Bioelectrical impedance analysis–derived phase angle predicts possible sarcopenia in patients on maintenance hemodialysis: A retrospective study

Bioelectrical impedance analysis–derived phase angle predicts possible sarcopenia in patients on maintenance hemodialysis: A retrospective study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Bioelectrical impedance analysis–derived phase angle predicts possible sarcopenia in patients on maintenance hemodialysis: A retrospective study Ying Zeng, Yang Chen, Yujie Yang, Ying Qiu, Huaihong Yuan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4064617/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Oct, 2024 Read the published version in BMC Nephrology → Version 1 posted 10 You are reading this latest preprint version Abstract Background Early identification of possible sarcopenia in patients on maintenance hemodialysis (MHD) is important to prevent adverse outcomes and improve the quality of life of these patients. The aim of this study was to investigate the relationship between phase angle (Pha) and possible sarcopenia and to assess its performance as a predictor of possible sarcopenia in MHD patients. Methods Data were retrospectively collected from outpatient under going MHD at Wenjiang Hemodialysis Center in the Department of Nephrology in West China Hospital, Sichuan University, Chengdu, China. The 2019 consensus update by Asian working group for sarcopenia (AWGS) was used to assess whether a MHD patient had sarcopenia. A total of 244 MHD patients were collected in this study, and after excluding patients with sarcopenia, data from 122 men (56 with possible sarcopenia) and 96 women (55 with possible sarcopenia) patients were included in this study. Participants were divided into a possible sarcopenic group and a non-sarcopenic group to develop a binary classification. Results After eliminating handgrip strength (HGS), short physical performance battery (SPPB), and skeletal muscle index (SMI), the best three features for possible sarcopenia identifcation of men patients are age, body mass index (BMI), and Pha ( P < 0.05). Meanwhile, age, and Pha are the best two features for Women ( P < 0.05). Spearman analysis showed that Pha was significantly negatively associated with possible sarcopenia (men: r =−0.501, P < 0.001; women: r =−0.356, P < 0.001). Pha showed significant positive associations with HGS, SPPB and SMI (men: r = 0.590, P < 0.001、 r = 0.485, P < 0.001、 r = 0.338, P < 0.001; women: r = 0.374, P < 0.001、 r = 0.360, P < 0.001、 r = 0.290, P = 0.004). The results of receiver operating characteristic (ROC) curve analysis showed that the area under the receiver operating characteristic curves (AUC) of Pha in screening male possible sarcopenia was 0.790, with sensitivity of 78.57%, specificity of 74.24%, and the optimal cutoff value of 6.52°. The AUC of Pha in screening women for possible sarcopenia was 0.707, sensitivity of 58.18%, specificity of 76.74%, and optimal cutoff value of 5.60°. Conclusions Pha may be a useful and simple predictor of the risk of possible sarcopenia in patients with MHD, and more research is needed to further promote the use of Pha in possible sarcopenia. maintenance hemodialysis patients bioimpedance phase angle possible sarcopenia receiver operating characteristic curve Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Background Chronic kidney disease (CKD) has become an important public health problem that jeopardizes human health globally due to its high prevalence, high disability rate, high medical expenses and low awareness rate - "three highs and one low". There are about 132.3 million CKD patients in China as of 2017 [ 1 ] .Once CKD patients enter end-stage kidney disease (ESKD), renal replacement therapy (including hemodialysis, peritoneal dialysis, or renal transplantation) is required to maintain life, which seriously affects the quality of life of patients [ 2 ] . According to a survey, maintenance hemodialysis (MHD) is still the main and most commonly used treatment for ESKD, and about 89.4% of patients in China choose MHD [ 3 ] . MHD patients, compared with the general population, commonly have reduced body protein and energy reserves due to nutrient loss and inadequate intake during dialysis [ 4 ] . In addition, decreased glomerular filtration rate or progression of proteinuria, as well as dialysis treatments, accelerate muscle protein catabolism and down-regulation of mitochondrial function, leading to decreased skeletal muscle strength and reduced skeletal muscle mass in patients with MHD, making MHD patients increasingly susceptible to sarcopenia [ 5 , 6 ] . Sarcopenia is a progressive generalized loss of muscle mass and/or loss of muscle strength or physical activity function with age [ 7 ] . According to a survey, the average prevalence of skeletal sarcopenia in patients with MHD is 28.5% [ 8 ] . Sarcopenia has been shown to be strongly associated with a variety of adverse outcomes such as falls, debilitation, fractures, and malnutrition [ 9 – 11 ] , and carries a risk of prolonged hospitalization and increased mortality [ 12 ] . Previous diagnoses of sarcopenia were mainly characterized by reduced muscle mass, but not by reduced muscle function and muscle strength [ 13 ] . However, it has been shown that slow gait speed and weaker muscle strength, even after adjusting for muscle content and other confounders, are associated with mortality, suggesting that muscle function and strength may be more relevant predictors of survival than muscle mass [ 14 ] . In a prospective study of 142 hemodialysis patients, Kim KV [ 15 ] et al. found that skeletal sarcopenia was strongly associated with long-term mortality and cardiovascular events in hemodialysis patients, and that the assessment of muscle strength and muscle mass could provide additional prognostic information for survival in patients with end-stage renal disease. A new definition of skeletal sarcopenia was released by European Working Group on Sarcopenia in Older People (EWGSOP) in 2019, which adds muscle function to the previous definition based solely on low muscle mass testing [ 16 ] . It has been shown that muscle strength is superior to muscle mass in predicting poor outcomes [ 17 ] . Moreover, the 2019 AWGS introduced "possible sarcopenia", which refers to a decline in muscle strength and/or somatic function, and advocates early identification and intervention [ 18 ] . Therefore, early screening, diagnosis, and treatment of possible sarcopenia is important to slow down the rate of muscle decay and improve the quality of life of the population. Currently, bioelectrical impedance analysis (BIA) and dualenergy X-ray absorptiometry (DXA) measurements are the recommended modalities under the criteria for the diagnosis of sarcopenia. However, BIA measurements are avoided in patients with pacemakers, and DXA is expensive and requires some installation space, so both instruments cannot always be used in patients with MHD. Therefore, alternative strategies using tools available in clinical practice are necessary, and we need to establish a simple diagnostic index for diagnosing sarcopenia in patients with MHD. In this study, we screened for sarcopenia in MHD patients according to the AWGS2019 diagnostic criteria, and we hope to identify an auxiliary screening indicator for the identification of sarcopenia in MHD patients, which will facilitate the early identification of those at risk for sarcopenia by healthcare professionals. The latest consensus of the 2019 EWGSOP on the diagnosis of sarcopenia that Pha can be used to assess muscle mass [ 16 ] . Pha is an index obtained by measuring the electrical resistance and reactance of the human body and calculating the ratio of the inverse tangent of the two by bioelectrical impedance analysis (BIA), which reflects the water content inside and outside the cell and the integrity of the cell membrane [ 19 ] . Pha values in healthy individuals range from 6.4° to 8.2° [ 20 ] . There have been many researchers who have used Pha to predict sarcopenia [ 21 – 23 ] . However, no studies have been conducted for possible sarcopenia. Moreover, sarcopenia is affected by many factors. In the past, the prediction of sarcopenia usually used gender as an influencing factor rather than a grouping index, which homogenized the prediction of sarcopenia, and it has been shown that gender-differentiated aging patterns involve changes in muscle mass and muscle strength [ 24 ] . Therefore, the present study focuses on gender differences to discuss the screening ability of Pha in possible sarcopenia, to further help clinicians to accurately screen for possible sarcopenia early and provide personalized preventive and therapeutic measures for patients with possible sarcopenia early, thereby slowing down the further progression of possible sarcopenia. Materials And Methods Study design and participants Use of convenience sampling. Data were retrospectively collected from outpatient under going MHD at Wenjiang Hemodialysis Center in the Department of Nephrology in West China Hospital, Sichuan University, Chengdu, China. The inclusion criteria were (1) age ≥ 18 years, (2) receiving maintenance hemodialysis for at least 3 months, (3) thinking and language expression ability is normal, and (4) volunteer to participate in this study and sign the informed consent form. The exclusion criteria were as follows: (1) cognitive impairment or mental illness, (2) patients with major disease changes in the last three months, (3) pregnant or lactating, (4) body mutilation, Immobility or other reasons can not cooperate, and (5) the InBodyS10 body composition analysis measurement cannot be performed, such as cardiovascular stent implantation, pacemaker installation, artificial joint replacement, etc. A total of 244 MHD patients were collected in this study, and after excluding patients with sarcopenia, data from 122 men (56 with possible sarcopenia) and 96 women (55 with possible sarcopenia) patients were included in this study. Data collection Prior to the study, two researchers were uniformly trained to assess questionnaires and measure anthropometric indicators. A face-to‐face interview was performed to verify demographics (sex, age) and characteristics (presence of diabetes mellitus and hypertension, and dialysis vintage). Using a wall‐secured stadiometer, a digital scale, and a retractable measuring tape, height, weight,and calf circumference (CC) were taken. Pha and body composition After dialysis, body composition was measured by multifrequency Bia (InBodyS10; InBody Co., Ltd Korea). All parameters, including Pha, SMI, and BMI, were directly measured and recorded by the devices. However, the SMI was used to evaluate the muscle mass in patients with MHD. The phase angle is estimated based on the ratio of reactance (Xc) to resistance (R) and the formula is below: Pha (°) = arctangent (Xc / R) × (180° / π) [ 25 ] . Muscle strength Muscle strength was assessed in MHD patients using HGS. Before dialysis, the researchers measured the patient's HGS with an electronic grip strength fitness tester (Zhongshan Camry Electronics Co., LTD.), asked the patient to measure with the non-fistula hand, and kept the standing position, the arms were naturally drooping, measured twice for 5s interval, and the maximum value was recorded. Physical performance measurements SPPB is recommended for evaluating physical performance in MHD patients [ 26 ] . The SPPB consists of 3 components: repeated chair stand, gait speed, and balance tests. Each component is scored on a scale of 0–4 points and the total score is 0–12 points. Patients with a score of ≤ 9 were identified as having low physical performance [ 18 ] . Sarcopenia diagnosis The diagnosis was made using the diagnostic consensus for sarcopenia developed by the 2019 AWGS [ 18 ] 。The diagnosis are as follows: ① SMI: <7.0 kg/㎡in men and <5.7 kg/㎡ in women. ② HGS: <28.0 kg for men and < 18.0 kg for women. ③ SPPB: Total score ≤ 9 points. Patients who meet the diagnostic criteria ① and ② and (or) ③ can be diagnosed with sarcopenia. Patients who meet the diagnostic criteria ② and (or) ③ can be diagnosed with possible sarcopenia. The present study analyzed possible sarcopenia as experimental group and non-sarcopenia as control group. Statistical analysis Statistical analysis was performed in SPSS, version 27.0 (SPSS Inc., Chicago, IL, USA). After the normality test. Measurement data consistent with the normal distribution were expressed by means and standard deviation (SD). Measometric data with non-normal distribution were expressed using median and interquartile range (IQR). Statistical methods were performed using the independent sample t-test and the Kruskal-Wallis H test. The categorical variables were presented as numbers and percentages. Categorical data were tested by the chi-square test or the Fisher exact probability method. Using binary logistic regression model (enter method) was used to analyze the factors affecting possible sarcopenia in men and women MHD patients, calculating the odds ratio (OR) and its 95% confidence interval (CI). The correlation between Pha and possible sarcopenic components was analyzed by Spearman. The ROC curve was used to evaluate the ability of Pha to screen for possible sarcopenia, and the AUC, sensitivity and specificity were significantly different, yielding the best cutoff value. Spearman Windows version GraphPad Prism (version 10.1.0, GraphPad Software, San Diego, California USA, www.graphpad.com ). The receiver operating characteristic (ROC) curve was plotted using MedCalc19.0. the significance value adopted was P < 0.05. Results General clinical characteristics of the patients Table 1 The mean age of men MHD patients was (53.12 ± 13.84) years, the median age on dialysis was 48.0 (19.5, 84.0) months, the median CC was 33 (31, 35) cm, the mean BMI was (22.52 ± 3.01) kg/㎡, and the mean Pha was (6.42 ± 1.22)°, and 107 (87.7%) of the patients had hypertension, 33 (27.0%) patients had diabetes. Table 2 The mean age of women MHD patients was (52.37 ± 13.06) years, the median age on dialysis was 58.5 (24.0, 84.5) months, the median CC was 31 (29, 33) cm, the mean BMI