Risk factors and predictive modeling in a US population with sarcopenia: a propensity score cohort study - Yao Sun; Shuguang Yang; Zengli Xiao; Youzhong An; Huiying Zhao (Scientific Reports)
Abstract Sarcopenia, characterized by loss of muscle mass and strength, particularly affects older adults and is linked to increased morbidity and mortality. The study aimed to investigate the relationship between biomarkers, including hemoglobin (Hb), lactate dehydrogenase (LDH), and Systemic Immune-Inflammation Index (SII), and sarcopenia in the US population. Utilizing NHANES data from 2003 to 2018, the study analyzed 5,615 participants, categorizing them based on quartiles of Hb, SII, and LDH levels. It employed logistic regression models to assess the relationship between these biomarkers and sarcopenia risk, adjusting for various confounders. High levels of LDH, Hb and SII were significantly associated with sarcopenia, with higher risk in the highest quartile. The AUC for all indicators in predicting sarcopenia was 0.925 (sensitivity 0.925; specificity 0.743). The study concludes that elevated Hb, LDH, and SII levels are significant biomarkers associated with sarcopenia, emphasizing the role of inflammation in its development and the potential for these markers in early detection and intervention.