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D. Azzolino1, S. Vettoretti2, M.M. Poggi3, A. Soldati3, L. Caldiroli2, L.A. Dalla Vecchia4, M. Cesari5


1. Geriatric Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico di Milano, Italy; 2. Unit of Nephrology, Dialysis and Kidney Transplantation, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico di Milano, Italy; 3. Specialisation School in Geriatrics, University of Milan, Italy; 4. Department of Cardiology, IRCCS Istituti Clinici Scientifici Maugeri, Milan, Italy, 5. Department of Clinical Sciences and Community Health, Università di Milano, Milan, Italy

Corresponding Author: Dr. Domenico Azzolino, Geriatric Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico di Milano, Via F. Sforza, 35 – 20122 Milan (Italy); do.azzolino@hotmail.it; Twitter: @doazzolino.

J Frailty Aging 2024
Published online January 9, 2024, http://dx.doi.org/10.14283/jfa.2024.2



BACKGROUND: Older patients in hemodialysis have high prevalence of malnutrition that is often associated with rapid weight loss till cachexia.
OBJECTIVESs: We aimed to investigate whether in older patients undergoing hemodialysis the association between poor nutritional status and mortality may be independent of comorbidities and other risk factors.
DESIGN: Retrospective longitudinal study.
SETTING: Unit of Nephrology, Dialysis and Kidney Transplantation of the Policlinic Hospital of Milan, Milan, Italy.
PARTICIPANTS: A total of 107 prevalent patients undergoing hemodialysis for at least three months.
MEASUREMENTS: Sociodemographic, clinical, and biological data were recorded. Unintentional weight loss (UWL) was defined as loss of body weight > 5% in 3 months or > 10% in 6 months. We computed a 21-item Frailty Index that included clinical conditions associated with malnutrition and mortality in this population. Unadjusted and adjusted Cox proportional hazard models were performed to test the association of UWL, albumin and transferrin levels with death. Survival analyses based on Kaplan-Meier estimates were performed.
RESULTS: Patients’ age was 79 (±7.7) years; 38 (35%) were women. Thirty-one patients (29%) died during follow-up. Eighteen (16.8%) patients experienced UWL during the follow-up period. UWL was positively associated with death in the unadjusted model and even after the progressive inclusion of potential confounders. Low albumin levels were positively associated with death only in the unadjusted and partially adjusted models while low transferrin levels were not associated with death in none of the models. Mortality was significantly higher in those patients experiencing both UWL and albumin levels below 3.5 mg/dL.
CONCLUSIONS: In older patients undergoing chronic hemodialysis UWL is associated with mortality independently of comorbidities and other risk factors. Patients presenting both UWL and low albumin levels were those experiencing the worst outcomes in terms of mortality.

Key words: Aging, malnutrition, inflammation, chronic kidney disease, frailty.



