoring, 2- the care plan considers the importance of caregivers and the use of local resources offered by the community; 3- a large place is given to new technologies or “digital medicine” (3,4). Indeed, information and communication technologies are crucial in the current context of medical demographic constraints, as well as the need to continuously monitor large populations.

The objective of ICOPE program is to prevent or delay the onset, and decrease the severity of care dependency. The goal is to enable as many people as possible to age in good health. To reach this objective, WHO proposes to follow the trajectory of intrinsic capacity covering six operational domains: mobility, cognition, vitality / nutrition, psychological state, vision, hearing (5, 6).
The large INSPIRE Program has two principal objectives (1). The first main objective is to build a resource and research platform for Geroscience extending from animals to humans, from cells to individuals, from research to clinical care. Although chronological age (civil age, date of birth) has always been used as the operational definition of aging, it does not necessarily reflect the biological process of aging. The second main objective of INSPIRE program is to implement in clinical care the WHO ICOPE Program. In the current paper, we describe the methods of implementation of the ICOPE program in the context of the INSPIRE initiative, the « INSPIRE ICOPE-CARE program”.

Figure 1
5 Steps of WHO ICOPE program

 

Method

Objectives of the “INSPIRE ICOPE-CARE program”

The main objective of the INSPIRE ICOPE-CARE program is to implement, at a large scale in the Occitania region, South-Western France, the WHO ICOPE program in a daily clinical routine. Secondary objectives are to explore the acceptability of the INSPIRE ICOPE-CARE program by both older adults and health care professionals, as well as to examine the use of new digital tools in the evaluation and monitoring of intrinsic capacity.

Population

The target population in the INSPIRE ICOPE-CARE program is independent seniors aged 60 years and over in Occitania region, in France. The actors are healthcare professionals, trained professionals, but also caregivers and seniors themselves. Indeed, the STEP 1 tool may be used by any person who has undergone a training course on ICOPE. To follow this population, the six domains of intrinsic capacity are systematically monitored with pre-established tools (STEP 1, and then if appropriate STEP 2, STEP 3, STEP 4, STEP 5). This allows the health professionals to intervene quickly if a decline occurs in any domain.

STEP 1 – Screen for declines in intrinsic capacity

The first tool proposed by WHO to evaluate intrinsic capacity is a screening tool referred to as ICOPE STEP 1. It is very simple, and usable by actors who are not necessarily health professionals after a brief training course (Figure 2). It allows a rapid assessment of the six operational domains of intrinsic capacity by very simple tests. In the INSPIRE ICOPE-CARE program, this tool has been adapted by the Toulouse Gerontopole to become a tool capable of monitoring intrinsic capacity over time. Then, the adapted ICOPE STEP 1 was elaborated in digital format to make it possible to undertake remote monitoring in a large-scale.

Figure 2
WHO STEP 1 screening tool (from WHO with permission)

 

The mobile phone is the technology that has spread best among the older population and is therefore an ideal support to remotely screen or monitor health indicators (7). Thus, two tools were developed by the Toulouse Gerontopole: a) the ICOPE MONITOR, an application, which is an adapted version of the ICOPE WHO application, accessible via smartphone or tablet; and b) the BOTFRAIL, an internet conversational robot, accessible via computer, smartphone or tablet. These two complementary tools can be used in two modes: professional mode and self-assessment mode for the senior or his/her caregiver. Both are connected to the pre-existing Gerontopole frailty database created in 2016 to collect medical and socio-demographic data from frail older people who received a face to face standardized gerontological assessment in the Occitania region. Data from more than 6,000 patients in 180 different health centers have already been collected since 2017. The database complies with all French and European regulations in terms of health data security. The authorization of the French “National Commission for Data Protection” was granted on April 13, 2017 (Ref. Nb. MMS/OSS/NDT171027, authorization request Nb. 19141154).
These tools may be used by everyone. However, in the context of the INSPIRE ICOPE-CARE program, during the first (face to face) STEP 1 screening, the professional collects the senior’s oral consent to keep his/her data in the frailty database as well as to monitor his/her intrinsic capacity regularly. If the assessment is normal, lifestyle advice is provided by the professional who also trains the senior or his family/caregiver to use the tools in «self-assessment» mode.

