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SERUM CREATININE–CYSTATIN C BASED SCREENING OF SARCOPENIA IN COMMUNITY DWELLING OLDER ADULTS: A CROSS-SECTIONAL ANALYSIS

 

 

R. Matsuzawa1, K. Nagai1, K. Takahashi2, T. Mori3,4, M. Onishi5, S. Tsuji5,6, K. Hashimoto7, K. Tamaki3, Y. Wada3,8, H. Kusunoki3,9, Y. Nagasawa3, K. Shinmura3

 

1. Department of Physical Therapy, School of Rehabilitation, Hyogo Medical University, Kobe, Japan; 2. Department of Biostatistics, Hyogo Medical University, Nishinomiya, Japan; 3. Department of General Internal Medicine, School of Medicine, Hyogo Medical University, Nishinomiya, Japan; 4. Amagasaki Medical COOP Honden Clinic, Amagasaki, Hyogo, Japan; 5. Department of Orthopedic Surgery, School of Medicine, Hyogo Medical University, Nishinomiya, Japan; 6. Department of Orthopedic Surgery, Tatsuno City Hospital, Tatsuno, Japan; 7. School of Pharmacy, Hyogo Medical University, Kobe, Japan; 8. Roppou Clinic, Toyooka, Hyogo, Japan; 9. Department of Internal Medicine, Osaka Dental University, Hirakata, Japan.

Corresponding Author: Ryota Matsuzawa, PT, PhD., Department of Physical Therapy, School of Rehabilitation, Hyogo Medical University, 1-3-6 Minatojima, Chuo-ku, Kobe, Hyogo 650-8530, Japan. Tel: +81-78-304-3181; Fax: +81-78-304-2811; E-mail: ryota122560@gmail.com

J Frailty Aging 2024;in press
Published online February 6, 2024, http://dx.doi.org/10.14283/jfa.2024.13

 


Abstract

OBJECTIVES: To compare the discriminative capabilities for the manifestation of sarcopenia or physical frailty between serum creatinine- and cystatin C-derived indices among community-dwelling older adults.
DESIGN: Cross-sectional study.
SETTING: Primary Care and Community.
PARTICIPANTS: We utilized a subset of data from the Frail Elderly in the Sasayama-Tamba Area (FESTA) study, which was initiated in 2015 to gather comprehensive information on various health-related parameters among community-dwelling older individuals (age ≥65 years).
MEASUREMENTS: Five serum creatinine–cystatin C based indices including the Sarcopenia Index, the serum creatinine/cystatin C ratio, the disparity between serum cystatin-C-based and creatinine-based estimated GFR, the total body muscle mass index (TBMM), and the prediction equation for skeletal muscle mass index (pSMI) were employed. Sarcopenia and physical frailty were identified based on the Asian Working Group for Sarcopenia criteria and the revised Japanese version of the Cardiovascular Health Study criteria, respectively. The receiver operating characteristic (ROC) and logistic regression analyses were performed to assess the discriminative abilities of these tools.
RESULTS: In the analysis of 954 participants, 52 (5.5%) were identified with sarcopenia and 35 (3.7%) with physical frailty. Regarding sarcopenia discrimination, TBMM and pSMI both exhibited area under the curve (AUC) values exceeding 0.8 for both men and women. Concerning the identification of physical frailty, AUC values ranged from 0.61 to 0.77 for males and 0.50 to 0.69 for females. In the multivariate logistic regression analyses, only TBMM and pSMI consistently displayed associations with sarcopenia, irrespective of sex (P<0.001, respectively). On the other hand, no consistent associations were observed between the indices and physical frailty.
CONCLUSIONS: This study provides a robust association of a serum creatinine- and cystatin C-derived indices, especially TBMM and pSMI, with sarcopenia among community-dwelling older adults. Conversely, the application of these indices for the screening of physical frailty has its constraints, necessitating further investigation.

Key words: Sarcopenia, frailty, creatinine, cystatin C, older adults.


