Nutritional Status Association With Sarcopenia in Patients Undergoing Maintenance Hemodialysis Assessed by Nutritional Risk Index

Introduction

Protein-energy wasting (PEW), which refers to loss of body protein mass and fuel reserves, is common in patients with end-stage kidney disease (ESKD), and also known to be associated with increased morbidity and mortality (1–3). For diagnosis of PEW, an international society panel of renal nutrition and metabolism experts has recommended use of four primary established categories; serum chemistry, body mass, muscle mass, and dietary intake (1).

Malnutrition is frequently observed in ESKD patients (4, 5) and nutritional screening tools, including the subjective global assessment of nutrition (SGA) (6), modified versions of the SGA (7, 8), and malnutrition–inflammation score (MIS) (9), are suggested to be potential clinical markers of PEW status (1). However, those tools require subjective assessment and judgment by the examiner, which may reduce reproducibility, and are also time-consuming, thus difficult to integrate into routine clinical practice. Recently, based on the concept of PEW, a nutritional risk index (NRI) was developed using data from the Japanese Society for Dialysis Therapy Renal Data Registry to predict the prognosis of maintenance hemodialysis (MHD) patients (10), which was later validated in the Q-Cohort Study that included elderly MHD patients (11). The NRI is comprised of four objective variables routinely measured in clinical settings, and has been shown to be a simple and useful nutritional screening tool for MHD patients in Japan (12).

Sarcopenia, characterized as loss of skeletal muscle mass and function (13), is also frequently observed in MHD patients (14, 15) and that condition is called uremic sarcopenia. Uremic sarcopenia is induced by complex pathways, including uremic changes, inflammation, myocellular changes, hormonal changes, and comorbid conditions (16). In related studies, nutritional intervention methods have been shown capable of increasing lean body mass, arm muscle circumference, or handgrip strength in patients undergoing MHD (17–19), suggesting a close relationship of nutritional status with sarcopenia in those cases.

However, the association of nutritional status with sarcopenia has not been fully clarified in regard to MHD patients. Therefore, the present study aimed to elucidate the relationship of malnutrition with sarcopenia in such patients by investigating the association of nutritional status, assessed by use of the NRI, with sarcopenia, assessed by the Asian Working Group for Sarcopenia (AWGS) 2019 criteria (20).

Materials and Methods

Study Design and Participants

This cross-sectional retrospective study was conducted at Inoue Hospital (Osaka, Japan) (21). Among 334 MHD patients who underwent measurements of muscle mass, muscle strength, and physical performance from January 2019 to December 2019, those who had been receiving therapy for <6 months (n = 3) or with missing data regarding nutritional status (n = 12) were excluded. Furthermore, patients with malignancy, acute illness, infection, or liver cirrhosis (n = 4) were further excluded from the present analysis. As a result, 315 patients undergoing MHD (199 males, 116 females) were retrospectively analyzed in the present study.

Body weight refers to “dry weight” in the present study. Body mass index (BMI) was defined as body weight in kilograms divided by the square of height in meters. Diabetes mellitus was defined based on the American Diabetes Association criteria or treatment for diabetes mellitus (22). Past history of cerebrovascular disease was defined as prior occurrence of intracerebral hemorrhage, transient ischemic attack, subarachnoid hemorrhage, and/or ischemic stroke (23, 24).

Owing to the retrospective nature of the investigation, the Inoue Hospital Ethics Committee waived the need/requirement for obtaining informed consent (approval no. 236). All data subjected to analysis were collected from relevant patient medical charts and records, after approval of the study protocol. The present study was conducted in full accordance with the principles of the Declaration of Helsinki.

Blood Sample Collection

Blood was drawn from each patient with or without fasting before the start of the first MHD session of the week. The level of albumin in serum was analyzed using a bromocresol purple method, while that of the serum standard (low-sensitive) C-reactive protein (CRP) was analyzed using a latex agglutination immunoassay (reference range; 0–4.5 mg/L) at the hospital. Other standard laboratory parameters including levels of total cholesterol, creatinine, and hemoglobin were analyzed by use of a routine laboratory method at the hospital (23, 24).

Nutritional Risk Index

Nutritional status was assessed using NRI score (10), which was calculated based on creatinine, total cholesterol, serum albumin, and BMI (Table 1).

TABLE 1

Table 1. NRI score.

Based on their NRI score, the enrolled patients were divided into the low-risk (score 0–7) and medium-/high-risk (score 8–13) groups (10).

