Abstract
Background
Muscle wasting has been linked to negative clinical outcomes in patients undergoing peritoneal dialysis (PD). However, it remains unclear how early changes in muscle mass after the initiation of PD affects the clinical outcome. This study aimed to identify factors influencing changes in lean tissue mass (LTM) over six months in new PD patients and to assess their prognostic significance.
Methods
We conducted a study of 90 new PD patients. Over a six-month period, we recorded changes in LTM and adipose tissue mass (ATM) using bioimpedance spectrometry. Outcome measures included patient and technique survival rates.
Results
After 6 months of PD, body weight and body mass index remained unchanged, but 42 patients (46.7%) had decrease in LTM for ≥ 1 kg. The percentage of LTM (LTMp) also dropped from 63.4 ± 13.6% to 61.5 ± 13.4% (p = 0.006), accompanied by an increase in ATM. Multiple linear regression models showed a strong correlation between changes in LTM and ATM; for every 1 kg increase in ATM, there was a 1.01 kg decrease in LTM (95% confidence interval: 0.797 to 0.855, p < 0.0001). However, the change in LTM during the first six months of PD was not associated with patient or technique survival rates.
Conclusion
Although the overall body weight was static, there was a trend of reduction in LTM and a concommitant increase in ATM during the first 6 months of PD. However, these changes were not associated with adverse clinical outcome.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12882-025-04350-6.
Keywords: Renal failure, Malnutrition, Sarcopenia, Frailty
Introduction
Sarcopenia refers to the loss of skeletal muscle mass and strength, which is prevalent among the elderly and individuals with chronic conditions, such as those undergoing chronic dialysis [1]. Numerous studies have demonstrated that the reduction in skeletal muscle is linked to negative consequences like falls, decreased function, frailty, and increased mortality [1]. In patients receiving dialysis, sarcopenia plays a role in their reduced functionality and higher morbidity rates [2, 3]. In a systematic review and meta-analysis, Wathanavasin et al. [4] showed that sarcopenia was significantly associated with higher mortality risk and cardiovascular events dialysis patients.
Lean tissue mass (LTM), which can be readily determined by bioimpedance spectroscopy (BIS), is now commonly used as the measurement of skeletal muscle mass [5]. BIS measures the resistances of body tissues to electrical current at various frequencies, which were then used to estimate the muscle mass and other body compositions and enable the diagnosis of sarcopenia [6, 7]. This method is particularly useful in the CKD population, as it provides a rapid and non-invasive approach for the assessment of muscle mass as well as body fluid status.
LTM has been found to have prognostic relevance in patients with and without kidney disease. In older adults, a low LTM was associated with increased risk of cognitive function imparement and mortality [8]. In patients with stage 4 and 5 CKD, a low LTM index (LTI) was found to be an independent risk factor for mortality [9]. In hemodialysis patients, progressive loss of LTM has been shown to be related to worse quality of life and increased overall mortality [10]. Published data on LTM in peritoneal dialysis (PD) patients, however, are limited. In a study of 160 PD patients, Kim et al. noted that low LTI at baseline predicted all-cause mortality, but the association became insignificant when cardiovascular factors were included in the multivariate analysis [11]. In this study, however, changes in LTI and fat tissue index (FTI) after 2 years of PD were strongly associated with all-cause mortality than single values in LTI and FTI [11].
In clinical practice, it is imperative to assess the prognostic significance of changes in LTM following patient stabilization on PD rather than the change after an extended period of dialysis. Our present study aims to examine the factors influencing LTM changes after a 6-month period of PD and to elucidate the prognostic implications of these changes.
Patients and methods
The study was approved by the Joint Chinese University Hong Kong-New Territories East Cluster Clinical Research Ethics Committee (approval number CRE-2023.363). All procedures in this study followed the guidelines outlined in the Declaration of Helsinki.