Remote screening of STEP 1 – ongoing monitoring
The ongoing screening of intrinsic capacity deficits is based on a remote monitoring system. After having been taught by health professionals how to use the ICOPE MONITOR app and/or BOTFRAIL tool, seniors are invited to continuously use the STEP 1 every 4-6 months. If the senior cannot carry out the self-assessment, a professional will intervene every 6 months to perform the STEP 1 follow-up. STEP 1 data collected using the ICOPE MONITOR application or BOTFRAIL every 4 to 6 months are transmitted to the Gerontopole frailty database. If a deterioration in one or more domains of intrinsic capacity is identified during monitoring, an alert is generated by an algorithm. During the first deployment phase of the project, the management and processing of these alerts is carried out by the experienced nurses of the Gerontopole in collaboration with the primary care providers [General Practitioners (GP) and nurses]. When an alert is detected, the senior or family (as appropriate) will be contacted to verify the clinical relevance of the intrinsic capacity deficit. If the deficit is confirmed, the GP will be contacted to initiate STEP 2. This first phase makes it possible to evaluate the relevance of the alerts, adjust the algorithm and develop decision trees (Figure 3 & Table 1).

Figure 3
Diagram of the INSPIRE ICOPE-CARE program

 

Table 1
Tele-health supports and INSPIRE ICOPE-CARE program

Note. The follow-up is always digital (self-assessment / caregiver or nurse support). Depending on the geographical context and health resources, STEP 2 can be performed face-to-face or through telemedicine tools. The actors involved are also context-dependent; Note: Tele -consultation is a tele-health consultation between a doctor/nurse and the senior. Tele expertise is between two health professionals; General Practitioner, GP, geriatricians, G.

 

STEP 2 and STEP 3 – Undertake a person-centered assessment in primary care, define the goal of care and develop a personalized care plan

If the screening of intrinsic capacity is abnormal, STEP 2 (person-centered assessment) and STEP 3 (personalized care plan) are carried out by the GP or, if possible, by a nurse trained in geriatrics using the delegation of task as part of the “French protocol of cooperation” or the «Hospital outside the walls» care unit, as described below:
– The cooperation protocol was developed by the Gerontopole of Toulouse and the Occitania Regional Health Agency (ARS) and obtained the approval from the High Authority for Health (HAS) on December 4, 2013 (8, 9). It aims to delegate to a self-employed trained nurse (40 hours of training), the geriatric assessment of older people identified as frail. At the end of this assessment, the nurse, can immediately refer the person to the GP (in the case of warning signs or unexplained or multiple anomalies), to social services, appropriate health professionals (specialist physicians, physiotherapists,…) or themselves initiate preventive measures. The delegated nurse intervenes at the request of the GP after obtaining the consent of the patient. The nurse’s evaluations and proposed interventions are re-analyzed and discussed during a multi-professional concertation meeting with patient’s GP, organized no later than 30 days following the geriatric assessment. This model of care is funded by local health authorities. To date, more than 160 nurses have been trained in the Occitania region.
– The «Hospital outside the walls» care unit of Gerontopole is an innovative unit of care created in 2015 at the Toulouse University Hospital to take care of frail older people outside the hospital. The geriatric evaluation of the older people is carried out by experienced trained nurses of the Gerontopole at their homes or in public spaces close to their homes. These nurses, with the support of a hospital geriatrician, propose a personalized care plan to the older people evaluated. This plan is then sent to the person’s GP who ensures its implementation and follow-up. This model has been rolled out in other hospital centers in the Occitania region. To date seven hospitals in the region have their own «Hospital outside the walls» care unit.

STEP 4 – Ensure a referral pathway and monitoring of the care plan with links to specialized geriatric care

As mentioned above, monitoring consists of the repetition every 4-6 months of STEP 1, either by self-assessment or with the help of a family member or professional caregiver. Digital medicine used in the INSPIRE ICOPE-CARE program makes it possible to simultaneously monitor large populations regardless of where they live and the extent of local medical resources and can also ensure the implementation and follow up of the personalized care plan proposed in STEP 3. Thus, digital medicine allows to focus the action of the health professionals on those who need and when they need (efficient use of resources and personalized medicine) using a dashboard and by the generation of automatized and graduated alerts (the algorithm will evolve over time). When a coordination meeting is necessary between the GP and other health professionals especially nurses who realized STEP2 and STEP3, tele-health consultations may be used (called tele-expertise). To make it possible, we are deploying the use of a tele-health platform to facilitate access to this expertise throughout the region regardless of location. In the context of “complexes cases”, the GP may request a tele-consultation or tele-expertise with geriatricians and other physicians (e.g. psychiatrists) in the reference center. In these situations all the Gerontopole’s paramedical resources: physiotherapists, nutritionists, neuropsychologists and social workers may be involved, as well.
Lastly, digital remote monitoring tools are an excellent support for assessing adherence to the care plan, coordinate care, but also for providing information or educational content (nutrition, physical activity) to seniors.