Methods for Muscle Mass, Muscle Strength, and Physical Performance Measurements

As a part of routine clinical care for MHD patients at Inoue Hospital, muscle mass, muscle strength, and physical performance are generally measured after the end of MHD treatment at the beginning of the week of their birthday (21). The participants were informed that they were scheduled to be evaluated in regard to muscle mass, muscle strength, and physical performance on a day when undergoing treatment prior to the scheduled test date. Muscle strength and physical performance were measured by 10 different examiners, who received training and standardized their methods in advance.

Determination of Muscle Mass

Muscle mass was assessed using a whole body dual-energy X-ray absorptiometry system (Horizon A; Hologic Inc, MA, USA) (25). Appendicular skeletal muscle was considered as an extremity fat-free mass lacking bone mineral content. Height-adjusted muscle mass was calculated as appendicular skeletal muscle in kilograms divided by height in meters squared (kg/m²) (15).

Measurement of Muscle Strength

Muscle strength was assessed with a handgrip strength test using a Smedley-type hand dynamometer (T.K.K.5101; Takei, Niigata, Japan), with the examination conducted by an experienced research staff member. The patients were instructed to apply maximum force in an upright position and hold the grip with their arm extended (26, 27). Measurements were repeated two times with both hands, and the maximum value (kg) was recorded.

Assessment of Physical Performance

A five-time chair stand test was conducted to assess physical performance based on the AWGS 2019 criteria (20). Each patient was instructed to stand and sit five times as fast as possible from a sitting position on a chair with a seat height of 40 cm and straight back without armrests, with their hands on their shoulders and arms crossed across the chest, as previously reported in the CHAIR (change hemodialysis patients' activity and impaired functions by chair stand exercise) study (28). They initiated the five-time chair standing test when an experienced research staff member spoke the word “start,” then the time (seconds) to complete the fifth repetition was recorded (29, 30).

Definitions of Low Muscle Mass, Low Muscle Strength, and Low Physical Performance

Based on the AWGS 2019 criteria, low muscle mass was defined as height-adjusted muscle mass of <7.0 kg/m² for males and <5.4 kg/m² for females, low muscle strength as handgrip strength of <28 kg for males and <18 kg for females, and low physical performance as a five-time chair stand test time of ≥12 seconds for both males and females (20).

Diagnosis of Sarcopenia and Severe Sarcopenia

For diagnosis of sarcopenia and severe sarcopenia, the AWGS 2019 criteria were used (20). In brief, subjects with low muscle mass, plus either low muscle strength or low physical performance were diagnosed as having sarcopenia, while those with low muscle mass, plus both low muscle strength and low physical performance were diagnosed as having severe sarcopenia.

Statistical Analysis

Values are expressed as the percent or median (interquartile range). A chi-squared test (categorical variables) and Mann–Whitney's U test (continuous variables) were used to compare variables between groups. Spearman's correlation coefficient was used to determine correlations between variables. Serum CRP values below the detection limit (0.1 mg/L) were handled as 0.1 mg/L. Before performing multivariable regression analysis, the serum level of CRP was logarithmically transformed (log) to follow a normal distribution. Multivariable linear regression analysis was used to determine whether the NRI score was independently associated with muscle mass, muscle strength, or physical performance, following adjustments using known risk factors, including age, gender, hemodialysis duration, presence of diabetes mellitus, history of cerebrovascular disease, use of intravenous and/or oral vitamin D, and hemoglobin and CRP levels. Multivariable logistic regression analyses were performed to determine whether NRI score, or a finding of medium- or high-risk assessed by the NRI was independently associated with presence of low muscle mass, low muscle strength, low physical performance, sarcopenia or severe sarcopenia, after adjustments using the known risk factors noted above. All statistical analyses were performed using the Statistical Package for the Social Sciences software package (IBM SPSS Statistics for Windows, 27.0, IBM Corp., Armonk, NY, USA). All reported P values are two-tailed, with a value < 0.05 considered to indicate statistical significance.

Results

Clinical Characteristics of Patients

Table 2 presents characteristics of the enrolled patients (n = 315). The rates of prevalence of low serum creatinine level, low serum total cholesterol level, high serum total cholesterol level, low serum albumin level, and low BMI based on the NRI score cut-off point were 38.1% (n = 120), 21.0% (n = 66), 7.3% (n = 23), 65.7% (n = 207), and 28.6% (n = 90), respectively. The median NRI score was 5.0 and the prevalence of patients in the medium-/high-risk group (NRI score ≥8) was 31.1% (n = 98). The prevalence ratios for low muscle mass, low muscle strength, and low physical performance were 55.9% (n = 176), 60.6% (n = 191), and 31.4% (n = 99), respectively, while those for sarcopenia and severe sarcopenia were 44.1% (n = 139) and 20.0% (n = 63), respectively. Finally, as compared to female subjects, male subjects had significantly (P < 0.001) higher values for height-adjusted muscle mass and handgrip strength, and significantly (P < 0.05) lower values for five-time chair stand test time (Table 2). However, the frequency of sarcopenia and severe sarcopenia was not significantly different between male and female subjects.