Patient selection
This study is a retrospective analysis of a prospective observational cohort on incident adult PD patients at a single center. Patients who had failed chronic hemodialysis, with pacemaker or metallic prosthesis, who were scheduled for living donor kidney transplant or transferal to other renal centers within 6 months were excluded. Baseline multi-frequency bioimpedance spectroscopy, dialysis adequacy, and other laboratory tests were performed around 4 weeks after patients were stable on PD and then repeated 6 months later. All patients provided written inform consent for the study.
Multi-frequency bioimpedance spectroscopy
As described previously [12], we assessed the lean tissue mass (LTM) using the multi-frequency bioimpedance spectroscopy study. Briefly, electrodes were attached to the patient’s right hand and right foot while in a supine position. The Body Composition Monitor (BCM, Fresenius Medical Care, Germany) was used to measure LTM. Percentage of LTM (LTMp) was computed from LTM and body weight. During the bioimpedance study, we also measured the adipose tissue mass (ATM), volume of overhydration (OH), total body water (TBW), extracellular water (ECW), and intracellular water (ICW). Bioimpedance spectroscopy study was performed during PD fluid dwell because peritoneal dialysate had minimal effect on the measurements according to our previous study [13].
Dialysis adequacy and other laboratory indices
The assessment of dialysis adequacy was performed by 24-hour dialysate and urine collection as previously described [14], and the total weekly Kt/V was calculated accordingly. The residual glomerular filtration rate (GFR) was determined by the average of 24-hour urinary urea and creatinine clearances [15]. Serum albumin levels were measured by the bromocresol purple method [16]. Other laboratory tests, including routine biochemistry, haemoglobin level, serum iron, total iron binding capacity, and ferritin levels, were performed as part of the routine clinical care.
Follow up and outcome parameters
After the second bioimpedance spectroscopy measurement at 6 months, all patients were further followed till December 2023. During the follow-up period, the clinical management was decided by an individual clinician and not affected by the study. Primary outcome measuress of this study includes patient survival, technique survival, peritonitis-free survival, peritonitis rate, number of hospital admission, and the total duration of hospitalizations. The peritonitis rate was reported as the number of peritonitis episodes per patient per year as previously described [17]. In this study, technique failure was defined as transferral to hemodialysis, receiving kidney transplant, or death, while transferral to other dialysis centers or recovery of renal function were considered as censoring events.
Statistical analysis
Statistical analysis was performed using the software SPSS (version 28.0. IBM Corporation, Armonk, NY) and GraphPad Prism (version 10.1.1, GraphPad Software, CA). Data are presented as the mean ± standard deviation unless specified otherwise. The Pearson’s correlation coefficient was employed to investigate the association between the correlation between LTM and other nutritional and biochemical parameters. Similarly, the correlation between changes in LTM (∆LTM) and changes in other parameters after 6 months of PD was also analyzed by the Pearson’s correlation coefficient. Multivariate linear regression models were constructed to identify independent factors associated with ∆LTM and ∆LTMp. In the linear regression models, we included sex, age, and variables with p values < 0.1 in the univariate linear regression analysis. The Kaplan-Meier method was utilized to present the data of patient, technical, and peritonitis-free survival rates. Patients were grouped in quartiles according to their ∆LTM, and the survival rates were compared by the log-rank test. The peritonitis rate, number of hospital admission, and duration of hospitalization between quartiles were compared by the Kruskal Wallis test. A p value less than 0.05 was taken as statistically significant. All probabilities were two-tailed.
Results
We studied 90 incident PD patients. Their baseline demographics and clinical are summarized in Table 1. Multifrequency bioimpedance spectroscopy, as well as other standard biochemical tests, were performed at baseline and then repeated 6 months after PD. The results are summarized in Table 2.
Table 1.