was (22.24 ± 2.95) kg/㎡, the mean Pha was (5.77 ± 1.08)°, and 82 (83.7%) of the patients had hypertension, 16 (16.3%) patients had diabetes. Results of the univariate analysis The two groups of men MHD patients were comparable in terms of age, diabetes and Pha. And the patients in the possible sarcopenia group had a greater mean age, more comorbid diabetes, and lower mean Pha compared to the patients in the non-sarcopenia group ( P < 0.05). The two groups of women MHD patients were comparable in terms of age, diabetes and Pha. And the patients in the possible sarcopenia group had a greater mean age, and lower mean Pha compared to the patients in the non-sarcopenia group ( P < 0.05). Results of the binary logistic regression analysis Table 3 Age, BMI, and Pha were influential factors in the development of possible sarcopenia in men MHD patients ( P < 0.05). Table 4 Age, and Pha were influential factors in the development of possible sarcopenia in women MHD patients ( P < 0.05). Correlates between Pha and possible sarcopenia Spearman correlation analysis showed Pha and possible sarcopenia (men: r =−0.501, P < 0.001; women: r =−0.356, P < 0.001), and HGS (men: r = 0.590, P < 0.001; women: r = 0.374, P < 0.001), and SPPB (men: r = 0.485, P < 0.001; women: r = 0.360, P < 0.001), and SMI (men: r = 0.338, P < 0.001; women: r = 0.290, P = 0.004), all showed significant associations (Fig. 1–6). Screening ability analysis of Pha in the possible sarcopenia screen The AUC of Pha in screening men for possible sarcopenia was 0.790, with a sensitivity of 78.57%, a specificity of 74.24%, and an optimal cutoff value of 6.52° (Fig. 7). The AUC of Pha in screening women for possible sarcopenia was 0.707, with a sensitivity of 58.18%, a specificity of 76.74%, and an optimal cutoff value of 5.6° (Fig. 8). Discussion Sarcopenia was estimated to influence 10%-16% of the elderly worldwide. The prevalence of sarcopenia ranged from 18% in diabetic patients to 66% in patients with unresectable esophageal cancer [ 27 ] . Patients with MHD have a significantly increased incidence of sarcopenia compared to healthy subjects. Souza [ 28 ] et al. found that among non-dialysis patients with CKD in South America (mean age 74 years), the prevalence of sarcopenia was 34.5% in patients with CKD stages 2 and 3A, whereas the prevalence was as high as 65.5% in patients with CKD stages 3B, 4 and 5. Yoowannakul [ 29 ] et al. found that the prevalence of sarcopenia in Asian hemodialysis patients (mean age 68 years) was 59.6%. Sarcopenia has been shown to be a common complication in patients with MHD and is associated with falls, fractures, malnutrition, and adverse cardiovascular events, posing a serious threat to patient safety [ 9 – 11 ] . In order to prevent the development of sarcopenia, the risk of developing sarcopenia should be screened in advance. Therefore, it is particularly important to screen patients in advance for the presence of decreased muscle strength and muscle function (i.e., possible sarcopenia). A simple and feasible Pha for the prediction of possible sarcopenia in MHD patients was used in this study to investigate the relationship between Pha and possible sarcopenia and the predictive value of Pha in possible sarcopenia, with a focus on gender specificity. The results show that Pha plays an independent role in predicting and identifying possible sarcopenia in MHD patients of both sexes. Pha is often used in the assessment of nutritional status [ 30 ] , it is considered to be a proxy for water distribution and somatic cell mass, and it also correlates with muscle strength and is a valid predictor of different clinical outcomes. Pha aids in the diagnosis of skeletal sarcopenia more easily and quickly than the 2019 AWGS diagnostic criteria. Many studies have shown the importance of Pha for the diagnosis of sarcopenia in patients with MHD [ 31 – 35 ] . Yamada [ 36 ] et al. divided 1,009 community-dwelling older adults into four groups (normal, presarcopenia, dynapenia, and sarcopenia), and the results of their study showed that there were significant differences in phase angles among the four groups of older adults. Kilic [ 37 ] et al. assessed 263 community-dwelling and hospitalized older adults by BIA and anthropometry, and showed that phase angle was an independently relevant variable for screening for sarcopenia, and that smaller phase angles increased the risk of developing sarcopenia. Since 2010, the diagnostic criteria for skeletal sarcopenia are not only muscle mass, but also measures of muscle function and muscle strength [ 18 , 38 – 40 ] . Sarcopenia is categorized into stages of non-sarcopenia, possible sarcopenia, sarcopenia and severe sarcopenia according to the AWGS diagnostic consensus [ 18 ] . Different stages of sarcopenia have different symptoms and clinical manifestations, and preventive and therapeutic measures may vary. Therefore, early diagnosis and intervention of possible sarcopenia is particularly important. In this study, we examined the relationship between Pha and possible sarcopenia in men and women MHD patients. Our study found that Pha plays an independent role in predicting and identifying possible sarcopenia in patients treated for MHD. A number of studies have also confirmed the ability of Pha to better predict sarcopenia [ 21 – 23 ] . In this study, we also found that age and Pha were influential factors for possible sarcopenia in both men and women MHD patients and Pha was significantly negatively correlated with possible sarcopenia and significantly positively correlated with HGS, SPPB, and SMI. Pha was directly correlated with muscular strength and declined with age [ 41 , 42 ] .Uemura [ 43 ] et al. found a significant relationship between Pha and SMI and HGS in both men and women was positively correlated, which is similar to our findings, as muscle mass and muscle strength declines in low Pha populations, which further leads to a decline in physical functional performance [ 44 ] . Although patients with possible sarcopenia have not yet developed sarcopenia, decreased muscle strength and muscle function can also affect the quality of life of patients. Therefore, healthcare professionals should increase their attention to patients with possible sarcopenia. The optimal cutoff value of Pha in this study was 6.52° in screening for possible sarcopenia in men and 5.60° in screening for possible sarcopenia in women, which is higher than that reported by Yamada [ 36 ] and others. The optimal cutoff value for Pha varied across studies, and differences in the optimal cutoff value for Pha were related to the choice of diagnostic criteria, racial differences, and the selection of the subject population. However, the reason for the wide variation in the cutoff value for predicting sarcopenia is that Pha varies by age and sex [ 45 , 46 ] , and it is therefore of interest to differentiate between men and women MHD patients in the onset and diagnosis of possible sarcopenia. The sensitivity and specificity of the Pha values obtained in this study for the diagnosis of sarcopenia were not particularly high, which may be related to the fact that this study was a single-center cross-sectional study with a limited sample size, which may have unavoidable selection bias, and although the results showed that Pha was significantly associated with possible sarcopenia and its components, they could not explain the causal relationship. Second, we screened patients who were able to complete BIA testing and muscle function tests, and perhaps the number of actual MHD patients with possible sarcopenia was higher. Although Pha has the ability to screen for possible sarcopenia, it is not as diagnostically accurate as CT, MRI, and DXA, so the accuracy of the study results is somewhat compromised. More prospective studies are needed to further promote the use of Pha in the diagnosis of possible sarcopenia. Conclusion In conclusion, there have been a number of papers that have used different approaches to explore the relationship between Pha and sarcopenia, but there are no relevant studies that have explored the ability of Pha to screen for possible sarcopenia in patients with MHD, using gender as a specific indicator. The results of this study suggest that Pha is a useful and simple predictor of the risk of possible sarcopenia in patients with MHD. Pha ≤ 6.52° can be used as a predictive threshold for the combination of possible sarcopenia in men MHD patients, and Pha ≤ 5.60° can be used as a predictive threshold for the combination of possible sarcopenia in women MHD patients. It provides a theoretical reference for early screening, diagnosis and treatment of possible sarcopenia in MHD patients of different genders, slows down muscle decay, improves the quality of life of the population, and provides individualized preventive and therapeutic measures. More research is needed to further promote the application of Pha in possible sarcopenia. Abbreviations AUC The area under the receiver operating characteristic curves AWGS Asia Working Group for Sarcopenia BIA Bioelectrical impedance analysis BMI Body mass index CC Calf circumference CI Confidence interval CKD Chronic kidney disease DM Diabetes mellitus DXA Dualenergy X-ray absorptiometry ESKD End-stage renal disease EWGSOP European Working Group on Sarcopenia in Older People HGS Handgrip strength HTN Hypertension IQR Interquartile range MHD Maintenance hemodialysis OR Odds ratio Pha Phase angle ROC Receiver operating characteristic SD Standard deviation SMI Skeletal muscle index SPPB Short physical performance battery Declarations Acknowledgments The authors would like to thank all of the healthcare providers and patients who participated in this study from Wenjiang Hemodialysis Center in the Department of Nephrology at West China Hospital, Sichuan University, Chengdu, China. Author Contributions Y.Z. and Y.C. participated in the conception and design of the study and drafted the manuscript. Y.Z. and Y.C. analyzed the data. H.H.Y. organized and coordinated the research efforts. Y.J.Y. participated in the design of the study. Y.Q. participated in the acquisition of the data. Y.Z. and Y.C. were the major contributors in writing the manuscript. All authors reviewed the manuscript. The final manuscript was read and approved by all authors. Funding None Data Availability Data available on request from the corresponding author. Ethics approval and consent to participate This study was approved by the biomedical ethics committee of the West China University of Sichuan University (ethical approval number: 2020[1002]) and was performed in accordance with the principles of the Declaration of Helsinki. All patients provided a written informed consent. In the case of illiterate patients, the consent was read to them in the presence of a literate relative and they provided a fingerprint on the consent form to indicate their informed consent to participate. This form of informed consent was also approved by the biomedical ethics committee of the West China University of Sichuan University. Consent to publication Not applicable. Conflicts of interest All authors declare no conflict of interest. References Collaboration GCKD: Global, regional, and national burden of chronic kidney disease, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017 . Lancet (London, England) 2020, 395 (10225):709-733. Lv JC, Zhang LX: Prevalence and Disease Burden of Chronic Kidney Disease . Advances in experimental medicine and biology 2019, 1165 :3-15. Manganaro M, Baldovino S: First considerations on the SARS-CoV-2 epidemic in the Dialysis Units of Piedmont and Aosta Valley, Northern Italy . Journal of nephrology 2020, 33 (3):393-395. Pauzi FA, Sahathevan S, Khor BH, Narayanan SS, Zakaria NF, Abas F, Karupaiah T, Daud ZAM: Exploring Metabolic Signature of Protein Energy Wasting in Hemodialysis Patients . Metabolites 2020, 10 (7). Hanna RM, Ghobry L, Wassef O, Rhee CM, Kalantar-Zadeh K: A Practical Approach to Nutrition, Protein-Energy Wasting, Sarcopenia, and Cachexia in Patients with Chronic Kidney Disease . Blood purification 2020, 49 (1-2):202-211. Nishi H, Takemura K, Higashihara T, Inagi R: Uremic Sarcopenia: Clinical Evidence and Basic Experimental Approach . Nutrients 2020, 12 (6). Chen LK, Liu LK, Woo J, Assantachai P, Auyeung TW, Bahyah KS, Chou MY, Chen LY, Hsu PS, Krairit O et al : Sarcopenia in Asia: consensus report of the Asian Working Group for Sarcopenia . Journal of the American Medical Directors Association 2014, 15 (2):95-101. Shu X, Lin T, Wang H, Zhao Y, Jiang T, Peng X, Yue J: Diagnosis, prevalence, and mortality of sarcopenia in dialysis patients: a systematic review and meta-analysis . Journal of cachexia, sarcopenia and muscle 2022, 13 (1):145-158. Pérez-Zepeda MU, Sgaravatti A, Dent E: Sarcopenia and post-hospital outcomes in older adults: A longitudinal study . Archives of gerontology and geriatrics 2017, 69 :105-109. Billot M, Calvani R, Urtamo A, Sánchez-Sánchez JL, Ciccolari-Micaldi C, Chang M, Roller-Wirnsberger R, Wirnsberger G, Sinclair A, Vaquero-Pinto N et al : Preserving Mobility in Older Adults with Physical Frailty and Sarcopenia: Opportunities, Challenges, and Recommendations for Physical Activity Interventions . Clinical interventions in aging 2020, 15 :1675-1690. Sim M, Prince RL, Scott D, Daly RM, Duque G, Inderjeeth CA, Zhu K, Woodman RJ, Hodgson JM, Lewis JR: Sarcopenia Definitions and Their Associations With Mortality in Older Australian Women . Journal of the American Medical Directors Association 2019, 20 (1):76-82.e72. Rossi AP, Bianchi L, Volpato S, Bandinelli S, Guralnik J, Zamboni M, Ferrucci L: Dynapenic Abdominal Obesity as a Predictor of Worsening Disability, Hospitalization, and Mortality in Older Adults: Results From the InCHIANTI Study . The journals of gerontology Series A, Biological sciences and medical sciences 2017, 72 (8):1098-1104. Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, Martin FC, Michel JP, Rolland Y, Schneider SM et al : Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People . Age and ageing 2010, 39 (4):412-423. Kittiskulnam P, Chertow GM, Carrero JJ, Delgado C, Kaysen GA, Johansen KL: Sarcopenia and its individual criteria are associated, in part, with mortality among patients on hemodialysis . Kidney international 2017, 92 (1):238-247. Kim JK, Kim SG, Oh JE, Lee YK, Noh JW, Kim HJ, Song YR: Impact of sarcopenia on long-term mortality and cardiovascular events in patients undergoing hemodialysis . The Korean journal of internal medicine 2019, 34 (3):599-607. Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, Cooper C, Landi F, Rolland Y, Sayer AA et al : Sarcopenia: revised European consensus on definition and diagnosis . Age and ageing 2019, 48 (1):16-31. Schaap LA, van Schoor NM, Lips P, Visser M: Associations of Sarcopenia Definitions, and Their Components, With the Incidence of Recurrent Falling and Fractures: The Longitudinal Aging Study Amsterdam . The journals of gerontology Series A, Biological sciences and medical sciences 2018, 73 (9):1199-1204. Chen LK, Woo J, Assantachai P, Auyeung TW, Chou MY, Iijima K, Jang HC, Kang L, Kim M, Kim S et al : Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment . Journal of the American Medical Directors Association 2020, 21 (3):300-307.e302. Akamatsu Y, Kusakabe T, Arai H, Yamamoto Y, Nakao K, Ikeue K, Ishihara Y, Tagami T, Yasoda A, Ishii K et al : Phase angle from bioelectrical impedance analysis is a useful indicator of muscle quality . Journal of cachexia, sarcopenia and muscle 2022, 13 (1):180-189. Selberg O, Selberg D: Norms and correlates of bioimpedance phase angle in healthy human subjects, hospitalized patients, and patients with liver cirrhosis . European journal of applied physiology 2002, 86 (6):509-516. Kang SH, Do JY, Kim JC: Impedance-derived phase angle is associated with muscle mass, strength, quality of life, and clinical outcomes in maintenance hemodialysis patients . PloS one 2022, 17 (1):e0261070. Chen Y, Wu J, Ran L, Yu D, Chen X, Liu M: The combination of phase angle and age has a good diagnostic value for sarcopenia in continuous ambulatory peritoneal dialysis patients . Frontiers in nutrition 2022, 9 :1036796. Saitoh M, Ogawa M, Kondo H, Suga K, Takahashi T, Itoh H, Tabata Y: Bioelectrical impedance analysis-derived phase angle as a determinant of protein-energy wasting and frailty in maintenance hemodialysis patients: retrospective cohort study . BMC nephrology 2020, 21 (1):438. Tseng TG, Lu CK, Hsiao YH, Pan SC, Tai CJ, Lee MC: Development of Taiwan Risk Score for Sarcopenia (TRSS) for Sarcopenia Screening among Community-Dwelling Older Adults . International journal of environmental research and public health 2020, 17 (8). Wang Y, Hu Y, Zhang M, Jin H, Wen Y, Tang R, Wang B, Liu B, Liu H: Bioelectrical impedance analysis-derived phase angle predicts sarcopenia in patients on maintenance hemodialysis . Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition 2023, 38 (4):881-888. Uchida J, Suzuki Y, Imamura K, Yoshikoshi S, Nakajima T, Fukuzaki N, Harada M, Kamiya K, Matsuzawa R, Matsunaga A: The Association of Short Physical Performance Battery With Mortality and Hospitalization in Patients Receiving Hemodialysis . Journal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation 2023. Yuan S, Larsson SC: Epidemiology of sarcopenia: Prevalence, risk factors, and consequences . Metabolism: clinical and experimental 2023, 144 :155533. Souza VA, Oliveira D, Barbosa SR, Corrêa J, Colugnati FAB, Mansur HN, Fernandes N, Bastos MG: Sarcopenia in patients with chronic kidney disease not yet on dialysis: Analysis of the prevalence and associated factors . PloS one 2017, 12 (4):e0176230. Yoowannakul S, Tangvoraphonkchai K, Vongsanim S, Mohamed A, Davenport A: Differences in the prevalence of sarcopenia in haemodialysis patients: the effects of gender and ethnicity . Journal of human nutrition and dietetics : the official journal of the British Dietetic Association 2018, 31 (5):689-696. Tan RS, Liang DH, Liu Y, Zhong XS, Zhang DS, Ma J: Bioelectrical Impedance Analysis-Derived Phase Angle Predicts Protein-Energy Wasting in Maintenance Hemodialysis Patients . Journal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation 2019, 29 (4):295-301. Polegato BF, Herrera MA, Pereira BLB, Silva RAC, Gonçalves AF, Cavallari KA, Costa NA, Tanni SE, Azevedo PS, Dorna MS et al : Phase angle is associated with the length of ICU stay in patients with non-ST elevation acute coronary syndrome . Nutrire 2017, 42 (1):2. Dos Reis AS, Santos HO, Limirio LS, de Oliveira EP: Phase Angle Is Associated With Handgrip Strength but Not With Sarcopenia in Kidney Transplantation Patients . Journal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation 2019, 29 (3):196-204. Basile C, Della-Morte D, Cacciatore F, Gargiulo G, Galizia G, Roselli M, Curcio F, Bonaduce D, Abete P: Phase angle as bioelectrical marker to identify elderly patients at risk of sarcopenia . Experimental gerontology 2014, 58 :43-46. Reis BCA, de Branco FMS, Pessoa DF, Barbosa CD, dos Reis AS, de Medeiros LA, de Oliveira EP: Phase Angle Is Positively Associated With Handgrip Strength in Hospitalized Individuals . Topics in Clinical Nutrition 2018, 33 (2). Maddocks M, Kon SS, Jones SE, Canavan JL, Nolan CM, Higginson IJ, Gao W, Polkey MI, Man WD: Bioelectrical impedance phase angle relates to function, disease severity and prognosis in stable chronic obstructive pulmonary disease . Clinical nutrition (Edinburgh, Scotland) 2015, 34 (6):1245-1250. Yamada M, Kimura Y, Ishiyama D, Nishio N, Otobe Y, Tanaka T, Ohji S, Koyama S, Sato A, Suzuki M et al : Phase Angle Is a Useful indicator for Muscle Function in Older Adults . The journal of nutrition, health & aging 2019, 23 (3):251-255. Kilic MK, Kizilarslanoglu MC, Arik G, Bolayir B, Kara O, Dogan Varan H, Sumer F, Kuyumcu ME, Halil M, Ulger Z: Association of Bioelectrical Impedance Analysis-Derived Phase Angle and Sarcopenia in Older Adults . Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition 2017, 32 (1):103-109. Morley JE, Abbatecola AM, Argiles JM, Baracos V, Bauer J, Bhasin S, Cederholm T, Coats AJ, Cummings SR, Evans WJ et al : Sarcopenia with limited mobility: an international consensus . Journal of the American Medical Directors Association 2011, 12 (6):403-409. Muscaritoli M, Anker SD, Argilés J, Aversa Z, Bauer JM, Biolo G, Boirie Y, Bosaeus I, Cederholm T, Costelli P et al : Consensus definition of sarcopenia, cachexia and pre-cachexia: joint document elaborated by Special Interest Groups (SIG) "cachexia-anorexia in chronic wasting diseases" and "nutrition in geriatrics" . Clinical nutrition (Edinburgh, Scotland) 2010, 29 (2):154-159. Fielding RA, Vellas B, Evans WJ, Bhasin S, Morley JE, Newman AB, Abellan van Kan G, Andrieu S, Bauer J, Breuille D et al : Sarcopenia: an undiagnosed condition in older adults. Current consensus definition: prevalence, etiology, and consequences. International working group on sarcopenia . Journal of the American Medical Directors Association 2011, 12 (4):249-256. de Blasio F, Santaniello MG, de Blasio F, Mazzarella G, Bianco A, Lionetti L, Franssen FME, Scalfi L: Raw BIA variables are predictors of muscle strength in patients with chronic obstructive pulmonary disease . European journal of clinical nutrition 2017, 71 (11):1336-1340. Yamada Y, Buehring B, Krueger D, Anderson RM, Schoeller DA, Binkley N: Electrical Properties Assessed by Bioelectrical Impedance Spectroscopy as Biomarkers of Age-related Loss of Skeletal Muscle Quantity and Quality . The journals of gerontology Series A, Biological sciences and medical sciences 2017, 72 (9):1180-1186. Uemura K, Yamada M, Okamoto H: Association of bioimpedance phase angle and prospective falls in older adults . Geriatrics & gerontology international 2019, 19 (6):503-507. Tomeleri CM, Cavalcante EF, Antunes M, Nabuco HCG, de Souza MF, Teixeira DC, Gobbo LA, Silva AM, Cyrino ES: Phase Angle Is Moderately Associated With Muscle Quality and Functional Capacity, Independent of Age and Body Composition in Older Women . Journal of geriatric physical therapy (2001) 2019, 42 (4):281-286. Norman K, Stobäus N, Pirlich M, Bosy-Westphal A: Bioelectrical phase angle and impedance vector analysis--clinical relevance and applicability of impedance parameters . Clinical nutrition (Edinburgh, Scotland) 2012, 31 (6):854-861. Barbosa-Silva MC, Barros AJ, Wang J, Heymsfield SB, Pierson RN, Jr.: Bioelectrical impedance analysis: population reference values for phase angle by age and sex . The American journal of clinical nutrition 2005, 82 (1):49-52. Tables Table 1 Characteristics of study population Features Men(n = 122) Non-sarcopenia group(n = 66) Possible sarcopenia group(n = 56) P value Basic information Age (years), mean ± SD 53.12 ± 13.84 46.00 ± 11.00 61.00 ± 12.00 0.224 ** Dialysis duration (Months), median (IQR) 48.00(19.50,84.00) 52(36,60) 48(36,72) -0.409 HTN, n (%) No 15(12.30%) 9(60.00%) 6(40.00%) 0.240 Yes 107(87.70) 57(53.30%) 50(46.70%) DM, n (%) No 89(73.00%) 57(64.00%) 32(36.00%) 13.109 ** Yes 33(27.00%) 9(27.30%) 24(72.70%) Body measurement results CC (cm), median (IQR) 33.00(31.00,35.00) 33.00(33.00, 34.00) 33.00(32.00,35.00) -1.184 BMI (kg/m²), mean ± SD 23.52 ± 3.01 23.40 ± 2.90 23.60 ± 3.10 0.502 Pha (°), mean ± SD 6.42 ± 1.22 6.98 ± 1.02 5.76 ± 1.12 0.200 ** SMI (kg/m²), median (IQR) 8.20(7.80,8.80) 8.30(8.10,8.70) 8.10(8.10,8.50) -1.685 HGS (kg), mean ± SD 31.42 ± 7.73 36.20 ± 5.70 25.80 ± 5.80 0.050 ** SPPB (scores), median (IQR) 10.00(8.00,12.00) 12.00(12.00,12.00) 8.00(8.00,8.00) -8.996 ** * P values less than 0.05 ** P values less than 0.001 Abbreviations: CC, Calf circumference; BMI, body mass index; Pha, phase angle; SMI, Skeletal muscle index; HGS, Handgrip strength; SPPB, Short Physical Performance Battery; SD, standard deviation; HTN, Hypertension; DM, Diabetes mellitus; IQR, interquartile range. Table 2 Characteristics of study population Features Women(n = 98) Non-sarcopenia group(n = 43) Possible sarcopenia group(n = 55) P value Basic information Age (years), mean ± SD 52.37 ± 13.06 44.00 ± 9.00 59.00 ± 12.00 1.963 ** Dialysis duration (Months), median (IQR) 58.50(24.00,84.50) 60.00(45.00,77.00) 57.00(40.00,72.00) -0.057 HTN, n (%) No 16(16.3%) 9(56.3%) 7(43.8%) 1.189 Yes 82(83.7%) 34(41.5%) 48(58.5%) DM, n (%) No 82(83.7%) 39(47.6%) 43(52.4%) 2.767 Yes 16(16.3%) 4(25.0%) 12(75.0%) Body measurement results CC (cm), median (IQR) 31.00(29.00,33.00) 32.00(32.00,33.00) 31.00(31.00,33.00) -0.252 BMI (kg/m²), mean ± SD 22.24 ± 2.95 21.70 ± 3.00 22.60 ± 2.80 0.038 Pha (°), mean ± SD 5.77 ± 1.08 6.17 ± 0.94 5.47 ± 1.09 1.188 * SMI (kg/m²), median (IQR) 6.60(6.30,7.12) 6.80(6.60,7.20) 6.50(6.40,6.80) -1.914 HGS (kg), mean ± SD 19.65 ± 5.85 23.60 ± 3.80 16.50 ± 5.30 4.106 ** SPPB (scores), median (IQR) 9.50(7.00,12.00) 12.00(12.00,12.00) 7.00(7.00,8.00) -7.885 ** * P values less than 0.05 ** P values less than 0.001 Abbreviations: CC, Calf circumference; BMI, body mass index; Pha, phase angle; SMI, Skeletal muscle index; HGS, Handgrip strength; SPPB, Short Physical Performance Battery; SD, standard deviation; HTN, Hypertension; DM, Diabetes mellitus; IQR, interquartile range. Table 3 Binary Logistic regression analysis of possible sarcopenia in men MHD patients. Variables B SE Wald χ² P value OR OR (95% CI) Lower Upper constant −0.287 3.645 0.006 0.937 0.751 - - Age (years) 0.093 0.025 13.986 <0.001 1.097 1.045 1.152 BMI (kg/m²) 0.264 0.125 4.471 0.034 1.302 1.020 1.664 Pha (°) −1.098 0.330 11.043 0.001 0.334 0.175 0.637 Note: The variables entered in step 1: age, Dialysis duration, diabetes, hypertension, CC, BMI, Pha. Abbreviations: CC, Calf circumference; BMI, body mass index; Pha, phase angle. Table 4 Binary Logistic regression analysis of possible sarcopenia in women MHD patients. Variables B SE Wald χ² P value OR OR (95% CI) Lower Upper constant −5.820 3.356 3.008 0.083 0.003 - - Age (years) 0.120 0.030 15.819 <0.001 1.127 1.063 1.196 Pha (°) −0.653 0.328 3.953 0.047 0.521 0.274 0.991 Note: The variables entered in step 1: age, Dialysis duration, diabetes, hypertension, CC, BMI, Pha. Abbreviations: CC, Calf circumference; BMI, body mass index; Pha, phase angle. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 16 Oct, 2024 Read the published version in BMC Nephrology → Version 1 posted Editorial decision: Revision requested 29 Jul, 2024 Reviews received at journal 27 Jul, 2024 Reviewers agreed at journal 22 Jul, 2024 Reviews received at journal 24 Jun, 2024 Reviewers agreed at journal 17 Jun, 2024 Reviewers invited by journal 21 Mar, 2024 Editor assigned by journal 21 Mar, 2024 Editor invited by journal 18 Mar, 2024 Submission checks completed at journal 18 Mar, 2024 First submitted to journal 10 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4064617","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":281273422,"identity":"6a66e644-7771-4b95-b5b0-90d4c4ab5c79","order_by":0,"name":"Ying Zeng","email":"","orcid":"","institution":"Department of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Zeng","suffix":""},{"id":281273423,"identity":"6f3cdcfe-6812-47f4-bf52-5631f3623cd4","order_by":1,"name":"Yang 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11:46:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4064617/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4064617/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12882-024-03787-5","type":"published","date":"2024-10-16T15:57:50+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53195178,"identity":"56451929-d12b-4f6c-b3e7-3354b1a1d9fd","added_by":"auto","created_at":"2024-03-21 18:18:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":15096,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between phase angle (Pha) and handgrip strength (HGS).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4064617/v1/f010ce4ba9223684b0910f8d.png"},{"id":53195659,"identity":"ab629269-b01d-4c04-a454-64bb16875a06","added_by":"auto","created_at":"2024-03-21 18:26:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":14001,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between phase angle (Pha) and short physical performance battery (SPPB).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4064617/v1/21590065c62cc38412f11fe3.png"},{"id":53195177,"identity":"a02f45c0-aa70-4630-8faf-af654b9781ad","added_by":"auto","created_at":"2024-03-21 18:18:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":14139,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between phase angle (Pha) and skeletal muscle index (SMI).