TABLE 2

Table 2. Clinical characteristics of patients (n = 315) stratified by gender and nutritional status assessed by NRI.

The primary disease related to renal failure in the enrolled patients was diabetic nephropathy in 91 (28.9%), chronic glomerulonephritis in 86 (27.3%), nephrosclerosis in 38 (12.1%), polycystic kidney disease in 20 (6.3%), graft loss in 17 (5.4%), unclassifiable nephritis in 7 (2.2%), congenital anomaly in the kidneys or urinary tract in 4 (1.3%), kidney or urinary tract tumor in 3 (1.0%), pregnancy-induced hypertension in 3 (1.0%), malignant hypertension in 2 (0.6%), autoimmune nephritis in 2 (0.6%), urinary tract obstruction in 2 (0.6%), chronic pyelonephritis in 1 (0.3%), acute kidney injury in 1 (0.3%), other disease in 4 (1.3%), and unknown etiology in 34 (10.8%).

Associations of NRI Score With Muscle Mass, Muscle Strength, and Physical Performance

NRI score showed weak to moderate though significant correlation with height-adjusted muscle mass (muscle mass; ρ = −0.359, P < 0.001), handgrip strength (muscle strength; ρ = −0.361, P < 0.001), and five-time chair stand test time (physical performance; ρ = 0.407, P < 0.001). To further examine whether NRI score is independently associated with those factors, multivariable linear regression analyses were performed (Table 3), which showed the score to be significantly associated with muscle mass (β = −0.310, P < 0.001), muscle strength (β = −0.200, P < 0.001), and physical performance (β = 0.195, P = 0.001), while age and gender also showed a significant (P < 0.01) association.

TABLE 3

Table 3. Multivariable linear regression analysis of factors possibly associated with muscle mass, muscle strength, and physical performance.

Associations of Nutritional Status With Low Muscle Mass, Low Muscle Strength, and Low Physical Performance

NRI score was significantly higher in patients with low muscle mass [7.0 (4.0–8.0) vs. 4.0 (1.0–7.0), P < 0.001], low muscle strength [7.0 (4.0–8.0) vs. 4.0 (0.3–5.8), P < 0.001], and low physical performance [7.0 (5.0–9.0) vs. 4.0 (3.0–7.0), P < 0.001], as compared to patients without those factors present. Furthermore, the medium-/high-risk group (n = 98) showed a significantly (P < 0.01) higher prevalence for low muscle mass, low muscle strength, and low physical performance as compared to the low-risk group (n = 217; Table 2, Figure 1). To examine whether NRI score and medium-/high-risk were independently associated with those factors in the patient cohort, multivariable logistic regression analyses were performed (Table 4). The results showed that NRI score was significantly associated with low muscle mass [odds ratio (OR) 1.260, 95% confidence interval (CI) 1.157–1.374; P < 0.001], low muscle strength (OR 1.310, 95% CI 1.178–1.457; P < 0.001), and low physical performance (OR 1.216, 95% CI 1.104–1.339; P < 0.001). Furthermore, when NRI score was replaced by presence of medium- or high-risk, medium-/high-risk status retained a significant association with low muscle mass (OR 2.141, 95% CI 1.219–3.760; P = 0.008), low muscle strength (OR 7.665, 95% CI 3.438–17.091; P < 0.001), and low physical performance (OR 2.570, 95% CI 1.401–4.716; P = 0.002). Finally, when use of lipid-lowering medications was added to the multivariable logistic regression model, NRI score and medium-/high-risk status remained significantly associated with low muscle mass, low muscle strength, and low physical performance (Supplementary Table S1).

FIGURE 1

Figure 1. Prevalence of sarcopenia and its components in medium-/high-risk and low-risk groups. Patients were divided into low-risk (score 0–7) and medium-/high-risk (score 8–13) groups based on NRI score. NRI, nutritional risk index.

TABLE 4

Table 4. Association of nutritional status with low muscle mass, low muscle strength, and low physical performance.