Baseline demographic and clinical characteristics
| No. of patients | 90 |
| Sex (male: female) | 44:46 |
| Age (years) | 60.8 ± 10.8 |
| Height (cm) | 161.5 ± 8.7 |
| Blood pressure (mmHg) | |
| Systolic | 134.1 ± 21.6 |
| Diastolic | 72.3 ± 12.7 |
| Renal diagnosis, no. of case (%) | |
| Diabetic nephropathy | 37 (41.1%) |
| Glomerulonephritis | 23 (25.6%) |
| Hypertension | 11 (12.2%) |
| Urological problem | 5 (5.6%) |
| Polycystic kidney disease | 3 (3.3%) |
| Others or unknown | 11 (12.2%) |
| Major comorbidities, no. of case (%) | |
| Diabetes mellitus | 45 (50.0%) |
| Coronary artery disease | 24 (26.7%) |
| Cerebrovascular accident | 21 (23.3%) |
| Peripheral vascular disease | 6 (6.7%) |
| Charlson’s comorbidity index | 6.1 ± 2.4 |
| Type of PD, no. of case (%) | |
| Machine-assisted automated PD | 15 (16.7%) |
| Low GDP solution | 21 (23.3%) |
PD, peritoneal dialysis; GDP, glucose degradation products
Table 2.
Baseline bioimpedance and biochemical information
| 0 month | 6 months | P value | |
|---|---|---|---|
| Body weight (kg) | 61.1 ± 11.3 | 61.9 ± 11.2 | 0.077 |
| Body mass index (kg/m2) | 23.4 ± 3.8 | 23.7 ± 3.6 | 0.248 |
| Bioimpedance parameters | |||
| Lean tissue mass (kg) | 38.6 ± 9.9 | 37.7 ± 9.3 | 0.041 |
| Lean tissue percentage (%) | 63.4 ± 13.6 | 61.5 ± 13.4 | 0.006 |
| Adipose tissue mass (kg) | 19.1 ± 9.3 | 20.6 ± 9.4 | 0.002 |
| Overhydration (L) | 3.3 ± 3.3 | 3.1 ± 3.0 | 0.286 |
| E/I ratio | 0.97 ± 0.18 | 0.97 ± 0.18 | 0.912 |
| Hemoglobin (g/dL) | 9.4 ± 1.5 | 9.6 ± 1.6 | 0.262 |
| Serum albumin (g/L) | 35.3 ± 4.8 | 35.3 ± 5.0 | 0.873 |
| Fasting plasma glucose (mmol/l) | 6.1 ± 2.1 | 6.6 ± 2.0 | 0.226 |
| Lipid profile (mmol/l) | |||
| Total cholesterol | 5.2 ± 1.6 | 5.2 ± 1.5 | 0.467 |
| LDL cholesterol | 3.1 ± 1.3 | 3.1 ± 1.2 | 0.827 |
| HDL cholesterol | 1.3 ± 0.4 | 1.3 ± 0.5 | 0.211 |
| Triglyceride | 1.8 ± 1.2 | 2.0 ± 1.9 | 0.433 |
| Total weekly Kt/V | 2.2 ± 0.6 | 2.1 ± 0.6 | 0.188 |
| Residual GFR (ml/min/1.73m2) | 3.9 ± 2.8 | 2.8 ± 2.5 | 0.008 |
| Iron profile | |||
| Plasma iron (µmol/l) | 12.6 ± 5.8 | 13.1 ± 5.4 | 0.845 |
| Plasma TIBC (µmol/l) | 37.4 ± 7.4 | 37.7 ± 8.1 | 0.585 |
| Iron saturation (%) | 0.3 ± 0.2 | 0.4 ± 0.1 | 0.979 |
| Serum ferritin (ng/mL) | 1124.5 ± 1004.7 | 1122.5 ± 1125.0 | < 0.0001 |
E/I ratio, extracellular to intracellular volume ration; LDL, low density lipoprotein; HDL, high density lipoprotein; Kt/V, dialysis adequacy; GFR, glomerular filtration rate; TIBC, total iron binding capacity
Change in body mass after 6 months
After PD for 6 months, 42 (46.7%) had decrease in LTM for ≥ 1 kg, 33 (36.7%) had decrease for ≥ 2 kg. On average, there was a significant decrease in lean tissue mass (LTM) from 38.6 ± 9.9 to 37.7 ± 9.3 kg (paired Student’s t test, p = 0.041) and lean tissue percentage (LTMp) from 63.4 ± 13.6% to 61.5 ± 13.4% (p = 0.006), but a concommitant increase in adipose tissue mass (ATM) from 19.1 ± 9.3 to 20.6 ± 9.4 kg (p = 0.002). As a result, there was no significant change in body weight or body mass index, and the volume of overhydration remained similar during this period (Table 2). The baseline clinical and biochemical characteristics for patients with decrease in LTM ≥ 1 kg and < 1 kg are compared in Supplementary Table 1. The internal correlation between body weight and bioimpedance spectroscopy parameters are summarized in Table 3. In essence, baseline LTM and LTMp were inversely correlated with ATM and E/I. Similarly, after PD for 6 months, the change in LTM and LTMp had close inverse correlations with the concommitant changes in ATM and E/I ratio. Notably, the change in body weight was significantly correlated with the change in ATM but inversely correlated with the change in LTMp.