\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4064617/v1/3007e38a0acd8a05c44c9fe2.png"},{"id":53195179,"identity":"620bfc64-ecf9-475c-8633-696c191f30a0","added_by":"auto","created_at":"2024-03-21 18:18:18","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":14226,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between phase angle (Pha) and handgrip strength (HGS).\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4064617/v1/1b979be855b38f7056c9a62c.png"},{"id":53195181,"identity":"a2030391-2c97-43d5-9ec9-c12bf2f882e5","added_by":"auto","created_at":"2024-03-21 18:18:18","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":13842,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between phase angle (Pha) and short physical performance battery (SPPB).\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4064617/v1/c175b03625124be59107bc41.png"},{"id":53195182,"identity":"e186f563-894c-4559-9056-cc4b314e6ba6","added_by":"auto","created_at":"2024-03-21 18:18:18","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":14038,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between phase angle (Pha) and skeletal muscle index (SMI).\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-4064617/v1/0084fffd74125570812705db.png"},{"id":53195183,"identity":"236addea-c51c-43d4-ae82-ab2ce8445d06","added_by":"auto","created_at":"2024-03-21 18:18:18","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":13677,"visible":true,"origin":"","legend":"\u003cp\u003eThe area under the ROC curve of Pha detection for the screening of possible sarcopenia in man MHD patients.\u003c/p\u003e\n\u003cp\u003eAUC, area under the curve; ROC, receiver operating characteristic.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-4064617/v1/aefa52d3c1402c27c0eaaf07.png"},{"id":53195184,"identity":"1600afa6-7e41-49b6-b644-cc259e983240","added_by":"auto","created_at":"2024-03-21 18:18:18","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":14476,"visible":true,"origin":"","legend":"\u003cp\u003eThe area under the ROC curve of Pha detection for the screening of possible sarcopenia in women MHD patients.\u003c/p\u003e\n\u003cp\u003eAUC, area under the curve; ROC, receiver operating characteristic.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-4064617/v1/ee17dc10751230bd9f8cb29e.png"},{"id":67149048,"identity":"28993fa7-5e36-4dd0-ab6a-e1006dde4750","added_by":"auto","created_at":"2024-10-21 16:11:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2144340,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4064617/v1/13cb069b-d7bf-480c-9c80-654b6a5a9e7f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Bioelectrical impedance analysis–derived phase angle predicts possible sarcopenia in patients on maintenance hemodialysis: A retrospective study","fulltext":[{"header":"Background","content":"\u003cp\u003eChronic kidney disease (CKD) has become an important public health problem that jeopardizes human health globally due to its high prevalence, high disability rate, high medical expenses and low awareness rate - \"three highs and one low\". There are about 132.3\u0026nbsp;million CKD patients in China as of 2017\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e.Once CKD patients enter end-stage kidney disease (ESKD), renal replacement therapy (including hemodialysis, peritoneal dialysis, or renal transplantation) is required to maintain life, which seriously affects the quality of life of patients\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. According to a survey, maintenance hemodialysis (MHD) is still the main and most commonly used treatment for ESKD, and about 89.4% of patients in China choose MHD\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eMHD patients, compared with the general population, commonly have reduced body protein and energy reserves due to nutrient loss and inadequate intake during dialysis\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. In addition, decreased glomerular filtration rate or progression of proteinuria, as well as dialysis treatments, accelerate muscle protein catabolism and down-regulation of mitochondrial function, leading to decreased skeletal muscle strength and reduced skeletal muscle mass in patients with MHD, making MHD patients increasingly susceptible to sarcopenia\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Sarcopenia is a progressive generalized loss of muscle mass and/or loss of muscle strength or physical activity function with age\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. According to a survey, the average prevalence of skeletal sarcopenia in patients with MHD is 28.5%\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Sarcopenia has been shown to be strongly associated with a variety of adverse outcomes such as falls, debilitation, fractures, and malnutrition\u003csup\u003e[\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e, and carries a risk of prolonged hospitalization and increased mortality\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003ePrevious diagnoses of sarcopenia were mainly characterized by reduced muscle mass, but not by reduced muscle function and muscle strength\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. However, it has been shown that slow gait speed and weaker muscle strength, even after adjusting for muscle content and other confounders, are associated with mortality, suggesting that muscle function and strength may be more relevant predictors of survival than muscle mass\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. In a prospective study of 142 hemodialysis patients, Kim KV\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e et al. found that skeletal sarcopenia was strongly associated with long-term mortality and cardiovascular events in hemodialysis patients, and that the assessment of muscle strength and muscle mass could provide additional prognostic information for survival in patients with end-stage renal disease. A new definition of skeletal sarcopenia was released by European Working Group on Sarcopenia in Older People (EWGSOP) in 2019, which adds muscle function to the previous definition based solely on low muscle mass testing\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. It has been shown that muscle strength is superior to muscle mass in predicting poor outcomes\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Moreover, the 2019 AWGS introduced \"possible sarcopenia\", which refers to a decline in muscle strength and/or somatic function, and advocates early identification and intervention\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Therefore, early screening, diagnosis, and treatment of possible sarcopenia is important to slow down the rate of muscle decay and improve the quality of life of the population.\u003c/p\u003e\u003cp\u003eCurrently, bioelectrical impedance analysis (BIA) and dualenergy X-ray absorptiometry (DXA) measurements are the recommended modalities under the criteria for the diagnosis of sarcopenia. However, BIA measurements are avoided in patients with pacemakers, and DXA is expensive and requires some installation space, so both instruments cannot always be used in patients with MHD. Therefore, alternative strategies using tools available in clinical practice are necessary, and we need to establish a simple diagnostic index for diagnosing sarcopenia in patients with MHD. In this study, we screened for sarcopenia in MHD patients according to the AWGS2019 diagnostic criteria, and we hope to identify an auxiliary screening indicator for the identification of sarcopenia in MHD patients, which will facilitate the early identification of those at risk for sarcopenia by healthcare professionals.\u003c/p\u003e\u003cp\u003eThe latest consensus of the 2019 EWGSOP on the diagnosis of sarcopenia that Pha can be used to assess muscle mass\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. Pha is an index obtained by measuring the electrical resistance and reactance of the human body and calculating the ratio of the inverse tangent of the two by bioelectrical impedance analysis (BIA), which reflects the water content inside and outside the cell and the integrity of the cell membrane\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. Pha values in healthy individuals range from 6.4\u0026deg; to 8.2\u0026deg;\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. There have been many researchers who have used Pha to predict sarcopenia\u003csup\u003e[\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. However, no studies have been conducted for possible sarcopenia. Moreover, sarcopenia is affected by many factors. In the past, the prediction of sarcopenia usually used gender as an influencing factor rather than a grouping index, which homogenized the prediction of sarcopenia, and it has been shown that gender-differentiated aging patterns involve changes in muscle mass and muscle strength\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Therefore, the present study focuses on gender differences to discuss the screening ability of Pha in possible sarcopenia, to further help clinicians to accurately screen for possible sarcopenia early and provide personalized preventive and therapeutic measures for patients with possible sarcopenia early, thereby slowing down the further progression of possible sarcopenia.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003e\u003cb\u003eStudy design and participants\u003c/b\u003e\u003c/p\u003e\u003cp\u003eUse of convenience sampling. Data were retrospectively collected from outpatient under going MHD at Wenjiang Hemodialysis Center in the Department of Nephrology in West China Hospital, Sichuan University, Chengdu, China. The inclusion criteria were (1) age\u0026thinsp;\u0026ge;\u0026thinsp;18 years, (2) receiving maintenance hemodialysis for at least 3 months, (3) thinking and language expression ability is normal, and (4) volunteer to participate in this study and sign the informed consent form. The exclusion criteria were as follows: (1) cognitive impairment or mental illness, (2) patients with major disease changes in the last three months, (3) pregnant or lactating, (4) body mutilation, Immobility or other reasons can not cooperate, and (5) the InBodyS10 body composition analysis measurement cannot be performed, such as cardiovascular stent implantation, pacemaker installation, artificial joint replacement, etc. A total of 244 MHD patients were collected in this study, and after excluding patients with sarcopenia, data from 122 men (56 with possible sarcopenia) and 96 women (55 with possible sarcopenia) patients were included in this study.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData collection\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePrior to the study, two researchers were uniformly trained to assess questionnaires and measure anthropometric indicators. A face-to‐face interview was performed to verify demographics (sex, age) and characteristics (presence of diabetes mellitus and hypertension, and dialysis vintage). Using a wall‐secured stadiometer, a digital scale, and a retractable measuring tape, height, weight,and calf circumference (CC) were taken.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePha and body composition\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAfter dialysis, body composition was measured by multifrequency Bia (InBodyS10; InBody Co., Ltd Korea). All parameters, including Pha, SMI, and BMI, were directly measured and recorded by the devices. However, the SMI was used to evaluate the muscle mass in patients with MHD. The phase angle is estimated based on the ratio of reactance (Xc) to resistance (R) and the formula is below: Pha (\u0026deg;)\u0026thinsp;=\u0026thinsp;arctangent (Xc / R) \u0026times; (180\u0026deg; / π)\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMuscle strength\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMuscle strength was assessed in MHD patients using HGS. Before dialysis, the researchers measured the patient's HGS with an electronic grip strength fitness tester (Zhongshan Camry Electronics Co., LTD.), asked the patient to measure with the non-fistula hand, and kept the standing position, the arms were naturally drooping, measured twice for 5s interval, and the maximum value was recorded.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePhysical performance measurements\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSPPB is recommended for evaluating physical performance in MHD patients\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. The SPPB consists of 3 components: repeated chair stand, gait speed, and balance tests. Each component is scored on a scale of 0\u0026ndash;4 points and the total score is 0\u0026ndash;12 points. Patients with a score of \u0026le;\u0026thinsp;9 were identified as having low physical performance\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSarcopenia diagnosis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe diagnosis was made using the diagnostic consensus for sarcopenia developed by the 2019 AWGS\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e。The diagnosis are as follows: ① SMI: \u0026lt;7.0 kg/㎡in men and \u0026lt;5.7 kg/㎡ in women. ② HGS: \u0026lt;28.0 kg for men and \u0026lt;\u0026thinsp;18.0 kg for women. ③ SPPB: Total score\u0026thinsp;\u0026le;\u0026thinsp;9 points. Patients who meet the diagnostic criteria ① and ② and (or) ③ can be diagnosed with sarcopenia. Patients who meet the diagnostic criteria ② and (or) ③ can be diagnosed with possible sarcopenia. The present study analyzed possible sarcopenia as experimental group and non-sarcopenia as control group.