STEP 5 – Engage community and support caregivers

This stage allows the establishment of an ecosystem favorable to «healthy aging». At this step, town halls, departments, and regions as well as several organizations (Departmental Councils, pension funds, insurances,…) can set up efficient organizations to encourage and promote «healthy aging». The INSPIRE ICOPE-CARE program is part of this step and plays an important role in bringing together different actors and organizations around the same objective which is the adaptation of our society to aging well.

Implementation of concrete actions in the Occitania region

The operational implementation of the INSPIRE ICOPE-CARE program in Occitania will be promoted by the network of Territorial Teams of Aging and Prevention of Dependency (ETVPD) which have more than 2,200 members composed of professionals in the medical, medico-social and social sectors. This Network was created in 2012 by the Gerontopole of Toulouse with the support of the Occitania Regional Health Agency (ARS). The objective of this network is to prevent dependency among seniors in Occitania by promoting care, training, research and innovation in gerontology. Several meetings take place every year in different territories in Occitania allowing to exchange with the actors of the field and to advance on innovative projects. The INSPIRE ICOPE-CARE program is currently the main project on which the territorial teams are working.
A number of targeted actions have started to facilitate the use of STEP 1 by healthcare professionals or different institutions:
Physicians: The GP has the principal role for the implementation of the intervention plan proposed to the senior in the INSPIRE ICOPE-CARE program. His/her adherence to the program is essential. We are currently working with the regional union of physicians and the University Department of General Medicine (DUMG) to establish a follow-up strategy adapted to the GP’s work.
Nurses: In the INSPIRE ICOPE-CARE program, the nurse, in connection with the GP, will coordinate the implementation of intervention plans. First, we started the implementation of the INSPIRE ICOPE-CARE program with our experienced nurses of the Gerontopole who work at the «Hospital outside the walls» care unit of Toulouse University Hospital. Since January 2019, these nurses have used the STEP 1 tool for all their patients; to date (March 2020), around 950 seniors have been assessed. Some preliminary data on step 1 in 755 subjects showed that mean age was 80.9 ± 7.3 years, 67.3% were female (n=298) and 699 (92.6%) had at least one domain of intrinsic capacity affected. Table 2 shows the results of the STEP 1 evaluations.
The nurses especially those trained on frailty assessment in the framework of cooperation protocol (more than 160 nurses) are also involved. Since January 2020, the Gerontopole has organized several training courses on the use of STEP 1 and ICOPE. To date, 94 nurses have been trained and 240 are registered for the next sessions. An agreement was signed between the Toulouse University Hospital and the Occitania Regional Health Agency to pay nurses 15 euros for this evaluation.

Table 2
STEP 1 analysis performed on the first 755 subjects evaluated

 

Pharmacists: In collaboration with the regional union of pharmacists and the pharmacy unit of Toulouse University Hospital, volunteer pharmacists and 6th year pharmacy students are also trained on the ICOPE program. To date (March 2020), 65 pharmacists have been trained and approximately 80 are registered for the next training sessions. The STEP 1 will be performed in the pharmacies by the pharmacists and in the event of an abnormal STEP 1, the pharmacist will direct the patient to his/her GP.
Institutions: A partnership is set up with CEDIP (CEntre D’Information et de Prévention – Agirc-Arrco), which is a complementary pension fund in France, to carry out STEP 1 for their beneficiaries. To date (March 2020), more than 300 seniors have been assessed. An analysis made on 207 subjects with usable data showed that mean age was 70.1 years, 61.8% were female (n=128) and 86.5% (n=179) had at least one domain of intrinsic capacity affected. The domain most affected was vision (64.7%) followed by hearing (60.9%) and cognition (41.5%).
A collaboration is developed with French National old age insurance fund (CNAV) to implement STEP 1 within the usual professional practices of home caregivers and create an innovative and specific prevention offer for young precarious retirees (62-70 years old).
Departmental Council of Haute Garonne is a partner of the Gerontopole of Toulouse. Their assessors are planned to be trained in June 2020 to carry out STEP 1 for all independent seniors who request them for a personalized autonomy allowance.
Several other actions are planned. A project is being developed with the French Mutual Insurance, which brings together the majority of existing mutual health insurance companies in France, to disseminate information about this program to primary healthcare providers. The Federation of Health Homes of Occitania (FORMS) was contacted to set up the INSPIRE ICOPE-CARE program in Health Homes. We are also collaborating with the Post Office, to set up an experiment in three cities in the Toulouse agglomeration in order to carry out STEP 1 by trained postmen from the Post Office. The experiment is due to start in September 2020. We are also working with spas, which receive a large number of seniors each year.