Table 3.
Internal correlation matrices between body composition parameters baseline body composition
| Body weight | LTM | LTMp | ATM | OH | |
|---|---|---|---|---|---|
| (A) Baseline body composition | |||||
| LTM |
r = 0.537, p < 0.0001 |
||||
| LTMp |
r = 0.187, p = 0.083 |
r = 0.720, p < 0.0001 |
|||
| ATM |
r = 0.396, p < 0.0001 |
r = -0.494, p < 0.0001 |
r = − 0.905, p < 0.0001 |
||
| OH |
r = 0.482, p < 0.0001 |
r = 0.248, p = 0.021 |
r = 0.121, p = 0.265 |
r = -0.068, p = 0.532 |
|
| E/I ratio |
r = 0.371, p < 0.0001 |
r = -0.247, p = 0.021 |
r = -0.566, p < 0.0001 |
r = 0.316, p = 0.003 |
r = 0.833, p < 0.0001 |
| (B) Change in body composition in 6 months | |||||
| LTM |
r = 0.193, p = 0.073 |
||||
| LTMp |
r = -0.319, p = 0.003 |
r = 0.851, p < 0.0001 |
|||
| ATM |
r = 0.344, p = 0.001 |
r = -0.769, p < 0.0001 |
r = -0.890, p < 0.0001 |
||
| OH |
r = 0.354, p = 0.001 |
r = 0.142, p = 0.188 |
r = -0.079, p = 0.467 |
r = -0.291, p = 0.007 |
|
| E/I ratio |
r = 0.423, p < 0.0001 |
r = -0.226, p = 0.036 |
r = -0.448, p < 0.0001 |
r = 0.093, p = 0.396 |
r = 0.895, p < 0.0001 |
Multiple linear regression model was further constructed to identify factors associated with changes in LTM after 6 months of PD. In essence, the change in body weight, ATM, and E/I ratio were the only independent factors associated with the change in LTM (Table 4; full model in Supplementary Table 2). In this model, a reduction in LTM by 1 kg was associated with a corresponding increase in ATM by 1.01 ± 0.42 kg, indicating a reciprocal change of the two parameters. Similar findings were observed when multiple linear regression model was constructed for the change in LTMp, with the change in body weight, ATM, and E/I ratio being the only independent predictors (Supplementary Table 3), and a reciprocal finding was observed when multiple linear regression model was constructed for the change in ATM, with the change in body weight, LTM, and overhydration volume being the only independent predictors (Supplementary Table 4).
Table 4.