Older people are vulnerable to nutritional issues because of physical impairment, psycho-social conditions, comorbidities and mutually interactive syndromes (1). In the last decades, the prevalence of chronic kidney disease (CKD) is substantially increased in older persons and, today, a relevant proportion of patients undergoing hemodialysis is aged 65 years or older. Indeed, with the worldwide increase in life expectancy, CKD incidence in older individuals has been increasing (2). Physiological changes seen with aging are responsible for a decline in kidney function. Additionally, age-related chronic diseases, both as stand-alone and simultaneously occurring (i.e., comorbidities), can exacerbate the deterioration of kidney function (3–5).
In the End-Stage Renal Disease (ESRD) context, dialysis treatment is life-saving replacement therapy. However, dialysis may also lead to several health-related problems (i.e., cardiovascular disease, bleeding, gonadal dysfunction, insulin resistance, immuno-deficiency, anemia, malnutrition, and muscle wasting) (6, 7). Advancing age is characterized by an increased level of circulating pro-inflammatory cytokines, the so-called “inflamm-aging” process (8). In particular, dialysis may further exacerbate this process since it is accompanied by chronic inflammation and increased protein catabolism (9, 10. It has been associated with physical inactivity, thus augmenting the risk of malnutrition and sarcopenia regardless of the aging process (2, 11, 12). Unintentional weight loss (UWL), experienced by many older people, may result from several age-related factors, including anorexia and catabolic diseases (2, 13). Furthermore, CKD patients may often present anorexia because of accumulating uremic toxins, depression, fatigue and physical disabilities (14). Low levels of testosterone and augmented leptin levels have been reported in male CKD older patients, thus exacerbating anorexia. Finally, gastrointestinal symptoms like nausea and vomiting can further contribute to weight loss (15).
In this context, UWL has been included in the Global Leadership Initiative on Malnutrition (GLIM) criteria for the diagnosis of malnutrition as a phenotypic criterion (16). It is also part of several tools for assessing malnutrition in older people both in the general population (e.g., Subjective Global Assessment (17), Malnutrition Inflammation Score (18), Mini Nutritional Assessment (19), Nutritional Risk Screening 2002 (20), Malnutrition Universal Screening tool (21)) and in hemodialyzed patients (18, 22). On the other hand, nutritional status is also frequently assessed through measuring specific biomarkers like as visceral proteins (i.e., albumin, pre-albumin, retinol- binding protein [RBP], and transferrin) useful to identify eventual modifications in the protein pool (23, 24). In particular, the RBP and pre-albumin have a short half-life (i.e., 12 h for RBP and 2–3 days for pre-albumin). Low serum levels of these two biomarkers may indeed reflect acute nutritional changes while proteins like transferrin and albumin (which have a longer half-life), may be reflective of long-term changes in nutritional status (24). However, it should not be overlooked that all these biomarkers have their own limitations since their levels can be influenced by some factors beyond nutritional status. In fact, inflammation (among all) may exert a marked influence on the levels of visceral proteins. Circulating pro-inflammatory molecules have been long associated with both morbidity and mortality in older persons, thus probably driving the vast majority of age-related negative conditions. Therefore, the present study aimed to evaluate whether, in patients undergoing chronic dialysis, the association between poor nutritional status and mortality may be independent of comorbidities and other risk factors.



Study design and population

This study included 107 older patients receiving chronic hemodialysis at the Nephrology Unit of a tertiary hospital in Milan (Italy) between 2014 and 2020. Only patients aged 65 and older were included in the study. The main exclusion criterion consisted in hemodialysis treatment for less than three months, this was applied not to include those patients that did not have a stable dry weight as well as to avoid the inclusion of individuals with end-stage illness and very short life expectancy. Information about clinical status, nutrition, biochemical parameters, dialysis, drug therapy and physical function were recorded.
The study adhered to the principles of the Declaration of Helsinki and was approved by the Ethical Committee of the Fondazione IRCCS Ca’ Granda – Policlinic Hospital of Milan (approval number: 383_2020). Since the collected data were all part of the clinical routine, no written informed consent was required according to local regulations (AIFA Resolution of 20 March 2008). However, all patients signed a consent form authorizing the processing of personal data (including for scientific research purposes) upon their access to the clinical service, during a complete interview with the clinician.

Nutritional and laboratory parameters

Body weight was measured at each clinical visit as part of the routine care. UWL was defined as a loss of body weight > 5% in 3 months or > 10% in 6 months according to the International Society of Renal Nutrition and Metabolism (ISRNM) criteria (22) which are in line with the GLIM criteria (i.e., >5% within past 6 months, or >10% beyond 6 months) (16). Serum albumin levels below 3.5 mg/dL and transferrin levels less than 200 mg/dL were also tested in the regression models. Serum high-sensitive C-reactive protein (hs-CRP) < 0.5 mg/dL was considered the cutoff level in our laboratory.


The outcome of interest for the present study was the all-cause mortality. Participants were regularly followed over time by the study center as referent for their hemodialytic procedures. Fatal events were retrieved from medical charts and administrative data.