INSPIRE ICOPE-CARE program: perspectives and future challenges for the care of individuals during aging

It is always difficult to change habits and implement new care pathways in clinical practice. The INSPIRE ICOPE-CARE program plans to screen and monitor the intrinsic capacity of 200,000 older people in Occitania region within five years and promote preventive actions, instead of only punctual, curative ones. WHO with ICOPE program is determined to reduce the number of older people worldwide who are care dependent by 15 million by 2025, which would mean 150,000 in France and 15,000 in Occitania (10).
The INSPIRE ICOPE-CARE program is in full agreement with the national project of “Ma santé 2022” (My Health 2022) (11), in which the French Ministry of Health highlights the following aspects: to organize healthcare around the older people and give them a qualified and relevant care, be more active in prevention in order to promote home maintenance and develop a better organization of care between healthcare providers with the support of digital medicine. In order to achieve these objectives, the nurses’ role has to be redefined, giving them a stronger place in the assessment and the coordination of the patient’s healthcare pathway. Another change has to take place in communication and organization between hospital and primary healthcare providers, especially GPs. To establish this new organization, the INSPIRE ICOPE-CARE program supports “Ma Santé 2022” by joining the projects of several Professional regional health communities (CPTS) in the Occitania region. The CPTS are a new mode of organization that allows health professionals to come together in the same territory around a common medical and medico-social project. Moreover, The French Presidential Plan Grand Age aims to largely implement the WHO ICOPE program in France following the experience of the INSPIRE ICOPE-CARE program in Occitania.
This initiative draws significantly on numeric tools, e-health and digital medicine to facilitate communication and coordination between professionals and seniors (12, 13), it plays an important role in the future of geriatrics (14-17). The INSPIRE ICOPE-CARE program will also allow us to implement in clinical practice the discoveries of INSPIRE platform concerning clinical and biological biomarkers (18-22).

 

Funding: The Inspire Program was supported by grants from the Region Occitanie/Pyrénées-Méditerranée (Reference number: 1901175), the European Regional Development Fund (ERDF) (Project number: MP0022856), ARS «Agence Régional de Santé d’Occitanie» and the Inspire Chairs of Excellence funded by: Alzheimer Prevention in Occitania and Catalonia (APOC), EDENIS, KORIAN, Pfizer, Pierre-Fabre, Fondation Avenir Cogfrail Grant.
Potential Conflicts of Interest: The authors declare that they have no conflict of interest for the present paper.
Acknowledgements: The authors thank all the health professionals participating in the INSPIRE ICOPE CARE Program especially Cendrine Blazy and Dr Marie Dominique Medou from Occitania Regional Health Agency and all the members of the Gerontopole “Hospital of the walls” care unit (Augusto S, Bouchon L, Cazes MC, Da Costa F, Poly M, Vaysset S) and all the members of the Occitania Territorial Teams of Aging and Prevention of Dependency.
Ethical standards: The INSPIRE protocol has been approved by the French Ethical Committee located in Rennes (CPP Ouest V) in October 2019. This research has been registered on the site http://clinicaltrials.gov (ID NCT04224038). In the INSPIRE ICOPE-CARE program, all the senior’s data are collected in the Gerontopole Frailty database. This database complies with all French and European regulations in terms of health data security. The authorization of the French “National Commission for Data Protection” was granted on April 13, 2017 (Ref. Nb. MMS/OSS/NDT171027, authorization request Nb. 19141154). During the first (face to face) STEP 1 screening, the professional collects the senior’s oral consent to keep his/her data in the frailty database as well as to monitor his/her intrinsic capacity regularly.
Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

 

