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Muscle mass is important in determining patients' nutritional status. However, measurement of muscle mass requires special equipment that is inconvenient for clinical use. We aimed to develop and validate a nomogram model for predicting low muscle mass in patients undergoing hemodialysis (HD). A total of 346 patients undergoing HD were enrolled and randomly divided into a 70% training set and a 30% validation set. The training set was used to develop the nomogram model, and the validation set was used to validate the developed model. The performance of the nomogram was assessed using the receiver operating characteristic (ROC) curve, a calibration curve, and the Hosmer–Lemeshow test. A decision curve analysis (DCA) was used to evaluate the clinical practicality of the nomogram model. Age, sex, body mass index (BMI), handgrip strength (HGS), and gait speed (GS) were included in the nomogram for predicting low skeletal muscle mass index (LSMI). The diagnostic nomogram model exhibited good discrimination with an area under the ROC curve (AUC) of 0.906 (95% CI, 0.862–0.940) in the training set and 0.917 (95% CI, 0.846–0.962) in the validation set. The calibration analysis also showed excellent results. The nomogram demonstrated a high net benefit in the clinical decision curve for both sets. The prediction model included age, sex, BMI, HGS, and GS, and it can successfully predict the presence of LSMI in patients undergoing HD. This nomogram provides an accurate visual tool for medical staff for prediction, early intervention, and graded management. [ABSTRACT FROM AUTHOR]

In the updated consensus, low muscle strength overtook the role of low muscle mass, and probable sarcopenia was diagnosed once low muscle strength was detected. Whether the modified creatinine index (mCI) could identify persons with probable sarcopenia who may be at risk of adverse outcomes remains unknown. We aimed to evaluate the association of the mCI with probable sarcopenia and mortality in patients undergoing hemodialysis. In the cross-sectional study (n = 346), univariate and multivariable logistic regression analyses were performed to study the association of mCI with probable sarcopenia. Modified Quantitative Subjective Global Assessment (MQSGA) was used to evaluate the nutritional status. The performance of the mCI value for identifying probable sarcopenia was analyzed using receiver operating characteristic (ROC) curve analysis. The appropriate cutoff points were determined using Youden's method. In the longitudinal cohort study composed of an independent hemodialysis cohort (n = 218), cox proportional regression models were used to evaluate crude and adjusted hazard ratios and 95% confidence intervals (CIs) of death by mCI and MQSGA. Cross-sectional results showed that after adjusting for confounders, the association of mCI with low muscle strength remained significant. The area under the curve (AUC) of the mCI to predict probable sarcopenia was 0.804 (95% CI, 0.744–0.863; p < 0.001) for men and 0.787 (95% CI, 0.711–0.864; p < 0.001) for women. The optimal mCI cutoff values were 21.07 mg/kg/d for men and 19.57 mg/kg/d for women, respectively. Longitudinal results showed that compared with those in the high mCI group, subjects in the low mCI group had a higher risk of death for all causes (adjusted HR, 2.51; 95% CI, 1.16–5.41; p = 0.019). Adding the mCI significantly improved the predictive accuracy for death with an increase in C-index from 0.785 to 0.805 (p = 0.026) and improved the net reclassification index (38.6%, p = 0.021), while adding MQSGA did not. The mCI is a predictor of muscle strength and survival in hemodialysis patients, and is preferable to the MQSGA for predicting death. Assessment of mCI could provide additional predictive and prognostic information to sarcopenia. [ABSTRACT FROM AUTHOR]

It is becoming increasingly evident that the accurate assessment of fluid status is critical to ensure optimal care in patients undergoing hemodialysis (HD). Various fluid parameters, including overhydration (OH) and overhydration/extracellular water (OH/ECW%), which can be obtained using a bioimpedance spectroscopy device have been used to indicate the hydration status in such patients. This study aimed to explore the effect of these fluid parameters on cardiovascular events and determine which parameter was a better predictor of cardiovascular events (CVEs). A total of 227 patients who underwent HD at the Hangzhou Hospital of Traditional Chinese Medicine were enrolled in this prospective study between December 2017 and August 2018. Clinical data were collected, and the fluid status of patients was assessed using a body composition monitor. The patients were followed up until December 2020. The primary outcomes were CVEs. The association between fluid parameters and CVEs was analyzed using Cox proportional hazards models. The areas under the curve (AUCs) of receiver operating characteristic analysis and improvement in the global chi-squared value were used to compare the predictive values of fluid parameters for CVEs. During a median follow-up of 31 months, 66 CVEs were recorded. The patients with a higher absolute hydration index (OH) and a relative hydration index (OH/ECW%) exhibited an increased risk of developing CVEs. After adjusting for confounding factors, both OH [hazard ratio (HR) 1.279 per L, 95% confidence interval (CI) 1.047–1.562; p = 0.016] and OH/ECW% (HR 1.061 per %, 95% CI 1.017–1.108; p = 0.006) were independently associated with CVEs. The predictive ability of the absolute hydration index was superior to the relative hydration index based on AUC calculations for CVEs. Furthermore, a greater change in χ2 in predicting CVEs was noted for the absolute hydration index. Both absolute hydration index and relative hydration index were found to be independent predictors of CVEs in univariate and multivariate analyses. Furthermore, the absolute hydration index had a better additive predictive value than the relative hydration index in predicting CVEs. [ABSTRACT FROM AUTHOR]