 

Introduction

Frailty is typically regarded as an age-related state marked by physiological susceptibility to stress, with 7.4% of older adults in the community demonstrating physical frailty (1). Numerous factors are interrelated and can be theoretically integrated into a frailty cycle, with sarcopenia occupying a central role in this cycle (2). Sarcopenia is a geriatric syndrome that is characterized by the loss of skeletal muscle mass and decreased muscle function. Recently, a meta-analysis reported that, among community-dwelling older adults, the prevalence of sarcopenia, which was diagnosed using established criteria, was between 9.9% and 12.9% (3). Sarcopenia has detrimental health outcomes, including disability (4), diminished quality of life (5, 6), increased mortality risk (4), and higher healthcare costs (7, 8). Despite the growing enthusiasm for interventions to address sarcopenia in older adults, diagnosing sarcopenia in routine clinical medicine remains a formidable task. This challenge is primarily rooted in the limitations presented by reliable and pragmatic tools for precisely quantifying muscle mass, including techniques such as dual X-ray absorptiometry (DXA), computer tomography (CT), or magnetic resonance imaging (MRI), as well as the time and personnel requirements for the meticulous evaluation of physical function and muscle strength. Hence, it is crucial to screen for potential sarcopenia through objective assessments with emerging potential, such as blood parameters.
Among blood markers, the serum creatinine level, which is commonly used to assess kidney function in the general population and patients with chronic illnesses, was the focus of our study. Creatinine is an end product of muscle metabolism, and if adjusted for the effects of the glomerular filtration rate (GFR), the serum creatinine level could effectively reflect individual variations in muscle mass and function, therefore, serving as a valid screening tool for sarcopenia. The GFR can be estimated using serum cystatin C levels—an endogenous protease inhibitor produced by all nucleated cells—which is less influenced by muscle metabolism (9). Several recent studies have documented the association between parameters derived from serum creatinine and cystatin C levels and the occurrence of sarcopenia or physical frailty in community-dwelling adults (10, 11), hospitalized patients (12), and individuals with chronic illnesses (13, 14). These parameters include the Sarcopenia Index (calculated as serum cystatin-C-based estimated GFR [eGFRcysC] multiplied by serum creatinine) (15), the serum creatinine/cystatin C ratio (CCR)(16), the disparity between eGFRcysC and serum creatinine-based estimated GFR (eGFRsCr) (eGFRdiffcysC-sCr) (11), the total body muscle mass index (TBMM) (17), and the prediction equation for skeletal muscle mass index (pSMI) (18). However, there is still a shortage of research in the domain of contrasting the discriminative capabilities for sarcopenia or physical frailty among these indices.
The objective of this study was to compare the discriminative capabilities for the manifestation of sarcopenia or physical frailty between parameters derived from serum creatinine and cystatin C. Our goal is to identify the optimal screening tool for application in the clinical context of community-dwelling older adults.

 

Methods

Study design and participants

We utilized a subset of data from the Frail Elderly in the Sasayama-Tamba Area (FESTA) study, which was initiated in 2015 to gather comprehensive information on various health-related parameters among community-dwelling older individuals residing in the Sasayama-Tamba area of Japan (19). Prior to their enrollment, all individuals provided written informed consent for their participation in the study. This cross-sectional analysis included 988 older adults (age ≥65 years), who were enrolled between 2015 and 2019, based on the eligibility criteria for this study. We excluded individuals who had missing data that prevented the determination of sarcopenia, those without available laboratory data, and those with end-stage renal disease or dementia. This study was approved by the Ethics Review Board (approval number: Rinhi 0342) and was conducted in accordance with the principles of the Declaration of Helsinki.

Clinical characteristics

Information on demographic factors, including age and sex, along with smoking habits and chronic diseases such as hypertension, dyslipidemia, diabetes mellitus, liver disease, cardiovascular disease, and cerebrovascular disease, were obtained through interviews and questionnaires. To assess the physical constitution, body mass index was calculated using body weight and height. Furthermore, blood samples were collected from all participants to determine the primary predictors of this study.