Summary of multi-variable linear regression models on the factors associated with the change in lean tissue mass
| Beta | 95% CI | P values | |
|---|---|---|---|
| Sex | 0.004 | -0.380 to 0.461 | 0.846 |
| Age | 0.017 | -0.008 to 0.024 | 0.330 |
| Baseline parameters | |||
| Lean tissue mass | 0.013 | -0.019 to 0.035 | 0.571 |
| Adipose tissue mass | 0.006 | -0.014 to 0.012 | 0.680 |
| Change in 6 months | |||
| Weight | 0.803 | 0.850 to 0.936 | < 0.0001 |
| Adipose tissue mass | -1.011 | -0.855 to – 0.797 | < 0.0001 |
| E/I ratio | -0.425 | -16.092 to -13.965 | < 0.0001 |
| FPG | 0.001 | -0.054 to 0.058 | 0.941 |
Patient and technical survival
During a median follow-up of 67.5 (IQR 37.9 to 99.9) months, 65 (72.2%) patients died. The causes of death were infections other than peritonitis (17 cases), ischemic heart disease (15 cases), cerebral vascular accident (7 cases), peritonitis (14 cases), sudden cardiac death (7 cases), termination of dialysis (1 case), and other specific causes (4 cases). During that period, 12 patients were converted to hemodialysis, 6 patients had kidney transplantation, and 3 patients were transferred to other centres. The relation between the change in LTM after 6 months of PD, divided into quartiles, and patient and technique survival rates are summarized in Kaplan Meier plots (Fig. 1A). The 2-year patient survival rates for quartiles I to IV of the change in LTM were 90.9%, 70.8%, 95.2%, and 86.3%, respectively (log-rank test p = 0.186). The 2-year technical survival rates for quartiles I to IV of the change in LTM were 87.0%, 66.7%, 95.2%, and 86.4%, respectively (log-rank text p = 0.098) (Fig. 1B). The result of survival analysis remained similar when follow up was censored at 24 months.
Fig. 1.
Kaplan-Meier plot of (A) patient survival; (B) technique survival; and (C) peritonitis-free survival. Patients were divided into quartiles according to the change in lean tissue mass (LTM) over the first 6 months of peritoneal dialysis, with quartile I the lowest values (i.e. most reduction in LTM). Data were compared by the log-rank test
Peritonitis and hospitalization
During the study period, there were 181 peritonitis episodes recorded in 62 patients; 28 patients (31.1%) were peritonitis-free. The overall peritonitis rate was 0.40 episode per patient-year follow up. The 2-year peritonitis-free survival rate for quartiles I to IV of the change in LTM were 56.2%, 61.6%, 83.3%, and 68.8%, respectively (log-rank test p = 0.304) (Fig. 1C). The peritonitis rate for quartiles I to IV of the change in LTM were 0.31, 0.51, 0.18, and 0.49 episodes per patient-year, respectively (p = 0.06). There was no significant association between the peritonitis rate and the change in LTM, LTMp, or ATM (Supplementary Table 5).
During the study period, there were 650 hospital admissions, with a total of 4554 days of hospital stay. The hospitalization rates were 1.50, 1.00, 0.99, and 1.53 per patient-year for quartiles I to IV of the change in LTM, respectively (p = 0.103). The durations of hospital stay were 13.2, 7.1, 6.5, and 11.8 days per patient-year for quartiles I to IV of the change in LTM, respectively. There was no significant association between the number of hospital admission or duration of hospitalization with the change in LTM, LTMp, or ATM (Supplementary Table 5).
Discussion
In this present study, we reviewed the changes in body composition and nutritional indicators during the first 6 months of PD. Unlike previous studies that often cover extended periods, our focus was on the early period when the patients were stabilized on PD. Our findings confirmed that muscle wasting and fat gain were common and occurred simultaneously in the early period after PD was initiated, which is consistent with the previous report of Guida et al. [18]. We found that in addition to weight loss, increase in adipose tissue mass and rise in extra-to-intracellular water ratio were independent predictors of lean tissue mass loss. In contrast, no baseline demographic or biochemical parameters predict muscle wasting in the early months after PD.