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStatistical analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eStatistical analysis was performed in SPSS, version 27.0 (SPSS Inc., Chicago, IL, USA). After the normality test. Measurement data consistent with the normal distribution were expressed by means and standard deviation (SD). Measometric data with non-normal distribution were expressed using median and interquartile range (IQR). Statistical methods were performed using the independent sample t-test and the Kruskal-Wallis H test. The categorical variables were presented as numbers and percentages. Categorical data were tested by the chi-square test or the Fisher exact probability method. Using binary logistic regression model (enter method) was used to analyze the factors affecting possible sarcopenia in men and women MHD patients, calculating the odds ratio (OR) and its 95% confidence interval (CI). The correlation between Pha and possible sarcopenic components was analyzed by Spearman. The ROC curve was used to evaluate the ability of Pha to screen for possible sarcopenia, and the AUC, sensitivity and specificity were significantly different, yielding the best cutoff value. Spearman Windows version GraphPad Prism (version 10.1.0, GraphPad Software, San Diego, California USA,\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.graphpad.com\" target=\"_blank\"\u003ewww.graphpad.com\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.graphpad.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The receiver operating characteristic (ROC) curve was plotted using MedCalc19.0. the significance value adopted was \u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eGeneral clinical characteristics of the patients\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e The mean age of men MHD patients was (53.12\u0026thinsp;\u0026plusmn;\u0026thinsp;13.84) years, the median age on dialysis was 48.0 (19.5, 84.0) months, the median CC was 33 (31, 35) cm, the mean BMI was (22.52\u0026thinsp;\u0026plusmn;\u0026thinsp;3.01) kg/㎡, and the mean Pha was (6.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22)\u0026deg;, and 107 (87.7%) of the patients had hypertension, 33 (27.0%) patients had diabetes.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e The mean age of women MHD patients was (52.37\u0026thinsp;\u0026plusmn;\u0026thinsp;13.06) years, the median age on dialysis was 58.5 (24.0, 84.5) months, the median CC was 31 (29, 33) cm, the mean BMI was (22.24\u0026thinsp;\u0026plusmn;\u0026thinsp;2.95) kg/㎡, the mean Pha was (5.77\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08)\u0026deg;, and 82 (83.7%) of the patients had hypertension, 16 (16.3%) patients had diabetes.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults of the univariate analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe two groups of men MHD patients were comparable in terms of age, diabetes and Pha. And the patients in the possible sarcopenia group had a greater mean age, more comorbid diabetes, and lower mean Pha compared to the patients in the non-sarcopenia group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The two groups of women MHD patients were comparable in terms of age, diabetes and Pha. And the patients in the possible sarcopenia group had a greater mean age, and lower mean Pha compared to the patients in the non-sarcopenia group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults of the binary logistic regression analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e Age, BMI, and Pha were influential factors in the development of possible sarcopenia in men MHD patients (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e Age, and Pha were influential factors in the development of possible sarcopenia in women MHD patients (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003cb\u003eCorrelates between Pha and possible sarcopenia\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSpearman correlation analysis showed Pha and possible sarcopenia (men: \u003cem\u003er\u003c/em\u003e =\u0026minus;0.501, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; women: \u003cem\u003er\u003c/em\u003e=\u0026minus;0.356, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and HGS (men: \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.590, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; women: \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.374, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and SPPB (men: \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.485, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; women: \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.360, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and SMI (men: \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.338, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; women: \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.290, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004), all showed significant associations (Fig.\u0026nbsp;1\u0026ndash;6).\u003c/p\u003e\u003cp\u003e\u003cb\u003eScreening ability analysis of Pha in the possible sarcopenia screen\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe AUC of Pha in screening men for possible sarcopenia was 0.790, with a sensitivity of 78.57%, a specificity of 74.24%, and an optimal cutoff value of 6.52\u0026deg; (Fig.\u0026nbsp;7). The AUC of Pha in screening women for possible sarcopenia was 0.707, with a sensitivity of 58.18%, a specificity of 76.74%, and an optimal cutoff value of 5.6\u0026deg; (Fig.\u0026nbsp;8).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eSarcopenia was estimated to influence 10%-16% of the elderly worldwide. The prevalence of sarcopenia ranged from 18% in diabetic patients to 66% in patients with unresectable esophageal cancer\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Patients with MHD have a significantly increased incidence of sarcopenia compared to healthy subjects. Souza\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e et al. found that among non-dialysis patients with CKD in South America (mean age 74 years), the prevalence of sarcopenia was 34.5% in patients with CKD stages 2 and 3A, whereas the prevalence was as high as 65.5% in patients with CKD stages 3B, 4 and 5. Yoowannakul\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e et al. found that the prevalence of sarcopenia in Asian hemodialysis patients (mean age 68 years) was 59.6%. Sarcopenia has been shown to be a common complication in patients with MHD and is associated with falls, fractures, malnutrition, and adverse cardiovascular events, posing a serious threat to patient safety\u003csup\u003e[\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. In order to prevent the development of sarcopenia, the risk of developing sarcopenia should be screened in advance. Therefore, it is particularly important to screen patients in advance for the presence of decreased muscle strength and muscle function (i.e., possible sarcopenia). A simple and feasible Pha for the prediction of possible sarcopenia in MHD patients was used in this study to investigate the relationship between Pha and possible sarcopenia and the predictive value of Pha in possible sarcopenia, with a focus on gender specificity. The results show that Pha plays an independent role in predicting and identifying possible sarcopenia in MHD patients of both sexes.\u003c/p\u003e\u003cp\u003ePha is often used in the assessment of nutritional status\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e, it is considered to be a proxy for water distribution and somatic cell mass, and it also correlates with muscle strength and is a valid predictor of different clinical outcomes. Pha aids in the diagnosis of skeletal sarcopenia more easily and quickly than the 2019 AWGS diagnostic criteria. Many studies have shown the importance of Pha for the diagnosis of sarcopenia in patients with MHD\u003csup\u003e[\u003cspan additionalcitationids=\"CR32 CR33 CR34\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. Yamada\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e et al. divided 1,009 community-dwelling older adults into four groups (normal, presarcopenia, dynapenia, and sarcopenia), and the results of their study showed that there were significant differences in phase angles among the four groups of older adults. Kilic\u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e et al. assessed 263 community-dwelling and hospitalized older adults by BIA and anthropometry, and showed that phase angle was an independently relevant variable for screening for sarcopenia, and that smaller phase angles increased the risk of developing sarcopenia. Since 2010, the diagnostic criteria for skeletal sarcopenia are not only muscle mass, but also measures of muscle function and muscle strength\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e. Sarcopenia is categorized into stages of non-sarcopenia, possible sarcopenia, sarcopenia and severe sarcopenia according to the AWGS diagnostic consensus\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Different stages of sarcopenia have different symptoms and clinical manifestations, and preventive and therapeutic measures may vary. Therefore, early diagnosis and intervention of possible sarcopenia is particularly important.\u003c/p\u003e\u003cp\u003eIn this study, we examined the relationship between Pha and possible sarcopenia in men and women MHD patients. Our study found that Pha plays an independent role in predicting and identifying possible sarcopenia in patients treated for MHD. A number of studies have also confirmed the ability of Pha to better predict sarcopenia\u003csup\u003e[\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. In this study, we also found that age and Pha were influential factors for possible sarcopenia in both men and women MHD patients and Pha was significantly negatively correlated with possible sarcopenia and significantly positively correlated with HGS, SPPB, and SMI. Pha was directly correlated with muscular strength and declined with age\u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e.Uemura\u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/sup\u003e et al. found a significant relationship between Pha and SMI and HGS in both men and women was positively correlated, which is similar to our findings, as muscle mass and muscle strength declines in low Pha populations, which further leads to a decline in physical functional performance\u003csup\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/sup\u003e. Although patients with possible sarcopenia have not yet developed sarcopenia, decreased muscle strength and muscle function can also affect the quality of life of patients. Therefore, healthcare professionals should increase their attention to patients with possible sarcopenia.\u003c/p\u003e\u003cp\u003eThe optimal cutoff value of Pha in this study was 6.52\u0026deg; in screening for possible sarcopenia in men and 5.60\u0026deg; in screening for possible sarcopenia in women, which is higher than that reported by Yamada\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e and others. The optimal cutoff value for Pha varied across studies, and differences in the optimal cutoff value for Pha were related to the choice of diagnostic criteria, racial differences, and the selection of the subject population. However, the reason for the wide variation in the cutoff value for predicting sarcopenia is that Pha varies by age and sex\u003csup\u003e[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/sup\u003e, and it is therefore of interest to differentiate between men and women MHD patients in the onset and diagnosis of possible sarcopenia.\u003c/p\u003e\u003cp\u003eThe sensitivity and specificity of the Pha values obtained in this study for the diagnosis of sarcopenia were not particularly high, which may be related to the fact that this study was a single-center cross-sectional study with a limited sample size, which may have unavoidable selection bias, and although the results showed that Pha was significantly associated with possible sarcopenia and its components, they could not explain the causal relationship. Second, we screened patients who were able to complete BIA testing and muscle function tests, and perhaps the number of actual MHD patients with possible sarcopenia was higher. Although Pha has the ability to screen for possible sarcopenia, it is not as diagnostically accurate as CT, MRI, and DXA, so the accuracy of the study results is somewhat compromised. More prospective studies are needed to further promote the use of Pha in the diagnosis of possible sarcopenia.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, there have been a number of papers that have used different approaches to explore the relationship between Pha and sarcopenia, but there are no relevant studies that have explored the ability of Pha to screen for possible sarcopenia in patients with MHD, using gender as a specific indicator. The results of this study suggest that Pha is a useful and simple predictor of the risk of possible sarcopenia in patients with MHD. Pha\u0026thinsp;\u0026le;\u0026thinsp;6.52\u0026deg; can be used as a predictive threshold for the combination of possible sarcopenia in men MHD patients, and Pha\u0026thinsp;\u0026le;\u0026thinsp;5.60\u0026deg; can be used as a predictive threshold for the combination of possible sarcopenia in women MHD patients. It provides a theoretical reference for early screening, diagnosis and treatment of possible sarcopenia in MHD patients of different genders, slows down muscle decay, improves the quality of life of the population, and provides individualized preventive and therapeutic measures. More research is needed to further promote the application of Pha in possible sarcopenia.