Creatinine and cystatin C measurements

Blood samples were collected from all participants on the designated day and were serum separated immediately after collection and stored frozen. The following laboratory parameters were ascertained: levels of serum creatinine (enzymatic method, Determiner L CRE, BioMajesty™ series JCA-BM8004 series, JEOL Ltd., Tokyo, Japan), serum cystatin-C (colloidal gold assay, NESCAUTO GC CystatinC, BioMajesty™ series JCA-BM8005 series, JEOL Ltd., Tokyo, Japan), serum albumin (modified bromocresol purple assay, Pureauto s ALB-N, BioMajesty™ series JCA-BM8000 series, JEOL Ltd., Tokyo, Japan), serum high-sensitive C-reactive protein (nephelometry, N Latex CRPⅡ, BN II System, Siemens Healthcare Diagnostics K.K., Tokyo, Japan), serum hemoglobin (sodium lauryl sulfate-hemoglobin concentration, SULFOLYSER, Automated Hematology Analyzer XN-1000, SYSMEX CORPORATION, Hyogo, Japan), hematocrit (electric resistance measurement, CELLPACK DCL, Automated Hematology Analyzer XN-1000, SYSMEX CORPORATION, Hyogo, Japan), serum total cholesterol (cholesterol oxidase-peroxidase method, Cholestest CHO, BioMajesty™ series JCA-BM8002 series, JEOL Ltd., Tokyo, Japan), serum high-density lipoprotein cholesterol (direct fulguration, Cholestest N HDL, BioMajesty™ series JCA-BM8003 series, JEOL Ltd., Tokyo, Japan), and serum total protein (biuret assay, Clinimate TP, BioMajesty™ series JCA-BM8001 series, JEOL Ltd., Tokyo, Japan). To estimate renal function, the following two formulae, which were validated for the Japanese population (9, 20), were used: eGFRsCr and eGFRcysC.
In this study, to discern physical frailty and sarcopenia by incorporating the creatinine filtration and serum creatinine levels, we employed five screening tools: Sarcopenia Index (15), CCR (16), eGFRdiffcysC-sCr (21), TBMM (17), and pSMI (18). The formulae for these parameters are as follows: Sarcopenia Index = eGFRcysC (mL/min per 1.73m2) × serum creatinine (mg/dL); CCR = serum creatinine (mg/dL) / serum cystatin C (mg/dL); eGFRdiffcysC-sCr = eGFRcysC – eGFRsCr; TBMM = body weight (kg) × serum creatinine (mg/dL) / (k × body weight [kg] × serum cystatin C [mg/dL] + serum creatinine [mg/dL]) (the coefficient values [k] were 0.00675 for men and 0.01006 for women); pSMI = 4.17 – 0.012 × Age (y) + 1.24 × (serum creatinine [mg/dL] / serum cystatin C [mg/dL]) – 0.0513 × Hb (g/dL) + 0.0598 × body weight (kg) (for men), 3.55 – 0.00765 × Age (y) + 0.852 × (serum creatinine [mg/dL] / serum cystatin C [mg/dL]) – 0.0627 × Hb (g/dL) + 0.0614 × body weight (kg) (for women).