Associations of Nutritional Status With Sarcopenia and Severe Sarcopenia

NRI score was significantly higher in patients with sarcopenia [7.0 (4.0–9.0) vs. 4.0 (2.0–7.0), P < 0.001] as well as those with severe sarcopenia [8.0 (5.0–10.0) vs. 4.0 (3.0–8.0), P < 0.001], as compared to those without. Furthermore, the medium-/high-risk group demonstrated a significantly (P < 0.001) higher prevalence for sarcopenia and severe sarcopenia, as compared to the low-risk group (Table 2, Figure 1). To examine whether NRI score and medium-/high-risk based on NRI score were independently associated with sarcopenia and severe sarcopenia in the cohort, multivariable logistic regression analyses were performed (Table 5). NRI score was shown to be significantly associated with both sarcopenia (OR 1.255, 95% CI 1.143–1.377; P < 0.001) and severe sarcopenia (OR 1.257, 95% CI 1.122–1.407; P < 0.001). Furthermore, when NRI score was replaced by medium-/high-risk, a significant association with sarcopenia (OR 2.960, 95% CI 1.623–5.401; P < 0.001) as well as severe sarcopenia (OR 2.241, 95% CI 1.151–4.362; P = 0.018) was retained. Finally, when use of lipid-lowering medications was added to the multivariable logistic regression model, NRI score and medium-/high-risk status remained significantly associated with sarcopenia and severe sarcopenia (Supplementary Table S2).

TABLE 5

Table 5. Association of nutritional status with sarcopenia and severe sarcopenia.

Discussion

The present findings demonstrated that NRI score was significantly associated with muscle mass, muscle strength, and physical performance in the present Asian patients undergoing MHD. Furthermore, NRI score and medium-/high-risk status based on that score were significantly associated with sarcopenia and severe sarcopenia, as well as low muscle mass, low muscle strength, and low physical performance. These results suggest that NRI score, a nutritional screening tool, is useful for detection of sarcopenia and its related components. Furthermore, it is indicated that malnutrition contributes to sarcopenia and severe sarcopenia in MHD patients by reducing muscle mass and strength, as well as physical performance.

Some studies conducted previously have found significant associations of nutritional status with sarcopenia-related components, such as muscle mass (31), muscle strength (32, 33, 35, 36), and physical performance (34, 36, 37) in MHD patients using nutritional screening tools, including SGA and MIS, as well as geriatric nutritional risk index (GNRI). SGA and MIS, which include assessment of muscle mass, are considered to be validated clinical tools for screening nutritional status, though the results obtained are subjective and assessment is time consuming. While GNRI is an objective nutritional screening tool comprised of serum albumin level, current body weight, and ideal body weight, it does not include assessment of muscle mass. The present results demonstrated an association of nutritional status with all isolated sarcopenia-related components using the NRI, an objective nutritional screening tool that includes assessment of muscle mass, as reflected by serum creatinine concentration.

There are few reports regarding the relationship of nutritional status indicators with sarcopenia based on the combined components of sarcopenia in MHD patients. Giglio et al. found that SGA score was significantly lower in MHD subjects with sarcopenia as compared to without, based on the European Working Group on Sarcopenia in Older People (EWGSOP) criteria in a study conducted in South America (35). In Asia, one study demonstrated a significant association of MIS score with sarcopenia (38), while another found a non-significant association of modified versions of SGA score with sarcopenia (39). However, the number of subjects included in those studies was relatively few (<135 in each). Furthermore, in those investigations conducted in Asia, sarcopenia was defined based on the EWGSOP but not the AWGS criteria, in spite of cultural, lifestyle-related, and/or anthropometric differences between Asian and Western populations. In contrast, the results of the present study clearly demonstrate a significant association of nutritional status with sarcopenia/severe sarcopenia based on the combined components of sarcopenia as well as each individual component using regionally appropriate diagnostic criteria for sarcopenia in a relatively large number of patients undergoing MHD (n = 315).

Low dietary intake is known to be associated with low muscle and strength, and also low physical performance in older adults (40–42), while nutritional intervention in older patients was reported to increase those factors (43–45). Of importance, nutritional status was shown to predict development of sarcopenia in older adults (46), thus demonstrating that malnutrition contributes to sarcopenia in that population. In studies of MHD patients, nutritional intervention was found to result in increases in muscle mass, muscle strength, and physical performance (17–19). As a result, nutritional status is considered to have a significant effect on sarcopenia even in those patients (47). On the other hand, the association of nutritional status with sarcopenia and its components in MHD cases has not been fully investigated. In the present study, NRI score and medium- or high-risk status were significantly associated with sarcopenia and its related components. Thus, malnutrition may lead to sarcopenia or severe sarcopenia by reducing muscle mass, muscle strength, and physical performance in patients undergoing MHD. On the other hand, proactive nutritional intervention may prevent onset and progression of sarcopenia in MHD patients with medium-/high-risk based on the NRI, an objective and simple nutritional screening tool.