References

1. De Souto Barreto P, Guyonnet S, Ader GI, Andrieu S, Casteilla L, Davezac N, Dray C, Fazilleau N, Gourdy P, Liblau R, Parini A, Payoux P. The INSPIRE research initiative: A program for geroscience and healthy aging research going from animal models to humans and the healthcare system. J Frailty Aging 2020;Doi: 10.14283/jfa.2020.18.
2. Beard JR, Jotheeswaran AT, Cesari M, Araujo de Carvalho I. The structure and predictive value of intrinsic capacity in a longitudinal study of ageing. BMJ Open. 2019;9(11):e026119.
3. WHO Guidelines on Integrated Care for Older People (ICOPE). WHO. Available at: https://apps.who.int/iris/bitstream/handle/10665/326843/WHO-FWC-ALC-19.1-eng.pdf;jsessionid=31CB3214293723D1D9A7D2B822B92D0E?sequence=1 (accessed April 2, 2020).
4. Islene Araujo de Carvalho, a JoAnne Epping-Jordan,b Anne Margriet Pot,c Edward Kelley,d Nuria Toro,e Jotheeswaran A Thiyagarajana & John R Beard. Organizing integrated health-care services to meet older people’s Needs Bull World Health Organ 2017;95:756–763.
5. Cesari M, Araujo de Carvalho I, Amuthavalli Thiyagarajan J, Cooper C, Martin FC, Reginster JY, Vellas B, Beard JR. Evidence for the Domains Supporting the Construct of Intrinsic Capacity. J Gerontol A Biol Sci Med Sci. 2018;73(12):1653-1660.
6. Beard JR, Jotheeswaran AT, Cesari M, Araujo de Carvalho I. The structure and predictive value of intrinsic capacity in a longitudinal study of ageing. BMJ Open. 2019;9(11):e026119.
7. Mobile Fact Sheet. Pew Research Center Internet & American Life Project. Available at: http://www.pewinternet.org/fact-sheet/mobile/ (accessed April 2, 2020).
8. AVIS N° 2013.0092/AC/SEVAM du 4 décembre 2013 du collège de la Haute Autorité de santé relatif au protocole de coopération «Intervention d’infirmières libérales à domicile afin de diagnostiquer et d’initier la prise en charge de la fragilité du sujet âgé». Available at: https://www.has-sante.fr/upload/docs/application/pdf/2014-03/a_2013_0092_pc_046.pdf (accessed April 2, 2020).
9. Piau A, Sourdet S, Toulza O, Bernon C, Tavassoli N, Nourhashemi F. Frailty Management in Community-Dwelling Older Adults: Initial Results of a Trained Nurses Program. J Am Med Dir Assoc. 2019;20(5):642-643.
10. WHO Clinical Consortium on Healthy Ageing 2018, Geneva, Switzerland. Available at: https://apps.who.int/iris/bitstream/handle/10665/330026/WHO-FWC-ALC-19.2-eng.pdf (accessed April 2, 2020).
11. Ma santé 2022, un engagement collectif. May 3, 2019. Available at: https://solidarites-sante.gouv.fr/IMG/pdf/dossier_de_presse_acces_aux_soins_avril2019_vdef.pdf (accessed April 2, 2020).
12. Takeda C., Guyonnet S., Sumi Y. Vellas B. Integrated Care for Older People and the Implementation in the INSPIRE Study. J Prev Alz Dis 2020;2(7):70-74
13. Beard J.R. Linking Geroscience and Integrated Care to Reinforce Prevention. J Prev Alz Dis 2020;2(7):68-69.
14. Morley JE. Editorial: The Future of Geriatrics. J Nutr Health Aging.2020;24(1):1-2. doi: 10.1007/s12603-019-1308-5. PubMed PMID: 31886800.
15. Marengoni A. Letter to the editor: Reply to: The Future of Geriatrics. J Nutr Health Aging. 2020;24(2):242. doi: 10.1007/s12603-020-1321-8. PubMed PMID:32003418.
16. Vellas B, Scrase D, Rosenberg GA, Andrieu S, Araujo de Carvalho I, Middleton LT. Editorial: WHO Guidelines on Community-Level Interventions to Manage Declines in Intrinsic Capacity: The Road for Preventing Cognitive Declines in Older Age? J Prev Alzheimers Dis. 2018;5(3):165-167.
17. Dent E, Morley JE, Cruz-Jentoft AJ, Woodhouse L, Rodríguez-Mañas L, Fried LP, Woo J, Aprahamian I, Sanford A, Lundy J, Landi F, Beilby J, Martin FC, Bauer JM, Ferrucci L, Merchant RA, Dong B, Arai H, Hoogendijk EO, Won CW, Abbatecola A,Cederholm T, Strandberg T, Gutiérrez Robledo LM, Flicker L, Bhasin S, Aubertin-Leheudre M, Bischoff-Ferrari HA, Guralnik JM, Muscedere J, Pahor M, Ruiz J, Negm AM, Reginster JY, Waters DL, Vellas B. Physical Frailty: ICFSR International Clinical Practice Guidelines for Identification and Management. J Nutr Health Aging. 2019;23(9):771-787. doi: 10.1007/s12603-019-1273-z. PubMed PMID: 31641726; PubMed Central PMCID: PMC6800406.
18. Guerville F, De Souto Barreto P, Ader I, Andrieu S, Casteilla L, Dray C, Fazilleau N, Guyonnet S, Langin D, Liblau R, Parini A, Valet P, Vergnolle N, Rolland Y, Vellas B. Revisiting the Hallmarks of Aging to Identify Markers of Biological Age. J Prev Alzheimers Dis. 2020;7(1):56-64.
19. Sierra F. Editorial: Geroscience and the Role of Aging in the Etiology and Management of Alzheimer’s Disease. J Prev Alzheimers Dis. 2020;7(1):2-3.
20. Berg-Weger M, Morley J. Editorial: Loneliness in Old Age: An unaddressed Health Problem. J Nutr Health Aging. 2020;24(3):243-245. doi: 10.1007/s12603-020-1323-6. PubMed PMID: 32115602.
21. Guralnik J, Bandeen-Roche K, Bhasin SAR, Eremenco S, Landi F, Muscedere J, Perera S, Reginster JY, Woodhouse L, Vellas B. Clinically Meaningful Change for Physical Performance: Perspectives of the ICFSR Task Force. J Frailty Aging. 2020;9(1):9-13. doi: 10.14283/jfa.2019.33. PubMed PMID: 32150208.
22. Rodriguez-Mañas L, Araujo de Carvalho I, Bhasin S, Bischoff-Ferrari HA, Cesari M, Evans W, Hare JM, Pahor M, Parini A, Rolland Y, Fielding RA, Walston J, Vellas B. ICFSR Task Force Perspective on Biomarkers for Sarcopenia and Frailty. J Frailty Aging. 2020;9(1):4-8. doi: 10.14283/jfa.2019.32. PubMed PMID: 32150207.