Diagnosis of sarcopenia

Sarcopenia was diagnosed according to the diagnostic criteria recommended by the Asian Working Group for Sarcopenia (AWGS2) (22) that considers low muscle mass and low muscle strength or low physical performance.
A multifrequency bioimpedance device, the InBody 770 (InBody Co., Ltd., Seoul, Republic of Korea), was used for bioelectrical impedance analysis measurements. The appendicular skeletal muscle mass was used as an indicator of muscle mass. To account for differences in physical constitution among the participants, the appendicular skeletal muscle mass was normalized by dividing it by the height squared (m2), and then expressed as the skeletal muscle index (SMI). The AWGS2-derived criterion for low muscle mass were SMI values of <7.0 and <5.7 kg/m2 for men and women, respectively.
Handgrip strength was assessed using a digital dynamometer (TKK 5101 Grip-D; Takei, Tokyo, Japan) using a standard protocol (22). The participants performed two maximal isometric voluntary contractions of the hands for 3 seconds each while standing with full elbow extension, and the higher of the two recorded values was used for analysis. Participants who were unable to stand unassisted were allowed to sit. The cutoff points for low muscle strength were handgrip strength of <28.0 and <18.0 kg for men and women, respectively (22).
For the evaluation of physical performance, we measured gait speed and five-time chair stand time, and used the Short Physical Performance Battery (SPPB). Gait speed was determined by measuring the time taken to walk 10 m at a normal pace from a moving start without deceleration (23). The velocity was then converted to meters per second (m/s). To assess the ability to rise from a chair, participants were instructed to fold their arms across their chest and stand up once from a chair. If successful, they were then asked to stand up and sit down five times as rapidly as possible, and the time taken from the initial sitting position to the final standing position at the end of the fifth stand was recorded. The SPPB, which comprises three components (gait speed, repeated chair stands, and standing balance), was assessed using established methods (23). Participants with a gait speed of <1.0 m/s, a five-time chair stand time of ≥12 seconds, or an SPPB score of ≤9 were classified as having low physical performance (22).

Identification of physical frailty

Physical frailty was determined using the revised Japanese version of the Cardiovascular Health Study (J-CHS) criteria (24), which were adapted to suit the characteristics of older Japanese adults. The J-CHS criteria encompass five physical components: shrinking, low activity, exhaustion, weakness, and slowness. Participants were assigned scores based on the following assessment procedures: shrinking: «Have you unintentionally lost 2 kg or more in the past 6 months?» (Yes = 1 point); low activity: (a) «Do you engage in moderate levels of physical exercise or sports for health?» (b) «Do you engage in low levels of physical exercise for health?» (No for both questions = 1 point); exhaustion: «Have you felt tired without a reason in the past 2 weeks?» (Yes = 1 point); weakness: handgrip strength <28.0 and <18.0 kg for men and women, respectively (1 point); and slowness: gait speed <1.0 m/s (1 point). Individuals were classified as having physical frailty if they had a score ≥3.

Statistical analysis

Baseline characteristics were summarized using median and interquartile range for continuous variables or frequency and proportion for categorical variables. The participants were divided into two groups based on sex, and the intergroup differences in the baseline characteristics were ascertained using the Wilcoxon rank-sum test for continuous variables or the chi-square test for categorical variables. To evaluate the discrimination performance of each primary predictor (Sarcopenia Index, CCR, eGFRdiffcysC-sCr, TBMM, and pSMI) for sarcopenia or physical frailty, the receiver operating characteristic (ROC) curve was described and the area under the curve (AUC) was calculated. The Youden index, which quantifies the combined specificity and sensitivity of a factor, was employed as a measure of overall performance (25). It is defined as the maximum vertical distance between the ROC curve and the chance line diagonal, and can be calculated as the maximum value of [sensitivity + specificity – 1]. The optimal Youden index was employed to determine the optimal cutoff point for each primary predictor in relation to sarcopenia or physical frailty within this investigation.
Univariable and multivariable logistic regression models were used to investigate the association of each main predictor with sarcopenia or physical frailty. The crude model examined the unadjusted associations; Model 1 adjusted for age, body mass index, smoking habits, physical activity level (low activity or not, considered only when addressing sarcopenia), and chronic diseases (diabetes mellitus and cardiovascular diseases); Model 2 adjusted for smoking habits, physical activity level (low activity or not, considered only when addressing sarcopenia), chronic diseases (diabetes mellitus and cardiovascular diseases), and serum albumin and high-sensitive C-reactive protein levels; Model 3 adjusted for age, body mass index, smoking habits, physical activity level (low activity or not, considered only when addressing sarcopenia), chronic diseases (diabetes mellitus and cardiovascular diseases), and serum albumin, high-sensitive C-reactive protein and hemoglobin levels). These analyses were conducted independently for each sex in addition to that of the entire participant pool. The selection of covariates in the models was driven by subject matter expertise in identifying potential confounding factors affecting the relationship between each primary predictor and the presence of sarcopenia or physical frailty. The odds ratios were computed per 1-point or 0.1-point decrease. Given the presence of some missing data in the dataset, a multiple imputation approach was used for logistic regression models as a sensitivity analysis. Furthermore, multivariable logistic regression models with three knots-restricted cubic splines were utilized to assess potential nonlinear associations between each main predictor and sarcopenia or physical frailty (26). Statistical analyses were conducted using R version 4.3.0 (R Foundation for Statistical Computing, Vienna, Austria). Statistical significance was set at P < 0.05; all tests were two-tailed.