This study has some important limitations. First, due to the design, dietary intake, an important factor related to nutritional status as well as sarcopenia and its components (40–42), was not determined. Second, for nutritional status assessment, while NRI was used, other nutrition indicators, such as SGA or modified versions and MIS, were not determined. Thus, a large-scale longitudinal study of patients undergoing MHD that includes assessments of dietary intake and nutritional status by other tools in addition to NRI is needed to clarify the role of malnutrition in sarcopenia. Nevertheless, the present results clearly demonstrate that nutritional status is significantly associated with sarcopenia/severe sarcopenia based on the combined components of sarcopenia as well as each isolated component in MHD patients.

In conclusion, the present results showed that NRI score and medium- or high-risk status were significantly associated with sarcopenia and severe sarcopenia, as well as low muscle mass, low muscle strength, and low physical performance in patients undergoing MHD. It is thus suggested that malnutrition contributes to sarcopenia and severe sarcopenia in these patients by reducing muscle mass and strength, as well as physical performance.

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Materials, further inquiries can be directed to the corresponding author.

Ethics Statement

The studies involving human participants were reviewed and approved by the Inoue Hospital Ethics Committee. The Ethics Committee waived the requirement of written informed consent for participation.

Author Contributions

MK contributed to study design, interpretation, and writing of the manuscript. KM, MM, SM, MI, and AK contributed to study design and interpretation. YT contributed to study design, data analysis, and interpretation. TM and ME reviewed the manuscript. All authors have read and approved the final version of the manuscript.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnut.2022.896427/full#supplementary-material

References

1. Fouque D, Kalantar-Zadeh K, Kopple J, Cano N, Chauveau P, Cuppari L, et al. A proposed nomenclature and diagnostic criteria for protein-energy wasting in acute and chronic kidney disease. Kidney Int. (2008) 73:391–8. doi: 10.1038/sj.ki.5002585

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Kalantar-Zadeh K, Ikizler TA, Block G, Avram MM, Kopple JD. Malnutrition-inflammation complex syndrome in dialysis patients: causes and consequences. Am J Kidney Dis. (2003) 42:864–81. doi: 10.1016/j.ajkd.2003.07.016

PubMed Abstract | CrossRef Full Text | Google Scholar

3. Acchiardo SR, Moore LW, Latour PA. Malnutrition as the main factor in morbidity and mortality of hemodialysis patients. Kidney Int Suppl. (1983) 16:S199–203.

PubMed Abstract | Google Scholar

4. Qureshi AR, Alvestrand A, Danielsson A, Divino-Filho JC, Gutierrez A, Lindholm B, et al. factors predicting malnutrition in hemodialysis patients: a cross-sectional study. Kidney Int. (1998) 53:773–82. doi: 10.1046/j.1523-1755.1998.00812.x

PubMed Abstract | CrossRef Full Text | Google Scholar

5. Kobayashi I, Ishimura E, Kato Y, Okuno S, Yamamoto T, Yamakawa T, et al. Geriatric nutritional risk index, a simplified nutritional screening index, is a significant predictor of mortality in chronic dialysis patients. Nephrol Dial Transplant. (2010) 25:3361–5. doi: 10.1093/ndt/gfq211

PubMed Abstract | CrossRef Full Text | Google Scholar

6. Steiber AL, Kalantar-Zadeh K, Secker D, McCarthy M, Sehgal A, McCann L. Subjective global assessment in chronic kidney disease: a review. J Ren Nutr. (2004) 14:191–200. doi: 10.1016/S1051-2276(04)00139-6

PubMed Abstract | CrossRef Full Text | Google Scholar

7. Kalantar-Zadeh K, Kleiner M, Dunne E, Lee GH, Luft FC. A modified quantitative subjective global assessment of nutrition for dialysis patients. Nephrol Dial Transplant. (1999) 14:1732–8. doi: 10.1093/ndt/14.7.1732

PubMed Abstract | CrossRef Full Text | Google Scholar

8. Adequacy of dialysis and nutrition in continuous peritoneal dialysis: association with clinical outcomes. Canada-USA (Canusa) Peritoneal Dialysis Study Group. J Am Soc Nephrol. (1996) 7:198–207. doi: 10.1681/ASN.V72198

PubMed Abstract | CrossRef Full Text | Google Scholar

9. Kalantar-Zadeh K, Kopple JD, Block G, Humphreys MH. A malnutrition-inflammation score is correlated with morbidity and mortality in maintenance hemodialysis patients. Am J Kidney Dis. (2001) 38:1251–63. doi: 10.1053/ajkd.2001.29222