Other measurements

Sociodemographic data (i.e., age, sex, education) and the presence of comorbidities (i.e., diabetes, COPD, dementia, hypertension, cancer, cerebrovascular disease, coronary artery disease, congestive heart failure) were collected. A 21-item Frailty Index, designed according to the model proposed by Rockwood and Mitnitski (25) was also computed. However, the items UWL, low albumin and transferrin levels (independent variables of the present study) were excluded from the computation of the total score used in the analyses. Each item composing the frailty index was categorized as 0 (i.e., the deficit was absent) or 1 (i.e., the deficit was pre-sent). The Frailty Index was then calculated as the number of deficits presented by each patient divided by the total number of considered deficits (i.e., 21). The biological validity of the frailty index is widely documented since frailty measured through the Frailty Index exponentially increases at older ages and rarely reaches values greater than 0.7 (as if a health deficit accumulation above 70% might become incompatible with life) (26). The association between frailty and adverse outcomes has been widely reported by large epidemiological cohorts studies like the Canadian Study of Health and Aging (27), the ESTHER study (28, 29) and the China Kadoorie Biobank study (30), just to name a few. In particular, the prognostic value of the FI in CKD older patients on hemodialysis has been previously reported (31). The variables included in FI are reported in supplemental materials (Table S1).

Statistical analysis

Data are presented as mean and standard deviation (SD) or absolute numbers and percentages for continuous and categorical variables, respectively. UWL, low albumin and transferrin levels were used as categorical variables in the analyses. Unadjusted and adjusted (considering age, sex, hs-CRP and Frailty Index as covariates) Cox regression models were performed to test the association of the three independent variables of interest with death (dependent variable of interest). Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were reported. Time to event was defined from baseline (i.e., three months after the initiation of the hemodialysis program) to the date of death (for those who died) or the date of the last visit (for those who did not). The correlation between hs-CRP and albumin was assessed by Pearson correlation test. Statistical significance was set at p value <0.05. All analyses were performed with JAMOVI version 1.6.



Participant characteristics are presented in Table 1. The study sample consisted of a total of 107 CKD older patients undergoing hemodialysis (mean age 79 ± 7.7 years; women n= 38, 35%). Median follow-up was 21 (interquartile [IQR] range 8-32) months. Mean albumin levels were 3.72 (SD 0.5) mg/dL, with 27 (25.2%) patients who had albumin levels below 3.5 mg/dL. UWL was found in 18 (17%) patients. Mean transferrin levels were 183 (SD 41.7) mg/dL, with 37 (34.6%) patients who had transferrin levels below 200 mg/dL. Mean frailty index was 0.23 (SD 0.10), with 31 (29%) patients who died during the follow-up period. High-sensitive C-reactive protein (hs-CRP) mean levels were 1.20 (SD 2.08) with 50 (46.7%) patients who had hs-CRP levels >0.5 mg/dL.

Table 1. Participant characteristics

* SD: standard deviation; CHF: Chronic Heart Failure; CHD: Coronary Heart Disease; COPD: Chronic Obstructive Pulmonary Disease; hs-CRP: high-sensitive C-Reactive Protein.


Figure 1 shows the results of the Kaplan-Meyer curves for UWL. Patient’s mortality was significantly higher in the UWL group (p<0.001). In Figure 2, the results of the Kaplan-Meyer curves for UWL and albumin are shown. Mortality was significantly higher in those patients experiencing both UWL and albumin levels below 3.5 mg/dL (Figure 2). Results of the multivariate Cox regression analyses are reported in Table 2. In both unadjusted (HR 3.68; CI95%: 1.72-7.89; p=0.001) and partially adjusted models (HR 3.55; CI95%: 1.61-7.84; p=0.002), UWL was positively associated with all-cause mortality. The results were confirmed after potential confounders were progressively included as covariates in the Cox proportional hazard model.

Figure 1. Survival Curves for UWL

* UWL: Unintentional weight loss


Also, albumin levels below 3.5 g/dL were significantly associated with all-cause mortality in both unadjusted (HR 2.20, CI95% 1.10-4.40, p=0.03) and partially adjusted models (HR 2.19, CI95% 1.09-4.41, p=0.03). However, the association disappeared when hs-CRP and the other two variables of interest (i.e., transferrin and UWL) were progressively added to the model. On the other hand, transferrin levels below 200 mg/dL were not significantly associated with death in both the unadjusted and adjusted models. There was a negative relationship between the level of hs-CRP and serum albumin level (r = –0.326, p < 0.001) as shown in Figure 3.`