The association between the changes in ATM and LTM is expected as similar findings have been reported in hemodialysis patients [19]. Based on our data, every 1 kg increase of ATM is asociated with 1.01 kg decrease in LTM (see Table 4). As a result, the overall body weight remained static. We also observed a significant inverse correlation between the change in E/I ratio and LTM. This is an expected finding because LTM measured by BIS is derived from the volume of intracellular water water (ICW) [20], which is the denominator of the E/I ratio. Although the E/I ratio is an indicator of fluid overload [21], we found no association between the change in LTM and overhydration volume (OH), suggesting that the correlation between the changes in E/I ratio and LTM is mathematical coupling rather than a biological phenomenon.
In this study, we did not find any baseline biochemical parameter or their serial chang related to the number of peritonitis episodes, number of hospitalizations, or the duration of hospitalization. Similarly, we did not find any association between reduction in muscle mass during the first 6 months of PD and the subsequent patient, technical, or peritonitis-free survival. On the first glance, our finding appears to be different from the previous studies [11, 23]. Notably, Kim et al. [11] reported that muscle wasting was associated with an increase in patient mortality, while Davenport [23] showed that weight change after PD was associated with the subsequent risk of peritonitis. Nonetheless, there are important differences between our studies from previous ones. Notably, both of the previous studies examined the changes of muscle mass over 2 years [11, 23], while we focused on the change in the first 6-month of PD. In addition, baseline LTM is negatively associated with its subsequent change in 6 months by univariate analysis. It was possible that patients who experienced greater LTM reduction were more likely to have a higher LTM at baseline, which negated the effect on patient mortality [22]. Since both our study and the previously ones had relatively small sample sizes, further studies are required to confirm the findings.
The present study has several limitations. First, the sample size was modest and outliers were not uncommon in our data set. Based on our observation, it is estimated that a sample size of 277 would be required to have 80% power for confirming a significant effect [24]. Since we only examined the change in LTM over the first 6 months of PD – and previous studies only examined the change in two time points [11, 23] – serial changes in muscle mass over extended period of time would be an important area to explore. Although we found an inverse correlation between muscle mass and fat mass, we did not classify the adipose tissue to subcutaneous and visceral fat, making it unclear which type of adipose tissue is actually replacing the muscle. More importantly, other factors that may affect muscle and adipose tissue mass, notably, physical activity, have not been assessed.
In conclusion, we found a trend of reduction in LTM and a concommitant increase in ATM during the first 6 months of PD. However, the changes during the first 6 months of PD was not associated with an adverse clinical outcome subsequently. Since the overall body weight remained static, our result highlights the need of comprehensive body composition examination in PD patients rather than relying on the simple BMI.
CI, confidence interval; E/I ratio, extracellular to intracellular fluid volume ration; FPG, fasting plasma glucose.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Author contributions
Research idea and study design: Lixing Xu (LXX), Jack KC Ng (JKCN), CC Szeto (CCS); data acquisition: JKCN, Winston WS Fung (WWSF), Gordon CK CHan (GCKC); data analysis/interpretation: LXX, JKCN, CCS; statistical analysis: LXX, JKCN, CCS; supervision or mentorship: KM Chow (KMC), CCS; manuscript preparation: LXX, CCS. Each author contributed important intellectual content during manuscript drafting or revision and accepts accountability for the overall work by ensuring that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved.
Funding
This study was supported by the Richard Yu Chinese University of Hong Kong (CUHK) PD Research Fund, and CUHK research accounts 6905134, 6906662, and 8601286. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Data availability
The original data supporting the findings of this study are openly available in Github repository at: https://github.com/szetocc/serial_LTM.
Declarations
Human ethics
The study was approved by the Joint Chinese University Hong Kong-New Territories East Cluster Clinical Research Ethics Committee (approval number CRE-2023.363). All procedures in this study followed the guidelines outlined in the Declaration of Helsinki.
Consent to participate
All patients provided written inform consent for the study.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The original data supporting the findings of this study are openly available in Github repository at: https://github.com/szetocc/serial_LTM.