 

Results

Characteristics of the participants

A total of 988 individuals underwent eligibility assessment for inclusion, and 27 individuals with indeterminable data for sarcopenia determination, 4 with missing laboratory data, and 3 with end-stage renal disease or dementia were excluded. Consequently, the final dataset included 954 community-dwelling older adults.
The characteristics of the participants, categorized by their sex, are summarized in Tables 1 and 2, respectively. This cohort had a median age of 73 [68, 77] years, with 67.6% women. Sarcopenia was identified in 52 (5.5%) and physical frailty in 35 (3.7%) participants.

Table 1. Baseline characteristics stratified by sex

Data are expressed as median [interquartile range] or frequency (proportion). Abbreviations: hCRP, high-sensitive C-reactive protein; HDL-C, high-density lipoprotein cholesterol; eGFRsCr, creatinine-based estimated glomerular filtration rate; eGFRcysC, cystatin-C-based estimated glomerular filtration rate; CCR, serum creatinine/cystatin C ratio; eGFRdiffcysC-sCr, disparity between eGFRcysC and eGFRsCr; TBMM, total body muscle mass index; pSMI, prediction equation for skeletal muscle mass index.

Table 2. Sarcopenia- and physical frailty-related parameters stratified by sex

Data are expressed as median [interquartile range] or frequency (proportion). Abbreviations: SPPB, Short Physical Performance Battery.

 

Discriminant power of the screening parameters for sarcopenia and physical frailty

The ROC curves illustrating the performance of the screening parameters, derived from creatinine and cystatin C, for sarcopenia and physical frailty are presented in Figure 1 and 2, respectively. AUCs of Sarcopenia Index, CCR, eGFRdiffcysC-sCr, TBMM, and pSMI in the whole cohort were 0.631, 0.612, 0.694, 0.650, and 0.667 for sarcopenia, and 0.655, 0.637, 0.699, 0.488, and 0.520 for physical frailty, respectively (Supplementary Tables 1 and 2). In sex-specific analyses, regarding the discrimination of sarcopenia, both TBMM and pSMI demonstrated AUC values surpassing 0.8 for both men and women. On the other hand, the Sarcopenia Index, CCR, and eGFRdiffcysC-sCr exhibited AUC values falling between 0.7 and 0.8 for men and ranging from 0.6 to 0.7 for women. When it comes to the discrimination of physical frailty, the Sarcopenia Index, CCR, and eGFRdiffcysC-sCr revealed AUC values within the range of 0.7 to 0.8 for men and 0.6 to 0.7 for women. In contrast, both TBMM and pSMI displayed AUC values lower than 0.7 for both men and women. The cutoff values for the screening parameters identifying those with sarcopenia or physical frailty based on the Youden index were summarized in Supplementary Table 1 and 2.