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAUC The area under the receiver operating characteristic curves\u003c/p\u003e\u003cp\u003eAWGS Asia Working Group for Sarcopenia\u003c/p\u003e\u003cp\u003eBIA Bioelectrical impedance analysis\u003c/p\u003e\u003cp\u003eBMI Body mass index\u003c/p\u003e\u003cp\u003eCC Calf circumference\u003c/p\u003e\u003cp\u003eCI Confidence interval\u003c/p\u003e\u003cp\u003eCKD Chronic kidney disease\u003c/p\u003e\u003cp\u003eDM Diabetes mellitus\u003c/p\u003e\u003cp\u003eDXA Dualenergy X-ray absorptiometry\u003c/p\u003e\u003cp\u003eESKD End-stage renal disease\u003c/p\u003e\u003cp\u003eEWGSOP European Working Group on Sarcopenia in Older People\u003c/p\u003e\u003cp\u003eHGS Handgrip strength\u003c/p\u003e\u003cp\u003eHTN Hypertension\u003c/p\u003e\u003cp\u003eIQR Interquartile range\u003c/p\u003e\u003cp\u003eMHD Maintenance hemodialysis\u003c/p\u003e\u003cp\u003eOR Odds ratio\u003c/p\u003e\u003cp\u003ePha Phase angle\u003c/p\u003e\u003cp\u003eROC Receiver operating characteristic\u003c/p\u003e\u003cp\u003eSD Standard deviation\u003c/p\u003e\u003cp\u003eSMI Skeletal muscle index\u003c/p\u003e\u003cp\u003eSPPB Short physical performance battery\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank all of the healthcare providers and patients who participated in this study from Wenjiang Hemodialysis Center in the Department of Nephrology at West China Hospital, Sichuan University, Chengdu, China.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY.Z. and Y.C. participated in the conception and design of the study and drafted the manuscript. Y.Z. and Y.C. analyzed the data. H.H.Y. organized and coordinated the research efforts. Y.J.Y. participated in the design of the study. Y.Q. participated in the acquisition of the data. Y.Z. and Y.C. were the major contributors in writing the manuscript. All authors reviewed the manuscript. The final manuscript was read and approved by all authors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData available on request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the biomedical ethics committee of the West China University of Sichuan University (ethical approval number: 2020[1002]) and was performed in accordance with the principles of the Declaration of Helsinki. All patients provided a written informed consent. In the case of illiterate patients, the consent was read to them in the presence of a literate relative and they provided a fingerprint on the consent form to indicate their informed consent to participate. This form of informed consent was also approved by the biomedical ethics committee of the West China University of Sichuan University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCollaboration GCKD: \u003cstrong\u003eGlobal, regional, and national burden of chronic kidney disease, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017\u003c/strong\u003e. \u003cem\u003eLancet (London, England) \u003c/em\u003e2020, \u003cstrong\u003e395\u003c/strong\u003e(10225):709-733.\u003c/li\u003e\n\u003cli\u003eLv JC, Zhang LX: \u003cstrong\u003ePrevalence and Disease Burden of Chronic Kidney Disease\u003c/strong\u003e. \u003cem\u003eAdvances in experimental medicine and biology \u003c/em\u003e2019, \u003cstrong\u003e1165\u003c/strong\u003e:3-15.\u003c/li\u003e\n\u003cli\u003eManganaro M, Baldovino S: \u003cstrong\u003eFirst considerations on the SARS-CoV-2 epidemic in the Dialysis Units of Piedmont and Aosta Valley, Northern Italy\u003c/strong\u003e. \u003cem\u003eJournal of nephrology \u003c/em\u003e2020, \u003cstrong\u003e33\u003c/strong\u003e(3):393-395.\u003c/li\u003e\n\u003cli\u003ePauzi FA, Sahathevan S, Khor BH, Narayanan SS, Zakaria NF, Abas F, Karupaiah T, Daud ZAM: \u003cstrong\u003eExploring Metabolic Signature of Protein Energy Wasting in Hemodialysis Patients\u003c/strong\u003e. \u003cem\u003eMetabolites \u003c/em\u003e2020, \u003cstrong\u003e10\u003c/strong\u003e(7).\u003c/li\u003e\n\u003cli\u003eHanna RM, Ghobry L, Wassef O, Rhee CM, Kalantar-Zadeh K: \u003cstrong\u003eA Practical Approach to Nutrition, Protein-Energy Wasting, Sarcopenia, and Cachexia in Patients with Chronic Kidney Disease\u003c/strong\u003e. \u003cem\u003eBlood purification \u003c/em\u003e2020, \u003cstrong\u003e49\u003c/strong\u003e(1-2):202-211.\u003c/li\u003e\n\u003cli\u003eNishi H, Takemura K, Higashihara T, Inagi R: \u003cstrong\u003eUremic Sarcopenia: Clinical Evidence and Basic Experimental Approach\u003c/strong\u003e. \u003cem\u003eNutrients \u003c/em\u003e2020, \u003cstrong\u003e12\u003c/strong\u003e(6).\u003c/li\u003e\n\u003cli\u003eChen LK, Liu LK, Woo J, Assantachai P, Auyeung TW, Bahyah KS, Chou MY, Chen LY, Hsu PS, Krairit O\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eSarcopenia in Asia: consensus report of the Asian Working Group for Sarcopenia\u003c/strong\u003e. \u003cem\u003eJournal of the American Medical Directors Association \u003c/em\u003e2014, \u003cstrong\u003e15\u003c/strong\u003e(2):95-101.\u003c/li\u003e\n\u003cli\u003eShu X, Lin T, Wang H, Zhao Y, Jiang T, Peng X, Yue J: \u003cstrong\u003eDiagnosis, prevalence, and mortality of sarcopenia in dialysis patients: a systematic review and meta-analysis\u003c/strong\u003e. \u003cem\u003eJournal of cachexia, sarcopenia and muscle \u003c/em\u003e2022, \u003cstrong\u003e13\u003c/strong\u003e(1):145-158.\u003c/li\u003e\n\u003cli\u003eP\u0026eacute;rez-Zepeda MU, Sgaravatti A, Dent E: \u003cstrong\u003eSarcopenia and post-hospital outcomes in older adults: A longitudinal study\u003c/strong\u003e. \u003cem\u003eArchives of gerontology and geriatrics \u003c/em\u003e2017, \u003cstrong\u003e69\u003c/strong\u003e:105-109.\u003c/li\u003e\n\u003cli\u003eBillot M, Calvani R, Urtamo A, S\u0026aacute;nchez-S\u0026aacute;nchez JL, Ciccolari-Micaldi C, Chang M, Roller-Wirnsberger R, Wirnsberger G, Sinclair A, Vaquero-Pinto N\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003ePreserving Mobility in Older Adults with Physical Frailty and Sarcopenia: Opportunities, Challenges, and Recommendations for Physical Activity Interventions\u003c/strong\u003e. \u003cem\u003eClinical interventions in aging \u003c/em\u003e2020, \u003cstrong\u003e15\u003c/strong\u003e:1675-1690.\u003c/li\u003e\n\u003cli\u003eSim M, Prince RL, Scott D, Daly RM, Duque G, Inderjeeth CA, Zhu K, Woodman RJ, Hodgson JM, Lewis JR: \u003cstrong\u003eSarcopenia Definitions and Their Associations With Mortality in Older Australian Women\u003c/strong\u003e. \u003cem\u003eJournal of the American Medical Directors Association \u003c/em\u003e2019, \u003cstrong\u003e20\u003c/strong\u003e(1):76-82.e72.\u003c/li\u003e\n\u003cli\u003eRossi AP, Bianchi L, Volpato S, Bandinelli S, Guralnik J, Zamboni M, Ferrucci L: \u003cstrong\u003eDynapenic Abdominal Obesity as a Predictor of Worsening Disability, Hospitalization, and Mortality in Older Adults: Results From the InCHIANTI Study\u003c/strong\u003e. \u003cem\u003eThe journals of gerontology Series A, Biological sciences and medical sciences \u003c/em\u003e2017, \u003cstrong\u003e72\u003c/strong\u003e(8):1098-1104.\u003c/li\u003e\n\u003cli\u003eCruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, Martin FC, Michel JP, Rolland Y, Schneider SM\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eSarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People\u003c/strong\u003e. \u003cem\u003eAge and ageing \u003c/em\u003e2010, \u003cstrong\u003e39\u003c/strong\u003e(4):412-423.\u003c/li\u003e\n\u003cli\u003eKittiskulnam P, Chertow GM, Carrero JJ, Delgado C, Kaysen GA, Johansen KL: \u003cstrong\u003eSarcopenia and its individual criteria are associated, in part, with mortality among patients on hemodialysis\u003c/strong\u003e. \u003cem\u003eKidney international \u003c/em\u003e2017, \u003cstrong\u003e92\u003c/strong\u003e(1):238-247.\u003c/li\u003e\n\u003cli\u003eKim JK, Kim SG, Oh JE, Lee YK, Noh JW, Kim HJ, Song YR: \u003cstrong\u003eImpact of sarcopenia on long-term mortality and cardiovascular events in patients undergoing hemodialysis\u003c/strong\u003e. \u003cem\u003eThe Korean journal of internal medicine \u003c/em\u003e2019, \u003cstrong\u003e34\u003c/strong\u003e(3):599-607.\u003c/li\u003e\n\u003cli\u003eCruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruy\u0026egrave;re O, Cederholm T, Cooper C, Landi F, Rolland Y, Sayer AA\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eSarcopenia: revised European consensus on definition and diagnosis\u003c/strong\u003e. \u003cem\u003eAge and ageing \u003c/em\u003e2019, \u003cstrong\u003e48\u003c/strong\u003e(1):16-31.\u003c/li\u003e\n\u003cli\u003eSchaap LA, van Schoor NM, Lips P, Visser M: \u003cstrong\u003eAssociations of Sarcopenia Definitions, and Their Components, With the Incidence of Recurrent Falling and Fractures: The Longitudinal Aging Study Amsterdam\u003c/strong\u003e. \u003cem\u003eThe journals of gerontology Series A, Biological sciences and medical sciences \u003c/em\u003e2018, \u003cstrong\u003e73\u003c/strong\u003e(9):1199-1204.\u003c/li\u003e\n\u003cli\u003eChen LK, Woo J, Assantachai P, Auyeung TW, Chou MY, Iijima K, Jang HC, Kang L, Kim M, Kim S\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eAsian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment\u003c/strong\u003e. \u003cem\u003eJournal of the American Medical Directors Association \u003c/em\u003e2020, \u003cstrong\u003e21\u003c/strong\u003e(3):300-307.e302.\u003c/li\u003e\n\u003cli\u003eAkamatsu Y, Kusakabe T, Arai H, Yamamoto Y, Nakao K, Ikeue K, Ishihara Y, Tagami T, Yasoda A, Ishii K\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003ePhase angle from bioelectrical impedance analysis is a useful indicator of muscle quality\u003c/strong\u003e. \u003cem\u003eJournal of cachexia, sarcopenia and muscle \u003c/em\u003e2022, \u003cstrong\u003e13\u003c/strong\u003e(1):180-189.\u003c/li\u003e\n\u003cli\u003eSelberg O, Selberg D: \u003cstrong\u003eNorms and correlates of bioimpedance phase angle in healthy human subjects, hospitalized patients, and patients with liver cirrhosis\u003c/strong\u003e. \u003cem\u003eEuropean journal of applied physiology \u003c/em\u003e2002, \u003cstrong\u003e86\u003c/strong\u003e(6):509-516.\u003c/li\u003e\n\u003cli\u003eKang SH, Do JY, Kim JC: \u003cstrong\u003eImpedance-derived phase angle is associated with muscle mass, strength, quality of life, and clinical outcomes in maintenance hemodialysis patients\u003c/strong\u003e. \u003cem\u003ePloS one \u003c/em\u003e2022, \u003cstrong\u003e17\u003c/strong\u003e(1):e0261070.\u003c/li\u003e\n\u003cli\u003eChen Y, Wu J, Ran L, Yu D, Chen X, Liu M: \u003cstrong\u003eThe combination of phase angle and age has a good diagnostic value for sarcopenia in continuous ambulatory peritoneal dialysis patients\u003c/strong\u003e. \u003cem\u003eFrontiers in nutrition \u003c/em\u003e2022, \u003cstrong\u003e9\u003c/strong\u003e:1036796.\u003c/li\u003e\n\u003cli\u003eSaitoh M, Ogawa M, Kondo H, Suga K, Takahashi T, Itoh H, Tabata Y: \u003cstrong\u003eBioelectrical impedance analysis-derived phase angle as a determinant of protein-energy wasting and frailty in maintenance hemodialysis patients: retrospective cohort study\u003c/strong\u003e. \u003cem\u003eBMC nephrology \u003c/em\u003e2020, \u003cstrong\u003e21\u003c/strong\u003e(1):438.\u003c/li\u003e\n\u003cli\u003eTseng TG, Lu CK, Hsiao YH, Pan SC, Tai CJ, Lee MC: \u003cstrong\u003eDevelopment of Taiwan Risk Score for Sarcopenia (TRSS) for Sarcopenia Screening among Community-Dwelling Older Adults\u003c/strong\u003e. \u003cem\u003eInternational journal of environmental research and public health \u003c/em\u003e2020, \u003cstrong\u003e17\u003c/strong\u003e(8).\u003c/li\u003e\n\u003cli\u003eWang Y, Hu Y, Zhang M, Jin H, Wen Y, Tang R, Wang B, Liu B, Liu H: \u003cstrong\u003eBioelectrical impedance analysis-derived phase angle predicts sarcopenia in patients on maintenance hemodialysis\u003c/strong\u003e. \u003cem\u003eNutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition \u003c/em\u003e2023, \u003cstrong\u003e38\u003c/strong\u003e(4):881-888.\u003c/li\u003e\n\u003cli\u003eUchida J, Suzuki Y, Imamura K, Yoshikoshi S, Nakajima T, Fukuzaki N, Harada M, Kamiya K, Matsuzawa R, Matsunaga A: \u003cstrong\u003eThe Association of Short Physical Performance Battery With Mortality and Hospitalization in Patients Receiving Hemodialysis\u003c/strong\u003e. \u003cem\u003eJournal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation \u003c/em\u003e2023.\u003c/li\u003e\n\u003cli\u003eYuan S, Larsson SC: \u003cstrong\u003eEpidemiology of sarcopenia: Prevalence, risk factors, and consequences\u003c/strong\u003e. \u003cem\u003eMetabolism: clinical and experimental \u003c/em\u003e2023, \u003cstrong\u003e144\u003c/strong\u003e:155533.\u003c/li\u003e\n\u003cli\u003eSouza VA, Oliveira D, Barbosa SR, Corr\u0026ecirc;a J, Colugnati FAB, Mansur HN, Fernandes N, Bastos MG: \u003cstrong\u003eSarcopenia in patients with chronic kidney disease not yet on dialysis: Analysis of the prevalence and associated factors\u003c/strong\u003e. \u003cem\u003ePloS one \u003c/em\u003e2017, \u003cstrong\u003e12\u003c/strong\u003e(4):e0176230.\u003c/li\u003e\n\u003cli\u003eYoowannakul S, Tangvoraphonkchai K, Vongsanim S, Mohamed A, Davenport A: \u003cstrong\u003eDifferences in the prevalence of sarcopenia in haemodialysis patients: the effects of gender and ethnicity\u003c/strong\u003e. \u003cem\u003eJournal of human nutrition and dietetics : the official journal of the British Dietetic Association \u003c/em\u003e2018, \u003cstrong\u003e31\u003c/strong\u003e(5):689-696.\u003c/li\u003e\n\u003cli\u003eTan RS, Liang DH, Liu Y, Zhong XS, Zhang DS, Ma J: \u003cstrong\u003eBioelectrical Impedance Analysis-Derived Phase Angle Predicts Protein-Energy Wasting in Maintenance Hemodialysis Patients\u003c/strong\u003e. \u003cem\u003eJournal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation \u003c/em\u003e2019, \u003cstrong\u003e29\u003c/strong\u003e(4):295-301.\u003c/li\u003e\n\u003cli\u003ePolegato BF, Herrera MA, Pereira BLB, Silva RAC, Gon\u0026ccedil;alves AF, Cavallari KA, Costa NA, Tanni SE, Azevedo PS, Dorna MS\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003ePhase angle is associated with the length of ICU stay in patients with non-ST elevation acute coronary syndrome\u003c/strong\u003e. \u003cem\u003eNutrire \u003c/em\u003e2017, \u003cstrong\u003e42\u003c/strong\u003e(1):2.\u003c/li\u003e\n\u003cli\u003eDos Reis AS, Santos HO, Limirio LS, de Oliveira EP: \u003cstrong\u003ePhase Angle Is Associated With Handgrip Strength but Not With Sarcopenia in Kidney Transplantation Patients\u003c/strong\u003e. \u003cem\u003eJournal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation \u003c/em\u003e2019, \u003cstrong\u003e29\u003c/strong\u003e(3):196-204.