PubMed Abstract | CrossRef Full Text | Google Scholar

10. Kanda E, Kato A, Masakane I, Kanno Y. A New nutritional risk index for predicting mortality in hemodialysis patients: nationwide cohort study. PLoS ONE. (2019) 14:e0214524. doi: 10.1371/journal.pone.0214524

PubMed Abstract | CrossRef Full Text | Google Scholar

11. Shimamoto S, Yamada S, Hiyamuta H, Arase H, Taniguchi M, Tsuruya K, et al. Association of the nutritional risk index for Japanese hemodialysis patients with long-term mortality: the q-cohort study. Clin Exp Nephrol. (2022) 26:59–67. doi: 10.1007/s10157-021-02124-6

PubMed Abstract | CrossRef Full Text | Google Scholar

12. Kanno Y, Kanda E, Kato A. Methods and nutritional interventions to improve the nutritional status of dialysis patients in Japan-a narrative review. Nutrients. (2021) 13:1390. doi: 10.3390/nu13051390

PubMed Abstract | CrossRef Full Text | Google Scholar

13. Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European Consensus on definition and diagnosis: report of the European Working Group on sarcopenia in older people. Age Ageing. (2010) 39:412–23. doi: 10.1093/ageing/afq034

PubMed Abstract | CrossRef Full Text | Google Scholar

14. Kim JK, Choi SR, Choi MJ, Kim SG, Lee YK, Noh JW, et al. Prevalence of and factors associated with sarcopenia in elderly patients with end-stage renal disease. Clin Nutr. (2014) 33:64–8. doi: 10.1016/j.clnu.2013.04.002

PubMed Abstract | CrossRef Full Text | Google Scholar

15. Mori K, Nishide K, Okuno S, Shoji T, Emoto M, Tsuda A, et al. Impact of diabetes on sarcopenia and mortality in patients undergoing hemodialysis. BMC Nephrol. (2019) 20:105. doi: 10.1186/s12882-019-1271-8

PubMed Abstract | CrossRef Full Text | Google Scholar

16. Fahal IH. Uraemic sarcopenia: aetiology and implications. Nephrol Dial Transplant. (2014) 29:1655–65. doi: 10.1093/ndt/gft070

PubMed Abstract | CrossRef Full Text | Google Scholar

17. Allman MA, Stewart PM, Tiller DJ, Horvath JS, Duggin GG, Truswell AS. Energy supplementation and the nutritional status of hemodialysis patients. Am J Clin Nutr. (1990) 51:558–62. doi: 10.1093/ajcn/51.4.558

PubMed Abstract | CrossRef Full Text | Google Scholar

18. Tietze IN, Pedersen EB. Effect of fish protein supplementation on aminoacid profile and nutritional status in haemodialysis patients. Nephrol Dial Transplant. (1991) 6:948–54. doi: 10.1093/ndt/6.12.948

PubMed Abstract | CrossRef Full Text | Google Scholar

19. Eustace JA, Coresh J, Kutchey C, Te PL, Gimenez LF, Scheel PJ, et al. Randomized double-blind trial of oral essential amino acids for dialysis-associated hypoalbuminemia. Kidney Int. (2000) 57:2527–38. doi: 10.1046/j.1523-1755.2000.00112.x

PubMed Abstract | CrossRef Full Text | Google Scholar

20. Chen LK, Woo J, Assantachai P, Auyeung TW, Chou MY, Iijima K, et al. Asian Working Group for Sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment. J Am Med Dir Assoc. (2020) 21:300–7.e2. doi: 10.1016/j.jamda.2019.12.012

PubMed Abstract | CrossRef Full Text | Google Scholar

21. Kurajoh M, Mori K, Miyabe M, Matsufuji S, Kizu A, Tsujimoto Y, et al. Xanthine oxidoreductase inhibitor use associated with reduced risk of sarcopenia and severe sarcopenia in patients undergoing hemodialysis. Front Med. (2022) 9:817578. doi: 10.3389/fmed.2022.817578

PubMed Abstract | CrossRef Full Text | Google Scholar

22. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. (2004) 27(Suppl 1):S5–10. doi: 10.2337/diacare.27.2007.S5

PubMed Abstract | CrossRef Full Text | Google Scholar

23. Miyabe M, Kurajoh M, Mori K, Okuno S, Okada S, Emoto M, et al. Superiority of glycated albumin over glycated haemoglobin as indicator of glycaemic control and predictor of all-cause mortality in patients with type 2 diabetes mellitus receiving peritoneal dialysis. Ann Clin Biochem. (2019) 56:684–91. doi: 10.1177/0004563219873688