What do you want to do ?

New mail

What do you want to do ?

New mail

What do you want to do ?

New mail

What do you want to do ?

New mail

What do you want to do ?

New mail

What do you want to do ?

New mail

MOBILE APPLICATION REMOVES SOCIETAL BARRIERS TO P4 MEDICINE

 

J.-P. MICHEL

 

Corresponding author: JP Michel, Geneva University (Switzerland) & French National Academy of Medicine – Paris (France), 40 A route de Malagnou – CH 1208 – Geneva Switzerland, jean-pierre.michel@unige.ch

J Frailty Aging 2017;6(4):216-218
Published online November 7, 2017, http://dx.doi.org/10.14283/jfa.2017.43


Abstract

The overlap between one innovative paradigm (P4 medicine: predictive, personalized, participatory and preventive) and another (a new definition of “Healthy ageing”) is fertile ground for new technologies; a new mobile application (app) that could broaden our scientific knowledge of the ageing process and help us to better analyse the impact of possible interventions in slowing the ageing decline. A novel mobile application is here presented as a game including questions and tests will allow in 10 minutes the assessment of the following domains: robustness, flexibility (lower muscle strength), balance, mental and memory complaints, semantic memory and visual retention. This game is completed by specific measurements, which could allow establishing precise information on functional and cognitive abilities. A global evaluation precedes advice and different types of exercises. The repetition of the tests and measures will allow a long follow up of the individual performances which could be shared (on specific request) with family members and general practitioners.

Key words: Mobile application, intrinsic capacity, physical abilities, balance, cognition.


 

 