\u003c/li\u003e\n\u003cli\u003eBasile C, Della-Morte D, Cacciatore F, Gargiulo G, Galizia G, Roselli M, Curcio F, Bonaduce D, Abete P: \u003cstrong\u003ePhase angle as bioelectrical marker to identify elderly patients at risk of sarcopenia\u003c/strong\u003e. \u003cem\u003eExperimental gerontology \u003c/em\u003e2014, \u003cstrong\u003e58\u003c/strong\u003e:43-46.\u003c/li\u003e\n\u003cli\u003eReis BCA, de Branco FMS, Pessoa DF, Barbosa CD, dos Reis AS, de Medeiros LA, de Oliveira EP: \u003cstrong\u003ePhase Angle Is Positively Associated With Handgrip Strength in Hospitalized Individuals\u003c/strong\u003e. \u003cem\u003eTopics in Clinical Nutrition \u003c/em\u003e2018, \u003cstrong\u003e33\u003c/strong\u003e(2).\u003c/li\u003e\n\u003cli\u003eMaddocks M, Kon SS, Jones SE, Canavan JL, Nolan CM, Higginson IJ, Gao W, Polkey MI, Man WD: \u003cstrong\u003eBioelectrical impedance phase angle relates to function, disease severity and prognosis in stable chronic obstructive pulmonary disease\u003c/strong\u003e. \u003cem\u003eClinical nutrition (Edinburgh, Scotland) \u003c/em\u003e2015, \u003cstrong\u003e34\u003c/strong\u003e(6):1245-1250.\u003c/li\u003e\n\u003cli\u003eYamada M, Kimura Y, Ishiyama D, Nishio N, Otobe Y, Tanaka T, Ohji S, Koyama S, Sato A, Suzuki M\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003ePhase Angle Is a Useful indicator for Muscle Function in Older Adults\u003c/strong\u003e. \u003cem\u003eThe journal of nutrition, health \u0026amp; aging \u003c/em\u003e2019, \u003cstrong\u003e23\u003c/strong\u003e(3):251-255.\u003c/li\u003e\n\u003cli\u003eKilic MK, Kizilarslanoglu MC, Arik G, Bolayir B, Kara O, Dogan Varan H, Sumer F, Kuyumcu ME, Halil M, Ulger Z: \u003cstrong\u003eAssociation of Bioelectrical Impedance Analysis-Derived Phase Angle and Sarcopenia in Older Adults\u003c/strong\u003e. \u003cem\u003eNutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition \u003c/em\u003e2017, \u003cstrong\u003e32\u003c/strong\u003e(1):103-109.\u003c/li\u003e\n\u003cli\u003eMorley JE, Abbatecola AM, Argiles JM, Baracos V, Bauer J, Bhasin S, Cederholm T, Coats AJ, Cummings SR, Evans WJ\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eSarcopenia with limited mobility: an international consensus\u003c/strong\u003e. \u003cem\u003eJournal of the American Medical Directors Association \u003c/em\u003e2011, \u003cstrong\u003e12\u003c/strong\u003e(6):403-409.\u003c/li\u003e\n\u003cli\u003eMuscaritoli M, Anker SD, Argil\u0026eacute;s J, Aversa Z, Bauer JM, Biolo G, Boirie Y, Bosaeus I, Cederholm T, Costelli P\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eConsensus definition of sarcopenia, cachexia and pre-cachexia: joint document elaborated by Special Interest Groups (SIG) \u0026quot;cachexia-anorexia in chronic wasting diseases\u0026quot; and \u0026quot;nutrition in geriatrics\u0026quot;\u003c/strong\u003e. \u003cem\u003eClinical nutrition (Edinburgh, Scotland) \u003c/em\u003e2010, \u003cstrong\u003e29\u003c/strong\u003e(2):154-159.\u003c/li\u003e\n\u003cli\u003eFielding RA, Vellas B, Evans WJ, Bhasin S, Morley JE, Newman AB, Abellan van Kan G, Andrieu S, Bauer J, Breuille D\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eSarcopenia: an undiagnosed condition in older adults. Current consensus definition: prevalence, etiology, and consequences. International working group on sarcopenia\u003c/strong\u003e. \u003cem\u003eJournal of the American Medical Directors Association \u003c/em\u003e2011, \u003cstrong\u003e12\u003c/strong\u003e(4):249-256.\u003c/li\u003e\n\u003cli\u003ede Blasio F, Santaniello MG, de Blasio F, Mazzarella G, Bianco A, Lionetti L, Franssen FME, Scalfi L: \u003cstrong\u003eRaw BIA variables are predictors of muscle strength in patients with chronic obstructive pulmonary disease\u003c/strong\u003e. \u003cem\u003eEuropean journal of clinical nutrition \u003c/em\u003e2017, \u003cstrong\u003e71\u003c/strong\u003e(11):1336-1340.\u003c/li\u003e\n\u003cli\u003eYamada Y, Buehring B, Krueger D, Anderson RM, Schoeller DA, Binkley N: \u003cstrong\u003eElectrical Properties Assessed by Bioelectrical Impedance Spectroscopy as Biomarkers of Age-related Loss of Skeletal Muscle Quantity and Quality\u003c/strong\u003e. \u003cem\u003eThe journals of gerontology Series A, Biological sciences and medical sciences \u003c/em\u003e2017, \u003cstrong\u003e72\u003c/strong\u003e(9):1180-1186.\u003c/li\u003e\n\u003cli\u003eUemura K, Yamada M, Okamoto H: \u003cstrong\u003eAssociation of bioimpedance phase angle and prospective falls in older adults\u003c/strong\u003e. \u003cem\u003eGeriatrics \u0026amp; gerontology international \u003c/em\u003e2019, \u003cstrong\u003e19\u003c/strong\u003e(6):503-507.\u003c/li\u003e\n\u003cli\u003eTomeleri CM, Cavalcante EF, Antunes M, Nabuco HCG, de Souza MF, Teixeira DC, Gobbo LA, Silva AM, Cyrino ES: \u003cstrong\u003ePhase Angle Is Moderately Associated With Muscle Quality and Functional Capacity, Independent of Age and Body Composition in Older Women\u003c/strong\u003e. \u003cem\u003eJournal of geriatric physical therapy (2001) \u003c/em\u003e2019, \u003cstrong\u003e42\u003c/strong\u003e(4):281-286.\u003c/li\u003e\n\u003cli\u003eNorman K, Stob\u0026auml;us N, Pirlich M, Bosy-Westphal A: \u003cstrong\u003eBioelectrical phase angle and impedance vector analysis--clinical relevance and applicability of impedance parameters\u003c/strong\u003e. \u003cem\u003eClinical nutrition (Edinburgh, Scotland) \u003c/em\u003e2012, \u003cstrong\u003e31\u003c/strong\u003e(6):854-861.\u003c/li\u003e\n\u003cli\u003eBarbosa-Silva MC, Barros AJ, Wang J, Heymsfield SB, Pierson RN, Jr.: \u003cstrong\u003eBioelectrical impedance analysis: population reference values for phase angle by age and sex\u003c/strong\u003e. \u003cem\u003eThe American journal of clinical nutrition \u003c/em\u003e2005, \u003cstrong\u003e82\u003c/strong\u003e(1):49-52.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":" \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cdiv class=\"SimplePara\"\u003eCharacteristics of study population\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eFeatures\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003eMen(n\u0026thinsp;=\u0026thinsp;122)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003eNon-sarcopenia group(n\u0026thinsp;=\u0026thinsp;66)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003ePossible sarcopenia group(n\u0026thinsp;=\u0026thinsp;56)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eP\u003c/span\u003e value\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eBasic information\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eAge (years), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e53.12\u0026thinsp;\u0026plusmn;\u0026thinsp;13.84\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e46.00\u0026thinsp;\u0026plusmn;\u0026thinsp;11.00\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e61.00\u0026thinsp;\u0026plusmn;\u0026thinsp;12.00\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.224\u003csup\u003e**\u003c/sup\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eDialysis duration (Months), median (IQR)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e48.00(19.50,84.00)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e52(36,60)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e48(36,72)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e-0.409\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eHTN, n (%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eNo\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e15(12.30%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e9(60.00%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e6(40.00%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.240\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eYes\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e107(87.70)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e57(53.30%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e50(46.70%)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eDM, n (%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eNo\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e89(73.00%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e57(64.00%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e32(36.00%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003e13.109\u003csup\u003e**\u003c/sup\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eYes\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e33(27.00%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e9(27.30%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e24(72.70%)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eBody measurement results\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eCC (cm), median (IQR)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e33.00(31.00,35.00)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e33.00(33.00, 34.00)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e33.00(32.00,35.00)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e-1.184\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eBMI (kg/m\u0026sup2;), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e23.52\u0026thinsp;\u0026plusmn;\u0026thinsp;3.01\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e23.40\u0026thinsp;\u0026plusmn;\u0026thinsp;2.90\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e23.60\u0026thinsp;\u0026plusmn;\u0026thinsp;3.10\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.502\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003ePha (\u0026deg;), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e6.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e6.98\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e5.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.200\u003csup\u003e**\u003c/sup\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eSMI (kg/m\u0026sup2;), median (IQR)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e8.20(7.80,8.80)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e8.30(8.10,8.70)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e8.10(8.10,8.50)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e-1.685\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eHGS (kg), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e31.42\u0026thinsp;\u0026plusmn;\u0026thinsp;7.73\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e36.20\u0026thinsp;\u0026plusmn;\u0026thinsp;5.70\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e25.80\u0026thinsp;\u0026plusmn;\u0026thinsp;5.80\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.050\u003csup\u003e**\u003c/sup\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eSPPB (scores), median (IQR)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e10.00(8.00,12.00)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e12.00(12.00,12.00)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e8.00(8.00,8.00)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e-8.996\u003csup\u003e**\u003c/sup\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003csup\u003e*\u003c/sup\u003e \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eP\u003c/span\u003e values less than 0.05\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e\u003csup\u003e**\u003c/sup\u003e \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eP\u003c/span\u003e values less than 0.001\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eAbbreviations: CC, Calf circumference; BMI, body mass index; Pha, phase angle; SMI, Skeletal muscle index; HGS, Handgrip strength; SPPB, Short Physical Performance Battery; SD, standard deviation; HTN, Hypertension; DM, Diabetes mellitus; IQR, interquartile range.\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003cbr/\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cdiv class=\"SimplePara\"\u003eCharacteristics of study population\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eFeatures\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003eWomen(n\u0026thinsp;=\u0026thinsp;98)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003eNon-sarcopenia group(n\u0026thinsp;=\u0026thinsp;43)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003ePossible sarcopenia group(n\u0026thinsp;=\u0026thinsp;55)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eP\u003c/span\u003e value\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eBasic information\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eAge (years), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e52.37\u0026thinsp;\u0026plusmn;\u0026thinsp;13.06\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e44.00\u0026thinsp;\u0026plusmn;\u0026thinsp;9.00\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e59.00\u0026thinsp;\u0026plusmn;\u0026thinsp;12.00\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.963\u003csup\u003e**\u003c/sup\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eDialysis duration (Months), median (IQR)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e58.50(24.00,84.50)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e60.00(45.00,77.00)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e57.00(40.00,72.00)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e-0.057\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eHTN, n (%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eNo\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e16(16.3%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e9(56.3%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e7(43.8%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.189\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eYes\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e82(83.7%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e34(41.5%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e48(58.5%)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eDM, n (%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eNo\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e82(83.7%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e39(47.6%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e43(52.4%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003e2.767\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eYes\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e16(16.3%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e4(25.0%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e12(75.0%)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eBody measurement results\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eCC (cm), median (IQR)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e31.00(29.00,33.00)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e32.00(32.00,33.00)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e31.00(31.00,33.00)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e-0.252\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eBMI (kg/m\u0026sup2;), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e22.24\u0026thinsp;\u0026plusmn;\u0026thinsp;2.95\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e21.70\u0026thinsp;\u0026plusmn;\u0026thinsp;3.00\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e22.60\u0026thinsp;\u0026plusmn;\u0026thinsp;2.80\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.038\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003ePha (\u0026deg;), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e5.77\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e6.