Figure 2. Survival Curves for UWL and low albumin levels

* UWL: Unintentional weight loss

Figure 3. Relationship between albumin and hs-CRP levels

* Hs-CRP: high-sensitive C-Reactive Protein

Table 2. Relationship of unintentional weight loss, low albumin and low transferrin levels with death in dialyzed older patients

* HR= hazard ratio; CI= confidence interval; UWL= unintentional weight loss. † Model 1: Adjusted for age, sex, frailty index. ‡ Model 2: Adjusted for age, sex, frailty index and hs-CRP levels. § Model 3: Adjusted for age, sex, frailty index, hs-CRP levels and the three independent variables of interest



Our study demonstrated a significant association of UWL with all-cause mortality in a population of older patients undergoing chronic hemodialysis. In particular, patients experiencing UWL during the follow-up period had a 2.9-fold risk of death. Notably, this association was independent of other potential confounders that may have influenced the overall prognosis and that are summarized by individual FI (table S1). Also, albumin levels below 3.5 mg/dL were associated with mortality in both the unadjusted and partially adjusted model (i.e., model 1). However, this association disappeared after the inclusion of hs-CRP and the other two independent variables of interest. On the other hand, low transferrin levels (i.e., <200 mg/dL) were not significantly associated with mortality in none of the models.