Figure 1. The discriminative efficacy of the screening parameters in relation to sarcopenia among (A) All participants, (B) men, and (C) women

Figure 2. The discriminative efficacy of the screening parameters in relation to physical frailty among (A) All participants, (B) men, and (C) women

 

Association of the screening parameters calculated based on creatinine and cystatin C with sarcopenia and physical frailty in the multiple logistic regression analyses

The results of the univariate and multivariate logistic regression analyses, which examined the association between the screening parameters calculated based on the levels of serum creatinine and cystatin C, and their relationship with sarcopenia and physical frailty, are shown in Tables 3 and 4. The Sarcopenia Index, CCR, eGFRdiffcysC-sCr, TBMM, and pSMI demonstrated significant associations with sarcopenia in the analyses encompassing all participants and men exclusively, even after adjusting for age, body mass index, smoking habits, physical activity levels, chronic illnesses, and laboratory parameters. However, within the analyses focused solely on women, only TBMM and pSMI exhibited a noteworthy association with sarcopenia (odds ratio [OR], 95% confidence interval [CI]: 1.784 [1.413 – 2.253] and 1.897 [1.510 – 2.382], respectively). The Sarcopenia Index, CCR, and eGFRdiffcysC-sCr demonstrated significant associations with physical frailty in the analyses encompassing all participants (OR, 95%CI: 1.052 [1.002 – 1.105], 1.535 [1.071 – 2.201], and 1.046 [1.008 – 1.085], respectively). However, in the analyses involving only men, CCR and eGFRdiffcysC-sCr were the sole parameters significantly associated with physical frailty (OR, 95%CI: 2.035 [1.056 – 3.924] and 1.074 [1.007 – 1.145], respectively). In the analyses limited to women, no significant association between any creatinine-derived parameter and physical frailty was observed. The utilization of multiple-imputation-based sensitivity analysis had negligible effects on the estimates concerning the association between the primary predictors and sarcopenia or physical frailty (Supplementary Tables 3 and 4). In the multivariate-adjusted cubic spline analyses, which evaluated sarcopenia and physical frailty using Sarcopenia Index, CCR, eGFRdiffcysC-sCr, TBMM, and pSMI as continuous variables, a decrease in these parameters was associated with an increased likelihood of sarcopenia (Supplementary Figures 1 and 2).

Table 3. Association of creatinine-derived parameters with sarcopenia

Crude model: without adjustment. Model 1: adjusted for age, body mass index, smoking habits, physical activity level (low activity or not), diabetes mellitus, and cardiovascular diseases. Model 2: adjusted for smoking habits, physical activity level (low activity or not), diabetes mellitus, cardiovascular diseases, serum albumin level, serum high-sensitive C-reactive protein level. Model 3: adjusted for age, body mass index, smoking habits, physical activity level (low activity or not), diabetes mellitus, cardiovascular diseases, serum albumin level, serum high-sensitive C-reactive protein level, and serum hemoglobin level. Abbreviations: OR, odds ratio; CI, confidence interval, CCR, serum creatinine/cystatin C ratio; eGFRdiffcysC-sCr, disparity between eGFRcysC and eGFRsCr; TBMM, total body muscle mass index; pSMI, prediction equation for skeletal muscle mass index.

Table 4. Association of creatinine-derived parameters with physical frailty

Crude model: without adjustment. Model 1: adjusted for age, body mass index, smoking habits, diabetes mellitus, and cardiovascular diseases. Model 2: adjusted for smoking habits, diabetes mellitus, cardiovascular diseases, serum albumin level, serum high-sensitive C-reactive protein level. Model 3: adjusted for age, body mass index, smoking habits, diabetes mellitus, cardiovascular diseases, serum albumin level, serum high-sensitive C-reactive protein level, and serum hemoglobin level. Abbreviations: OR, odds ratio; CI, confidence interval, CCR, serum creatinine/cystatin C ratio; eGFRdiffcysC-sCr, disparity between eGFRcysC and eGFRsCr; TBMM, total body muscle mass index; pSMI, prediction equation for skeletal muscle mass index.