At its origin, P4 medicine (the 4 Ps being Predictable, Personalized, Preventive and Participatory) was about quantifying wellness and demystifying disease (1). However, as stated by Lee Hood et al, P4 medicine is facing two major challenges, namely technical and societal barriers, and of these, the societal barriers will prove the most challenging. In 2011, Lee Hood, the promotor of P4 medicine, was looking for ways to bring patients, physicians and members of the health-care community into alignment with the enormous opportunities of P4 medicine (2). Until now, this question has remained open.
On examining the billions of different types of digital data that will likely be typical components of patients’ health records in the future to enable P4 medicine (3) and to follow the subject’s trajectory, I admit that I was extremely surprised to notice that there was no mention of daily functioning. In 2015, the then-Director General Margaret Chan totally demystified disease in the introduction to the World Report on Ageing and Health by stating that healthy ageing is more than just the absence of disease (4). Within the report, healthy ageing was defined as “the process of developing and maintaining the functional ability that enables wellbeing in older age” (4). The World Health Organization (WHO) report placed functional ability centre stage, along with its various components, from nutrition, to muscle mass and strength, mobility disorders and indeed, cognition.
Slightly less than 5,000 papers in the medical literature have focused on childhood growth curves, but significantly fewer are devoted to analysing the longitudinal physiological changes occurring with ageing (5, 6), the cumulative effect of disadvantages, or the relationships between adult ageing, gait speed and dementia, quality of life or functional decline.
The overlap between one innovative paradigm (P4 medicine) and another (a new definition of “Healthy ageing”) is fertile ground for new technologies, such as a mobile application (app) that could broaden our scientific knowledge of the ageing process and help us to better analyse the impact of possible interventions in slowing the ageing decline (7). A mobile app of this type would make it possible meet the P4 objectives (Predictive, Preventive, Personalized and Participatory) while simultaneously removing the societal hindrances mentioned by Hood (2). This new app will also clarify the constant interactions between individual characteristics (intrinsic capacity) and a person’s own life surroundings (functional abilities), as clearly stated in the WHO report (8).
With the wider demographic use of smartphones and other connected devices, a mobile app based on the integrative philosophy of p4 Medicine will definitely set the stage for a paradigm-shift from bio-medicine to functional medicine, with far-reaching societal impact. Engaging health care consumers as pioneers to use a mobile device that can assess their overall physical and cognitive performances, will yield data collection that will give new insights into the pathophysiology of aging (9). Examples exist today: based on big data, they analyze the relationships between physical activity and cardiovascular mortality (10) or age, walking ability and weight (11). In the same way, the proposed innovative app will benefit society as a whole, from users to patients, and may help decrease age-related disability and care costs, while increasing scientific knowledge, favoring education and the use of assistive devices.
Is the new mobile app, which is in the process of being patented, really P4 compatible? And will it be able to subvert the classical world order, namely by making individual functioning surpass the disease-based approach to care?
Any new mobile app attempting to reach these goals has to be PREDICTIVE; that is, it must provide information to determine an individual’s risk of accelerating age-related decline, linked to the silent and challenging physiological changes, such as the accumulation of years of life, stress, unhealthy life styles or health behaviours, or indeed trauma and disease. As previously stated, ageing is a continuous process that peaks at midlife, when physiological reserves are high, and daily physical and cognitive abilities are good. This life period is also characterized by great resilience, which can lead us to forget the insidious accumulation of various and multiple sources of damage, which may be revealed suddenly by a stressing life event. Recently, a 50-year old colleague who was working arduously in the hope of a promotion, provided an illustrative example of this phenomenon. Aware of the toll his strenuous work was taking on his physical health, he asked me whether his round-the-clock professional devotion might be accelerating his ageing process. Being aware of the impact of his behaviour on his health would help him, and countless others like him, to adapt their personal, family and social life conditions so that they can finally stop neglecting their health, limit their disproportionate ambition, and increase their wellness.
This new mobile app enables PERSONALIZED assessment, based on questionnaires (both basic and specific), and involving the performance of selected but very simple tests. Indeed, specific measures in daily life will be necessary to determine with accuracy a few essential criteria, such as nutrition, sarcopenia/frailty, physical, mental and cognitive abilities. Regular repetition of measures at 1 or 3 months for the long term will pinpoint early functional changes linked to sedentary habits (12), inadequate diet or the transition to disease(as it was well demonstrated for cognitive disorders or lung cancer (13-15). Visualizing real-time progress in the results is the most important element of the personalized information, yielding fundamental insights into physio-pathology. It also brings home to the user that their current life habits, lifestyles and life behaviours are intervening positively (or not) on their physical and mental capacities. It further indicates whether the exercises are having any positive effects. If not, automatic alerts will prompt the user to seek medical advice to address the problem(s) identified. The long term goal of the mobile app, if used regular from midlife onwards, is to identify personal risk factors, deliver advice and prevent age-related disability (16).
The third important aspect of the mobile app is to be PARTICIPATORY. After getting overall yet personalized results of the assessment, each individual has the possibility to share the test results with their entourage, i.e. their spouse, partner, children, friends or even their physician. A positive aspect of this mobile app is to the amusing games that can be played alone or in a network against competitors. In this way, it will not only stimulate the use to change any bad dietary habits, but also to stop smoking, exercise in groups and more (16). A variety of stimulating mental/cognitive activities, as well as balance practice, weight lifting, bowling competitions, and other coordinative actions will inspire each individual user. The creation of user networks will help to encourage everyone to live life to the full, stay active and enjoy the feeling of wellbeing well into the latest years of life.
Lastly, the mobile app promotes healthy ageing and enables personalized PREVENTIVE INTERVENTIONS. Updated critical analysis of results from randomized controlled interventions, summarized in plain language, will be available for users faced with a specific condition, such as physical exercise plus protein intake, in case of loss of muscle mass/strength, a Mediterranean diet recommended for users with cardiovascular issues and other such situation-appropriate responses (17, 18). In the near future, individualized answers to each user’s health concerns or problems are also being envisaged.
If this mobile app would be used by thousands of individuals around the world, it would generate big data collection (19), and the dynamics of this data would help us to respond to essential questions about how to reduce the functional decline linked to the ageing process. In this way, it would be possible to maintain good physiological reserve, increase physical function, stimulate brain activities and prevent or delay age-related disability. The impact of these positive outcomes would in turn help improve the well-being of ageing/aged adults and their caregivers in a virtuous circle.
With the mobile app, P4 medicine may mean that users, patients, researchers, physicians, and the entire health care community can join forces to transform the practice of medicine, and make it more proactive than reactive—and, in turn, less expensive and more effective (9).

