Protein-energy wasting, which involves loss of fat and muscle mass, is prevalent and is associated with mortality in hemodialysis (HD) patients. We investigated the associations of fat tissue and muscle mass indices with all-cause mortality in HD patients. The study included 162 patients undergoing HD. The fat tissue index (FTI) and skeletal muscle mass index (SMI), which represent respective tissue masses normalized to height squared, were measured by bioimpedance analysis after dialysis. Patients were divided into the following four groups according to the medians of FTI and SMI values: group 1 (G1), lower FTI and lower SMI; G2, higher FTI and lower SMI; G3, lower FTI and higher SMI; and G4, higher FTI and higher SMI. The associations of the FTI, SMI, and body mass index (BMI) with all-cause mortality were evaluated. During a median follow-up of 2.5 years, 29 patients died. The 5-year survival rates were 48.6%, 76.1%, 95.7%, and 87.4% in the G1, G2, G3, and G4 groups, respectively (P = 0.0002). The adjusted hazard ratio values were 0.34 (95% confidence interval [CI] 0.10–0.95, P = 0.040) for G2 vs. G1, 0.13 (95%CI 0.01–0.69, P = 0.013) for G3 vs. G1, and 0.25 (95%CI 0.07–0.72, P = 0.0092) for G4 vs. G1, respectively. With regard to model discrimination, on adding both FTI and SMI to a model with established risk factors, the C-index increased significantly when compared with the value for a model with BMI (0.763 vs. 0.740, P = 0.016). Higher FTI and/or higher SMI values were independently associated with reduced risks of all-cause mortality in HD patients. Moreover, the combination of the FTI and SMI may more accurately predict all-cause mortality when compared with BMI. Therefore, these body composition indicators should be evaluated simultaneously in this population.

The geriatric nutritional risk index (GNRI) and modified creatinine index (mCI) are surrogate markers of protein-energy wasting in patients receiving hemodialysis. We aimed to examine whether a combined evaluation of these indices improved mortality prediction in this population. We retrospectively investigated 263 hemodialysis patients divided into two groups, using 91.2 and 20.16 mg/kg/day as cut-off values of GNRI and mCI, respectively. The resultant four groups were reshuffled into four subgroups defined using combinations of cut-off values of both indices and were followed up. During the follow-up period (median: 3.1 years), 103 patients died (46/103, cardiovascular causes). Lower GNRI and lower mCI were independently associated with all-cause mortality (adjusted hazard ratio (aHR) 4.96, 95% confidence intervals (CI) 3.10–7.94, and aHR 1.92, 95% CI 1.22–3.02, respectively). The aHR value for the lower GNRI and lower mCI group vs. the higher GNRI and higher mCI group was 7.95 (95% CI 4.38–14.43). Further, the addition of GNRI and mCI to the baseline risk assessment model significantly improved the C-index of all-cause mortality (0.801 to 0.835, p = 0.025). The simultaneous evaluation of GNRI and mCI could be clinically useful to stratify the risk of mortality and to improve the predictability of mortality in patients on hemodialysis.

Computed tomography (CT)-measured psoas muscle thickness standardized for height (PMTH) has emerged as a promising predictor of mortality. The study aimed to investigate whether PMTH could accurately predict mortality in patients undergoing hemodialysis. We examined 207 patients (mean age: 63.1 years; men: 66.2%) undergoing hemodialysis for more than 6 months in hospital affiliated clinic. PMTH was calculated at the L3 vertebra level using CT. Patients were divided according to the PMTH cut-off points: 8.44 mm/m in women and 8.85 mm/m in men; thereafter, they were combined into low and high PMTH groups. PMTH was independently correlated with the simplified creatinine index (β = 0.213, P = 0.021) and geriatric nutritional risk index (β = 0.295, P < 0.0001) in multivariate regression analysis. During a median follow-up of 3.7 (1.8–6.4) years, 76 patients died, including 41 from cardiovascular causes. In the multivariate Cox regression analysis, low PMTH (adjusted hazard ratio, 2.48; 95% confidence interval, 1.36–4.70) was independently associated with an increased risk of all-cause mortality. The addition of binary PMTH groups to the baseline risk model tended to improve net reclassification improvement (0.460, p = 0.060). In conclusion, PMTH may be an indicator of protein energy wasting and a useful tool for predicting mortality in patients undergoing hemodialysis.

This study aimed to investigate the associations of computed tomography (CT)-measured psoas muscle index (PMI: psoas muscle area normalized by height) and psoas muscle density (PMD: average of bilateral psoas muscle CT values [Hounsfield unit (HU)]) with mortality in patients undergoing hemodialysis. We included 188 hemodialysis patients who underwent abdominal CT. PMI and PMD were measured at the third lumbar vertebral level. We found that PMI and PMD were independently associated with the geriatric nutritional risk index and log C-reactive protein, respectively. The optimal cut-off values of PMI and PMD for men and women were 3.39 cm2/m2 and 41.6 HU, and 2.13 cm2/m2 and 37.5 HU, respectively. During follow-up (median 3.5 years), 69 patients died. Lower PMI and lower PMD were independently associated with an increased risk of all-cause mortality [adjusted hazard ratio (aHR) 2.05, 95% confidence interval (CI) 1.14–3.68; aHR 3.67, 95% CI 2.04–6.60), respectively]. The aHR for lower PMI and lower PMD vs. higher PMI and higher PMD was 5.34 (95% CI 2.38–11.97). The addition of PMI and PMD to the risk model significantly improved C-index from 0.775 to 0.893 (p < 0.00001). The combination of PMI and PMD may improve mortality prediction in patients undergoing hemodialysis.