 

Discussion

In this cross-sectional study, which involved 954 community-dwelling individuals aged 65 or older in Japan, we assessed and compared the discriminative abilities of various indices, including the Sarcopenia Index, CCR, eGFRdiffcysC-sCr, TBMM, and pSMI. These all indices were calculated using serum creatinine and cystatin C. Among the study participants, 52 (5.5%) were identified with sarcopenia and 35 (3.7%) with physical frailty. Our primary findings indicate that serum creatinine- and cystatin C-derived indices, particularly TBMM and pSMI, consistently demonstrated moderate accuracy in identifying sarcopenia. Due to their objectivity and reliance on easily obtainable data, these indices appear to be valuable tools for screening sarcopenia in routine clinical practice and health check-ups. Conversely, the screening for physical frailty using parameters derived from serum creatinine and cystatin C presented challenges, particularly in women. In the future, it is imperative to conduct further research to gain a deeper understanding of the mechanisms influencing the differences in the discriminative ability of physical frailty between sexes.
Numerous factors, including chronic undernutrition, comorbid burden, anorexia, sedentary lifestyle, metabolic disturbances, reduced physical function, exercise intolerance, and loss of muscle mass, are interconnected and theoretically unified in a physiological cycle of frailty (2). Sarcopenia represents a pivotal component of this cycle, and early identification of sarcopenia is crucial to impede the progression of this detrimental cycle in older adults. Detecting sarcopenia and physical frailty in community-dwelling older individuals during regular office visits and health check-ups presents difficulties due to the lack of validated and practical assessment tools, time constraints, and the need for personnel capable of accurately assessing muscle mass depletion (for the purpose of detecting sarcopenia), physical function, and muscle strength. Hence, if a strong association were found between sarcopenia/physical frailty and laboratory blood parameters that are both objective and commonly measured, it would greatly facilitate the establishment of early identification and management protocols for these conditions among older adults in community.
The creatinine excretion we focused on is traditionally recognized as a measure of muscle metabolism in individuals (27). Creatinine is a waste product that is generated in the body as a consequence of muscle metabolism and is derived from creatine, a molecule involved in supplying energy to muscles during contraction. Our recent report revealed a significant association between a decline in serum creatinine levels and a higher risk of sarcopenia among patients with severely impaired renal excretion who required hemodialysis therapy (28). Conversely, as creatinine is produced at a relatively consistent rate and is primarily eliminated by the kidneys through urine in the general population, excluding patients with anuria, the serum creatinine level serves as an indicator of the kidneys’ effectiveness in filtering waste products from the bloodstream, i.e., renal function. Therefore, to predict muscle mass and function using serum creatinine levels in the general population, it is necessary to adjust for the influence of GFR, calculated based on the serum cystatin C levels, which is unrelated to muscle metabolism.
Among the indices derived from serum creatinine and cystatin C, CCR has been the most commonly utilized in previous research. A recent meta-analysis assessing CCR’s ability to discriminate sarcopenia, which encompassed 38 studies and 20,362 patients, it revealed an AUC of 0.689 (30), indicating a level of accuracy below the moderate range and largely consistent with our study’s results. Moreover, CCR has been reported to possess limited discriminatory accuracy of sarcopenia, and certain studies older people aged ≥60 years participated in have concluded that CCR had not been able to accurately detect either low muscle mass or sarcopenia (31). On the contrary, TBMM has exhibited a substantial correlation with skeletal muscle mass estimated through DXA (17), and it maintains a moderate association with sarcopenia diagnoses based on AWGS criteria (10), which is consistent with the results of this study. The TBMM formula includes not only serum creatinine and cystatin C but also factors such as sex and body weight. Conversely, the pSMI calculation takes into account age, sex, body weight, and Hb values. Given the significance of body weight as an indicator for estimating muscle mass, it is hypothesized that both TBMM and pSMI displayed superior discriminatory capabilities when compared to alternative indices like the Sarcopenia Index, CCR, and eGFRdiffcysC-sCr. In addition, as both formulas of TBMM and pSMI include a factor of sex, we have surmised that disparities in discriminatory capacities of sarcopenia between sexes as observed in the Sarcopenia Index, CCR, and eGFRdiffcysC-sCr had been eliminated. On the other hand, it is prudent to exercise caution when attempting to identify physical frailty through the utilization of serum creatinine and cystatin C. In a large-scale cohort study encompassing 9,092 hypertensive individuals, a strong association between eGFRdiffcysC-sCr and physical frailty has been reported (11). In our own investigation, within a multivariate analysis confined to men participants, a significant association of the Sarcopenia Index, CCR, and eGFRdiffcysC-sCr with physical frailty was discerned. However, in the case of women, no significant associations were detected. One plausible contributing factor to this outcome might be the limited number of cases exhibiting physical frailty in our study.
This study has several limitations. Firstly, it was conducted in a specific region of Japan with a relatively small sample size, thereby limiting the generalizability of the findings to a broader international population. Therefore, further large-scale studies are warranted. Secondly, our study utilized a cross-sectional design, and assessments were undertaken only at the initiation of the study. It is important to consider the fluctuations in muscle mass and clinical parameters over time. Thirdly, we employed the bioelectrical impedance analysis method for estimating skeletal muscle mass, as opposed to the techniques of DXA, CT, or MRI. Fourthly, we failed to perform a comparative analysis of the discriminatory efficacy between the serum creatinine- and cystatin C-derived parameters and endorsed screening tools such as calf circumference and SARC-F by AWGS. This omission stems from missing data within the FESTA study. However, it is imperative to acknowledge that their application is not devoid of limitations. Measuring calf circumference necessitates skilled human resources to ensure reproducible results, and some researchers have expressed doubts about the questionnaire SARC-F’s capacity for discerning sarcopenia (32). Lastly, as most participants volunteered and were able to visit our hospital either independently or with family support, they were likely to be healthier individuals. Although sarcopenia is widely prevalent among older adults, its prevalence among our participants remained at 5.5%, which is lower than the range of 9.9% to 12.9% reported in a previous meta-analysis (3). Nevertheless, this selective bias in the study population is unlikely to have substantially impacted the relationship between our primary predictors and sarcopenia or physical frailty.