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e5.47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.188\u003csup\u003e*\u003c/sup\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eSMI (kg/m\u0026sup2;), median (IQR)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e6.60(6.30,7.12)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e6.80(6.60,7.20)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e6.50(6.40,6.80)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e-1.914\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eHGS (kg), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e19.65\u0026thinsp;\u0026plusmn;\u0026thinsp;5.85\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e23.60\u0026thinsp;\u0026plusmn;\u0026thinsp;3.80\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e16.50\u0026thinsp;\u0026plusmn;\u0026thinsp;5.30\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e4.106\u003csup\u003e**\u003c/sup\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eSPPB (scores), median (IQR)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e9.50(7.00,12.00)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e12.00(12.00,12.00)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e7.00(7.00,8.00)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e-7.885\u003csup\u003e**\u003c/sup\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003csup\u003e*\u003c/sup\u003e \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eP\u003c/span\u003e values less than 0.05\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e\u003csup\u003e**\u003c/sup\u003e \u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eP\u003c/span\u003e values less than 0.001\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eAbbreviations: CC, Calf circumference; BMI, body mass index; Pha, phase angle; SMI, Skeletal muscle index; HGS, Handgrip strength; SPPB, Short Physical Performance Battery; SD, standard deviation; HTN, Hypertension; DM, Diabetes mellitus; IQR, interquartile range.\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003cbr/\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cdiv class=\"SimplePara\"\u003eBinary Logistic regression analysis of possible sarcopenia in men MHD patients.\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eVariables\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eB\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eSE\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eWald χ\u0026sup2;\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eP\u003c/span\u003e value\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eOR\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003eOR (95% CI)\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003eLower\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003eUpper\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003econstant\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026minus;0.287\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e3.645\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.006\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.937\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.751\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eAge (years)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.093\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.025\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e13.986\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026lt;0.001\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.097\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.045\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.152\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eBMI (kg/m\u0026sup2;)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.264\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.125\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e4.471\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.034\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.302\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.020\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.664\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003ePha (\u0026deg;)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026minus;1.098\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.330\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e11.043\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.001\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.334\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.175\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.637\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eNote: The variables entered in step 1: age, Dialysis duration, diabetes, hypertension, CC, BMI, Pha.\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eAbbreviations: CC, Calf circumference; BMI, body mass index; Pha, phase angle.\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003cbr/\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cdiv class=\"SimplePara\"\u003eBinary Logistic regression analysis of possible sarcopenia in women MHD patients.\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eVariables\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eB\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eSE\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eWald χ\u0026sup2;\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eP\u003c/span\u003e value\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eOR\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003eOR (95% CI)\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003eLower\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003eUpper\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003econstant\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026minus;5.820\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e3.356\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e3.008\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.083\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.003\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eAge (years)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.120\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.030\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e15.819\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026lt;0.001\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.127\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.063\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.196\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003ePha (\u0026deg;)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026minus;0.653\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.328\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e3.953\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.047\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.521\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.274\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.991\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eNote: The variables entered in step 1: age, Dialysis duration, diabetes, hypertension, CC, BMI, Pha.\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eAbbreviations: CC, Calf circumference; BMI, body mass index; Pha, phase angle.\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e "}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"maintenance hemodialysis patients, bioimpedance, phase angle, possible sarcopenia, receiver operating characteristic curve","lastPublishedDoi":"10.21203/rs.3.rs-4064617/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4064617/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cb\u003eBackground\u003c/b\u003e Early identification of possible sarcopenia in patients on maintenance hemodialysis (MHD) is important to prevent adverse outcomes and improve the quality of life of these patients. The aim of this study was to investigate the relationship between phase angle (Pha) and possible sarcopenia and to assess its performance as a predictor of possible sarcopenia in MHD patients.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMethods\u003c/b\u003e Data were retrospectively collected from outpatient under going MHD at Wenjiang Hemodialysis Center in the Department of Nephrology in West China Hospital, Sichuan University, Chengdu, China. The 2019 consensus update by Asian working group for sarcopenia (AWGS) was used to assess whether a MHD patient had sarcopenia. A total of 244 MHD patients were collected in this study, and after excluding patients with sarcopenia, data from 122 men (56 with possible sarcopenia) and 96 women (55 with possible sarcopenia) patients were included in this study. Participants were divided into a possible sarcopenic group and a non-sarcopenic group to develop a binary classification.\u003c/p\u003e \u003cp\u003e \u003cb\u003eResults\u003c/b\u003e After eliminating handgrip strength (HGS), short physical performance battery (SPPB), and skeletal muscle index (SMI), the best three features for possible sarcopenia identifcation of men patients are age, body mass index (BMI), and Pha (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05). Meanwhile, age, and Pha are the best two features for Women (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05). Spearman analysis showed that Pha was significantly negatively associated with possible sarcopenia (men: \u003cem\u003er\u003c/em\u003e =\u0026minus;0.501, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; women: \u003cem\u003er\u003c/em\u003e=\u0026minus;0.356, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Pha showed significant positive associations with HGS, SPPB and SMI (men: \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.590, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001、\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.485, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001、\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.338, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; women: \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.374, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001、\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.360, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001、\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.290, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004). The results of receiver operating characteristic (ROC) curve analysis showed that the area under the receiver operating characteristic curves (AUC) of Pha in screening male possible sarcopenia was 0.790, with sensitivity of 78.57%, specificity of 74.24%, and the optimal cutoff value of 6.52\u0026deg;. The AUC of Pha in screening women for possible sarcopenia was 0.707, sensitivity of 58.18%, specificity of 76.74%, and optimal cutoff value of 5.60\u0026deg;.\u003c/p\u003e \u003cp\u003e \u003cb\u003eConclusions\u003c/b\u003e Pha may be a useful and simple predictor of the risk of possible sarcopenia in patients with MHD, and more research is needed to further promote the use of Pha in possible sarcopenia.\u003c/p\u003e","manuscriptTitle":"Bioelectrical impedance analysis–derived phase angle predicts possible sarcopenia in patients on maintenance hemodialysis: A retrospective study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-21 18:18:13","doi":"10.21203/rs.3.rs-4064617/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-29T09:10:59+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-28T01:54:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"338049924539449955785569125374724889426","date":"2024-07-22T20:08:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-24T13:43:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"26442482971752157424510844819394493758","date":"2024-06-17T16:12:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-21T18:00:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-21T17:58:38+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-03-18T17:53:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-18T17:40:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nephrology","date":"2024-03-10T11:17:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"01b28d4b-4e5e-414b-b5f3-857354154c91","owner":[],"postedDate":"March 21st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-10-21T16:03:29+00:00","versionOfRecord":{"articleIdentity":"rs-4064617","link":"https://doi.org/10.1186/s12882-024-03787-5","journal":{"identity":"bmc-nephrology","isVorOnly":false,"title":"BMC Nephrology"},"publishedOn":"2024-10-16 15:57:50","publishedOnDateReadable":"October 16th, 2024"},"versionCreatedAt":"2024-03-21 18:18:13","video":"","vorDoi":"10.1186/s12882-024-03787-5","vorDoiUrl":"https://doi.org/10.1186/s12882-024-03787-5","workflowStages":[]},"version":"v1","identity":"rs-4064617","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4064617","identity":"rs-4064617","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}