Recently, several scientific societies including the National Kidney Foundation’s Kidney Disease Outcomes Quality Initiative (KDOQI) (32) and the European Society for Clinical Nutrition and Metabolism (ESPEN) (33) in their updated guidelines, re-evaluated the utility of visceral proteins in assessing nutritional status. In particular, both KDOQI and ESPEN stated that albumin levels should not be interpreted in isolation since such a marker is not sufficiently valid or reliable in reflecting nutritional status despite it has been extensively associated with illness and mortality, especially in ESRD patients (32, 33). In fact, several non-nutritional factors like hepatic failure and inflammation among all, can influence albumin levels (32, 34, 35). Particularly, in chronic kidney disease, systemic chronic inflammation has been evoked as a main contributor to the so-called “uremic phenotype” characterized by the accumulation of uremic toxins which are biologically active compounds that, in normal conditions, are removed from the blood by the kidney. However, in the chronic kidney disease scenario, uremic toxins can accumulate exerting negative effects (36). The uremic phenotype is then associated with adverse outcomes and increased mortality as a result of a range of conditions including cardiovascular disease, infectious complications, protein-energy wasting, depression, osteoporosis and frailty (36). Persistent inflammation through the inhibition of albumin synthesis and the promotion of its catabolism (37), can be looked as the potential mechanism mediating the documented association between low albumin levels and mortality (38–40). Furthermore, oxidative stress may be envisioned as an additional mechanism, partially stimulated by the inflammation during the uremic milieu, contributing to cardiovascular risk factors and mortality in CKD patients (38). Indeed, oxidative stress as a result of sustained inflammation and in combination with low albumin levels may lead to several adverse outcomes including the deterioration of nutritional status (38). In other words, inflammation through its systemic effects including decreased albumin levels could promote the so-called “Malnutrition, Inflammation and Atherosclerosis syndrome” (38, 41). At the same time, also transferrin levels can be influenced by liver disease and inflammatory states but also by iron status since transferrin serves as an iron transport protein (24). Indeed, such markers should be used in combination with an appropriate nutritional assessment and clinical judgment (33). In fact, among GLIM etiologic criteria for the diagnosis of malnutrition, there is also the disease burden/inflammation (16). GLIM suggests that laboratory markers like CRP, albumin or pre-albumin can be used as supportive proxy measures of inflammation. However, even accordingly to GLIM, the diagnosis of malnutrition requires at least 1 phenotypic criterion and 1 etiologic criterion (16).
Several changes occurring with aging make older individuals at risk of developing the so-called “anorexia of aging” which is a clear risk factor for malnutrition, frailty and sarcopenia (42). Inflammatory cytokines are a clear determinant of the anorexia of aging through their effects on the gastrointestinal system, appetite and energy expenditure (38). It has been also suggested that hypoalbuminemia in CKD patients undergoing dialysis may also negatively affect the intestinal absorption of essential nutrients like vitamins and minerals, which have clear antioxidant properties, through the promotion of intestinal edema (38, 43, 44). Furthermore, the inflamm-aging theory suggests that the production of inflammatory cytokines can drive several age-related phenotypes and pathologies (8). Despite the exact pathophysiological mechanisms underlying chronic inflammation are not completely understood, its etiology has been suggested to be multifactorial. Particularly, several potential factors have been described including (a) the production of reactive species by infiltrating leukocytes against pathogens; (b) the production of cytokines by damaged nonimmune cells and activated immune cells that can amplify or modulate the inflammatory response altering the phenotypes of adjacent cells and thus normal tissue function; (c) the interference with anabolic and catabolic signaling (8). Furthermore, in CKD patients, inflammation seems to be exacerbated by several other mechanisms, characteristic of the uremic milieu including dialysis membranes and central venous catheters, oxidative stress and cellular senescence, tissue factors (i.e., hypoxia, fluid and sodium overload), microbial factors (i.e., immune dysfunction and gut dysbiosis), uremic toxins retention (i.e., indoxyl sulfate, advanced glycation end products, calcioprotein particles) (36).
In the aging context, UWL is a frequently assessed parameter and has been repeatedly associated with higher mortality rates (45). This is true also in CKD patients where malnutrition and rapid involuntary weight loss are very commonly observed, particularly in patients undergoing hemodialysis (46, 47). However, it should be considered that the proportion of UWL may slightly differ depending on the instrument used to determine malnutrition since both the rate of UWL and the time range are quite different among various instruments (i.e., Nutrition Risk Screening 2002, GLIM, International Society of Renal Nutrition and Metabolism criteria).
Our results are in line with those of Cabezas- Rodriguez et al. (48) that reported an increased mortality risk in CKD patients experiencing weight loss over 6 months. The authors also showed that those CKD patients aged 65 and older with weight loss, had a higher risk of death compared to their younger counterparts. Chang et al. (47) reported a rapid decline in body weight, with a nadir at 5 months, in those patients who survived the first year of hemodialysis. They also reported an association between rapid weight loss during the first 12 months with a higher risk of mortality.