 

Conclusion

This study assessed the validity of serum creatinine and cystatin C indices for identifying sarcopenia and physical frailty in community-dwelling older adults. It also established a robust association between TBMM and pSMI with sarcopenia in older adults. These indices, calculated exclusively from laboratory parameters and readily obtainable demographic factors, confer clinical advantages due to their exceptional accessibility, absence of the requirement for specialized techniques, and the absence of specific contraindications. Moreover, we contend that the widespread adoption of TBMM or pSMI across diverse settings, including routine clinical practice and regular health checkups, will streamline the early detection and management of sarcopenia in these populations. Conversely, the utilization of parameters derived from serum creatinine and cystatin C for screening physical frailty presents specific challenges, especially among women, necessitating further research.

 

Acknowledgments: The authors wish to express their appreciation of the staff for all the time and attention that they have devoted to the study.

Conflicts of interest: The authors declare that they have no conflicts of interest.

Financial support: This work was supported in part by the JSPS KAKENHI (grant number: 22K19496 to K.S. in 2022), Uehara Memorial Foundation (grant number: 202120105 to K.S.), National Center for Geriatrics and Gerontology (grant number: Choujyu 20-1 to K.S. in 2022), Hyogo Medical University Grant for Research Promotion, 2023 (to R.M.), and the JSPS KAKENHI (grant number: 20K19332 to R.M. in 2020).

Ethical approval: All participants of the Frail Elderly in the Sasayama-Tamba Area (FESTA) study provided written informed consent before study enrollment. This study was approved by the Ethic Review Board (approval number: Rinhi 0342) and conducted in accordance with the principles of the Declaration of Helsinki.

 

SUPPLEMENTARY MATERIAL

 

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