PubMed Abstract | CrossRef Full Text | Google Scholar

24. Matsufuji S, Shoji T, Yano Y, Tamaru A, Tsuchikura S, Miyabe M, et al. Difficulty in activities of daily living and falls in patients undergoing hemodialysis: a cross-sectional study with nondialysis controls. Hemodial Int. (2021). doi: 10.1111/hdi.12930

PubMed Abstract | CrossRef Full Text | Google Scholar

25. Cheung YM, Roff G, Grossmann M. Precision of the hologic horizon a dual energy X-ray absorptiometry in the assessment of body composition. Obes Res Clin Pract. (2020) 14:514–8. doi: 10.1016/j.orcp.2020.10.005

PubMed Abstract | CrossRef Full Text | Google Scholar

26. Inaba M, Kurajoh M, Okuno S, Imanishi Y, Yamada S, Mori K, et al. Poor muscle quality rather than reduced lean body mass is responsible for the lower serum creatinine level in hemodialysis patients with diabetes mellitus. Clin Nephrol. (2010) 74:266–72. doi: 10.2379/CNX06500

PubMed Abstract | CrossRef Full Text | Google Scholar

27. Kurajoh M, Inaba M, Motoyama K, Kuriyama N, Ozaki E, Koyama T, et al. Inverse association of plasma leptin with cortical thickness at distal radius determined with a quantitative ultrasound device in patients with type 2 diabetes mellitus. J Diabetes Investig. (2020) 11:174–83. doi: 10.1111/jdi.13071

PubMed Abstract | CrossRef Full Text | Google Scholar

28. Matsufuji S, Shoji T, Yano Y, Tsujimoto Y, Kishimoto H, Tabata T, et al. Effect of chair stand exercise on activity of daily living: a randomized controlled trial in hemodialysis patients. J Ren Nutr. (2015) 25:17–24. doi: 10.1053/j.jrn.2014.06.010

PubMed Abstract | CrossRef Full Text | Google Scholar

29. Ozden F, Coskun G, Bakirhan S. The test-retest reliability and concurrent validity of the five times sit to stand test and step test in older adults with total hip arthroplasty. Exp Gerontol. (2020) 142:111143. doi: 10.1016/j.exger.2020.111143

PubMed Abstract | CrossRef Full Text | Google Scholar

30. Nishimura T, Arima K, Okabe T, Mizukami S, Tomita Y, Kanagae M, et al. Usefulness of chair stand time as a surrogate of gait speed in diagnosing sarcopenia. Geriatr Gerontol Int. (2017) 17:659–61. doi: 10.1111/ggi.12766

PubMed Abstract | CrossRef Full Text | Google Scholar

31. Tominaga H, Oku M, Arishima Y, Ikeda T, Ishidou Y, Nagano S, et al. Association between bone mineral density, muscle volume, walking ability, and geriatric nutritional risk index in hemodialysis patients. Asia Pac J Clin Nutr. (2018) 27:1062–6. doi: 10.6133/apjcn.052018.03

PubMed Abstract | CrossRef Full Text | Google Scholar

32. Bakkal H, Dizdar OS, Erdem S, Kulakoglu S, Akcakaya B, Katircilar Y, et al. The relationship between hand grip strength and nutritional status determined by malnutrition inflammation score and biochemical parameters in hemodialysis patients. J Ren Nutr. (2020) 30:548–55. doi: 10.1053/j.jrn.2020.01.026

PubMed Abstract | CrossRef Full Text | Google Scholar

33. Chen SC, Chung WS, Wu PY, Huang JC, Chiu YW, Chang JM, et al. Associations among geriatric nutrition risk index, bone mineral density, body composition and handgrip strength in patients receiving hemodialysis. Nutrition. (2019) 65:6–12. doi: 10.1016/j.nut.2019.02.013

PubMed Abstract | CrossRef Full Text | Google Scholar

34. Vanden Wyngaert K, Celie B, Calders P, Eloot S, Holvoet E, Van Biesen W, et al. Markers of protein-energy wasting and physical performance in haemodialysis patients: a cross-sectional study. PLoS ONE. (2020) 15:e0236816. doi: 10.1371/journal.pone.0236816

PubMed Abstract | CrossRef Full Text | Google Scholar

35. Giglio J, Kamimura MA, Lamarca F, Rodrigues J, Santin F, Avesani CM. Association of sarcopenia with nutritional parameters, quality of life, hospitalization, and mortality rates of elderly patients on hemodialysis. J Ren Nutr. (2018) 28:197–207. doi: 10.1053/j.jrn.2017.12.003

