Decreasing skeletal muscle as a risk factor for mortality in elderly patients with sepsis: a retrospective cohort study

Background: Older patients account for the majority of patients with sepsis. The objective of this study was to determine if decreased skeletal muscle mass is associated with outcomes in elderly patients with sepsis. Methods: Patients (60 years and older) who were admitted to a tertiary medical center intensive care unit with a primary diagnosis of sepsis between January 2012 and February 2016 were included. Patients who had not undergone abdominal computed tomography on the day of admission, had cardiopulmonary arrest on arrival, or had iliopsoas abscess were excluded from the analyses. Cross-sectional muscle area at the 3rd lumber vertebra was quantified, and the relation to in-hospital mortality was analyzed. Multivariable logistic regression analysis that included sex and APACHE II score as explanatory variables was performed. The optimal cutoff value to define decreased muscle mass (sarcopenia) was calculated using receiver operating characteristic curve analysis, and the odds ratio for in-hospital mortality was determined. Results: There were 150 elderly patients with sepsis (median age, 75 years) enrolled; in-hospital mortality and median APACHE II score were 38.7 and 24%, respectively. The skeletal muscle area of deceased patients was significantly lower than that of the survival group (P < 0.001). The multivariable logistic regression analysis demonstrated that decreased muscle mass was significantly associated with increased mortality (odds ratio = 0.94, 95% confidence interval = 0.90 to 0.97, P < 0.001). The optimal cutoff value of skeletal muscle area to predict inhospital mortality was 45.2 cm(2) for men and 39.0 cm(2) for women. With these cutoff values, the adjusted odds ratio for decreased muscle area was 3.27 (95% CI, 1.61 to 6.63, P = 0.001). Conclusions: Less skeletal muscle mass is associated with higher in-hospital mortality in elderly patients with sepsis. The results of this study suggest that identifying patients with low muscularity contributes to better stratification in this population.