Of particular note, UWL is a well-known contributor of frailty. To date, the frailty phenotype model, proposed by Fried et al. (13), includes weight loss as one of the five criteria to define frailty. Conversely, higher body mass index (BMI), as well as weight gain, have been associated with better survival rates in hemodialysis patients (7), the so-called “obesity paradox” (47). However, the use of BMI (as well as weight loss) in body composition assessment presents several limitations, starting from the fact that it is not a pure index of adiposity since its numerator (i.e., body weight) is the sum of both fat and fat-free mass. Furthermore, cut-off points to define obesity were originally based on young and middle-aged cohorts and therefore not suitable for older people who present a decreased fat-free mass along with high adiposity, even with a normal/overweight BMI (23). Indeed, recent GLIM criteria for the diagnosis of malnutrition included a BMI threshold of 22 Kg/m2 to define malnutrition in those people aged 70 and older (16). At the same time, it has been recommended a BMI threshold of 23 Kg/m2 in CKD patients, independently of age, to screen for malnutrition (2, 22, 49). It has not been well established whether the effects of weight change can be dependent on initial BMI, final BMI (i.e., after weight loss), or the degree of weight loss or gain. UWL can be misclassified even if adjusted for initial or final BMI. In other words, overweight and obese people experiencing unintentional weight loss can be misclassified into a normal weight group (50). Other measurements (i.e., computed tomography [CT], Magnetic Resonance Imaging [MRI], bioelectrical impedance analysis [BIA]) may be of difficult implementation in the routine clinical practice. Additionally, BIA results may be inaccurate because of fluid overload, a condition frequently seen in hemodialysis patients. Our study seems to confirm a rather marginal prognostic capacity of serum albumin in patients with chronic kidney failure. Furthermore, as can be seen in Figure 3, a progressive increase in the hs-CRP level was correlated with a parallel decline in the serum albumin level confirming that albumin is a more sensitive marker of inflammation (given its longer half-life and lower variability than other inflammatory biomarkers) than nutritional status. These findings are in line with other studies reporting that the prognostic value of albumin is lost after adjustment for inflammatory markers (51–53). As reported by Kaysen et al. (35) in the National Institutes of Health (NIH)-sponsored HEMO Study, inflammation is advocated as the main cause of decreased serum albumin levels with little evidence for poor nutrition as a causative factor. Similar results were also obtained for transferrin, a negative-phase serum protein that is sometimes used to determine the nutritional status (54). Kim et al. (55) also reported an inverse correlation between albumin and CRP levels as well as correlations between albumin and other markers of endothelial dysfunction. Our results are also in line with those of Campbell et al. (56) that showed an independent significant association between UWL and death in dialyzed patients, while albumin was not associated with mortality when adjusted for the confounding variables (i.e., age, comorbidities, dialysis vintage, ethnicity, and gender). However, it should be noted that in their study they also included adult patients (i.e., aged 18 and older). Few studies have been focused on older people, especially those who are frail and/or on hemodialysis, which are frequently excluded from clinical trials (57, 58). The assessment of UWL may thus provide more accurate information than the biomarkers. It might be hypothesized that, thanks to its multidimensional nature, UWL might better capture the individual’s complexity. Furthermore, it is noteworthy that the definition of UWL implies the drawing of a longitudinal trajectory, describing the dynamic evolution of the system. The capacity to capture time-related clinical modifications is surely more informative than the cross-sectional measurement of a biological variable. Albumin should be thus (re)considered as a marker of illness rather than of nutritional status, as suggested by mounting evidence (59). However, visceral proteins can be used in combination with other nutritional parameters (i.e., UWL, low muscle mass) in order to capture, in a multidimensional way, the complexity of frail older people undergoing hemodialysis. In fact, as can be seen in Figure 2, patients experiencing both UWL and low albumin levels are those with the worst outcomes in terms of mortality.
Limitations of our study may reside in the retrospective design and the small sample size. However, it should be noted that our sample optimally captures a population of older persons in the chronic need of hemodialysis, since we excluded those who did not survive the first three months after initiation of the treatment. In this way, we have been able to well define the clinical relevance of UWL in the absence of the acute/terminal phase of the kidney disease. A further limitation is related to the single-site experience represented in the study, which does not allow to exclude that specific peculiarities of our setting might explain our findings. Although we selected two limited time frames of three and six months after the first three months since the beginning of dialysis to detect involuntary weight loss, we did not register whether it happened gradually or suddenly during an acute event. Therefore, we cannot reconstruct in which circumstances and how fast weight loss happened. Finally, since fatal events were retrieved from medical charts and administrative data, people who died outside the hospital might be unlikely to have their death recorded.
In conclusion, our study showed a significant association between UWL and mortality in older patients undergoing hemodialysis, independently of potential confounders. On the other hand, the association between albumin levels and death disappeared when other confounders were progressively added in the model, confirming a marginal role of albumin as a stand-alone in reflecting nutritional status, as recently suggested by several reports. Indeed, UWL may be looked as a simple, easy-to-obtain/implement in the routine clinical practice and affordable measure to help clinicians in assessing the nutritional status of CKD patients on dialysis in order to prevent and/or delay poor outcomes. The combination of different measures can be looked as a better strategy to capture, in a multidimensional way, the clinical complexity of frail older people.


• Older people undergoing hemodialysis have a high prevalence of malnutrition often associated with a rapid loss of body weight.
• Older patients on hemodialysis experiencing unintentional weight loss had a 2.9-fold risk of death.
• The presence of unintentional weight loss, both as stand-alone or in combination with other risk factors, should lead to the prompt and comprehensive assessment of the older person undergoing hemodialysis.


Author Contributions: DA and MC contributed to conceptualizing and writing the manuscript. SV, MMP, AS, LC and LADL edited and revised manuscript. DA, SV, MMP, AS, LC, LADL and MC approved the final version of manuscript.

Funding: none.

Conflicts of Interest: The authors declare no conflict of interest.

Ethical standards: The procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy) and with the Helsinki Declaration of 1975, as revised in 2000.





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