PubMed Abstract | CrossRef Full Text | Google Scholar

36. Reis JMS, Alves LS, Vogt BP. According to revised EWGSOP sarcopenia consensus cut-off points, low physical function is associated with nutritional status and quality of life in maintenance hemodialysis patients. J Ren Nutr. (2021). doi: 10.1053/j.jrn.2021.06.011

PubMed Abstract | CrossRef Full Text | Google Scholar

37. Kono K, Moriyama Y, Yabe H, Hara A, Ishida T, Yamada T, et al. Relationship between malnutrition and possible sarcopenia in the Awgs 2019 consensus affecting mortality in hemodialysis patients: a prospective cohort study. BMC Nephrol. (2021) 22:378. doi: 10.1186/s12882-021-02566-w

PubMed Abstract | CrossRef Full Text | Google Scholar

38. Lin YL, Liou HH, Lai YH, Wang CH, Kuo CH, Chen SY, et al. Decreased serum fatty acid binding protein 4 concentrations are associated with sarcopenia in chronic hemodialysis patients. Clin Chim Acta. (2018) 485:113–8. doi: 10.1016/j.cca.2018.06.025

PubMed Abstract | CrossRef Full Text | Google Scholar

39. Ren H, Gong D, Jia F, Xu B, Liu Z. Sarcopenia in patients undergoing maintenance hemodialysis: incidence rate, risk factors and its effect on survival risk. Ren Fail. (2016) 38:364–71. doi: 10.3109/0886022X.2015.1132173

PubMed Abstract | CrossRef Full Text | Google Scholar

40. Houston DK, Nicklas BJ, Ding J, Harris TB, Tylavsky FA, Newman AB, et al. Dietary protein intake is associated with lean mass change in older, community-dwelling adults: the health, aging, and body composition (Health Abc) study. Am J Clin Nutr. (2008) 87:150–5. doi: 10.1093/ajcn/87.1.150

PubMed Abstract | CrossRef Full Text | Google Scholar

41. Bollwein J, Diekmann R, Kaiser MJ, Bauer JM, Uter W, Sieber CC, et al. Distribution but not amount of protein intake is associated with frailty: a cross-sectional investigation in the region of Nurnberg. Nutr J. (2013) 12:109. doi: 10.1186/1475-2891-12-109

PubMed Abstract | CrossRef Full Text | Google Scholar

42. Mendonca N, Hengeveld LM, Visser M, Presse N, Canhao H, Simonsick EM, et al. Low protein intake, physical activity, and physical function in european and north american community-dwelling older adults: a pooled analysis of four longitudinal aging cohorts. Am J Clin Nutr. (2021) 114:29–41. doi: 10.1093/ajcn/nqab051

PubMed Abstract | CrossRef Full Text | Google Scholar

43. Cermak NM, Res PT, de Groot LC, Saris WH, van Loon LJ. Protein supplementation augments the adaptive response of skeletal muscle to resistance-type exercise training: a meta-analysis. Am J Clin Nutr. (2012) 96:1454–64. doi: 10.3945/ajcn.112.037556

PubMed Abstract | CrossRef Full Text | Google Scholar

44. Malafarina V, Uriz-Otano F, Iniesta R, Gil-Guerrero L. Effectiveness of nutritional supplementation on muscle mass in treatment of sarcopenia in old age: a systematic review. J Am Med Dir Assoc. (2013) 14:10–7. doi: 10.1016/j.jamda.2012.08.001

PubMed Abstract | CrossRef Full Text | Google Scholar

45. Yoshimura Y, Wakabayashi H, Yamada M, Kim H, Harada A, Arai H. Interventions for treating sarcopenia: a systematic review and meta-analysis of randomized controlled studies. J Am Med Dir Assoc. (2017) 18:553e1–e16. doi: 10.1016/j.jamda.2017.03.019

PubMed Abstract | CrossRef Full Text | Google Scholar

46. Beaudart C, Sanchez-Rodriguez D, Locquet M, Reginster JY, Lengele L, Bruyere O. Malnutrition as a strong predictor of the onset of sarcopenia. Nutrients. (2019) 11:2883. doi: 10.3390/nu11122883

PubMed Abstract | CrossRef Full Text | Google Scholar

47. Mori K. Maintenance of skeletal muscle to counteract sarcopenia in patients with advanced chronic kidney disease and especially those undergoing hemodialysis. Nutrients. (2021) 13:1538. doi: 10.3390/nu13051538

PubMed Abstract | CrossRef Full Text | Google Scholar