Nutrients · 8 authors, 4 centres
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This retrospective study of 60 elderly hemodialysis patients developed two regression equations (EHSI-M and EHSI-S) using easily accessible nutritional and anthropometric parameters to predict moderate and severe sarcopenia as defined by EWGSOP2 criteria, achieving AUCs of 0.80 and 0.866, respectively. The main limitation is the need for external validation in different populations and the use of bioimpedance instead of gold-standard imaging for muscle mass assessment.
Sarcopenia, defined by EWGSOP2 as loss of muscle mass and strength, is common in elderly hemodialysis patients but its diagnosis can be technically challenging. Malnutrition is closely linked to sarcopenia in this population. Methods: A retrospective study of 60 patients aged 75-95 years on chronic hemodialysis was conducted. Anthropometric, analytical, and nutritional variables were collected, including the Malnutrition-Inflammation Score (MIS). EWGSOP2 criteria for sarcopenia (grip strength, appendicular skeletal muscle mass via bioimpedance, and gait speed) were applied. Binomial logistic regressions were used to develop indices predicting moderate (EHSI-M) and severe (EHSI-S) sarcopenia. Key Results: Severe sarcopenia correlated with malnutrition parameters. The EHSI-M, combining gender, age, serum albumin, phosphate, and cholesterol, predicted moderate sarcopenia with an AUC of 0.80 (specificity 87%, sensitivity 61%). The EHSI-S, combining gender, age, MIS, cholesterol, lymphocytes, and subscapular fold, predicted severe sarcopenia with an AUC of 0.866 (specificity 94%, sensitivity 76%). Limitations: The study is retrospective with a small sample size (n=60) from a single country, uses bioimpedance instead of gold-standard imaging for muscle mass, and requires external validation in diverse populations. Implications: The EHSI may provide a simple, low-cost tool for identifying sarcopenia in elderly hemodialysis patients, particularly in low-resource settings, potentially aiding in nutritional and clinical management decisions.