 

Acknowledgments:  Fabrice Denis (MD, PhD) and Fiona Ecarnot (PhD, for her careful review of the manuscript).
Personal funding: No conflict of interest.

 

References

1.     Hood L, Price ND. Demystifying disease, democratizing health care. Sci Transl Med 2014;6:225ed5.
2.    Hood L, Friend SH. Predictive, personalized, preventive, participatory (P4) cancer medicine. Nat Rev Clin Oncol 2011;8:184-7.
3.    Tian Q, Price ND, Hood L. Systems cancer medicine: towards realization of predictive, preventive, personalized and participatory (P4) medicine. J Intern Med 2012;271:111-21.
4.    World Health Organization. The world report on Ageing and Health. Geneva: WHO; 2015.
5.    Kuh D, New Dynamics of Ageing Preparatory N. A life course approach to healthy aging, frailty, and capability. J Gerontol A Biol Sci Med Sci 2007;62:717-21.
6.    Skidmore PM, Hardy RJ, Kuh DJ, Langenberg C, Wadsworth ME. Life course body size and lipid levels at 53 years in a British birth cohort. J Epidemiol Community Health 2007;61:215-20.
7.    Michel JP, Dreux C, Vacheron A. Healthy ageing: Evidence that improvement is possible at every age. Europ Geriatr Med 2016;7:298-305.
8.    Beard JR, Officer A, de Carvalho IA, et al. The World report on ageing and health: a policy framework for healthy ageing. Lancet 2016;387:2145-54.
9.    Hood L, Flores M. A personal view on systems medicine and the emergence of proactive P4 medicine: predictive, preventive, personalized and participatory. N Biotechnol 2012;29:613-24.
10.    Lear SA, Hu W, Rangarajan S, et al. The effect of physical activity on mortality and cardiovascular disease in 130 000 people from 17 high-income, middle-income, and low-income countries: the PURE study. Lancet 2017, Sep 21. pii: S0140-6736(17)31634-3. doi: 10.1016/S0140-6736(17)31634-3. [Epub ahead of print].
11.    Althoff T, Sosic R, Hicks JL, King AC, Delp SL, Leskovec J. Large-scale physical activity data reveal worldwide activity inequality. Nature 2017;547:336-9.
12.    Bell KE, von Allmen MT, Devries MC, Phillips SM. Muscle Disuse as a Pivotal Problem in Sarcopenia-related Muscle Loss and Dysfunction. J Frailty Aging 2016;5:33-41.
13.    Denis F, Viger L, Charron A, et al. Detection of lung cancer relapse using self-reported symptoms transmitted via an internet web-application: pilot study of the sentinel follow-up. Support Care Cancer 2014;22:1467-73.
14.    Denis F, Viger L, Charron A, Voog E, Letellier C. Detecting lung cancer relapse using self-evaluation forms weekly filled at home: the sentinel follow-up. Support Care Cancer 2014;22:79-85.
15.    Denis F, Yossi S, Septans AL, et al. Improving Survival in Patients Treated for a Lung Cancer Using Self-Evaluated Symptoms Reported Through a Web Application. Am J Clin Oncol 2015.
16.    Inzitari M, Ruiz D, Martos J, Santaeugenia S. «Move on Against Frailty»: Time to Raise Awareness about Frailty and Prevention of Disability in the Community. J Frailty Aging 2016;5:201-3.
17.    Silva RB, Aldoradin-Cabeza H, Eslick GD, Phu S, Duque G. The Effect of Physical Exercise on Frail Older Persons: A Systematic Review. J Frailty Aging 2017;6:91-6.
18.    Xu F, Delmonico MJ, Lofgren IE, et al. Effect of a Combined Tai Chi, Resistance Training and Dietary Intervention on Cognitive Function in Obese Older Women. J Frailty Aging 2017;6:167-71.
19.    Beckmann JS, Lew D. Reconciling evidence-based medicine and precision medicine in the era of big data: challenges and opportunities. Genome Med 2016;8:134.