Predictive nomogram for in-hospital mortality among older patients with intra-abdominal sepsis incorporating skeletal muscle mass

Abstract

Background: Studies on prognostic factors for older patients with intra-abdominal sepsis are scarce, and the association between skeletal muscle mass and prognosis among such patients remains unclear. Aims: To develop a nomogram to predict in-hospital mortality among older patients with intra-abdominal sepsis. Methods: Older patients with intra-abdominal sepsis were prospectively recruited. Their demographics, clinical features, laboratory results, abdominal computed tomography-derived muscle mass, and in-hospital mortality were recorded. The predictors of mortality were selected via least absolute shrinkage and selection operator and multivariable logistic regression analyses, and a nomogram was developed. The nomogram was assessed and compared with Sequential Organ Failure Assessment score, Acute Physiology and Chronic Health Evaluation II score, and Simplified Acute Physiology Score II. Results: In total, 464 patients were included, of whom 104 (22.4%) died. Six independent risk factors (skeletal muscle index, cognitive impairment, frailty, heart rate, red blood cell distribution width, and blood urea nitrogen) were incorporated into the nomogram. The Hosmer–Lemeshow goodness-of-fit test and calibration plot revealed a good consistency between the predicted and observed probabilities. The area under the receiver operating characteristic curve was 0.875 (95% confidence interval = 0.838–0.912), which was significantly higher than those of commonly used scoring systems. The decision curve analysis indicated the nomogram had good predictive performance. Discussion: Our nomogram, which is predictive of in-hospital mortality among older patients with intra-abdominal sepsis, incorporates muscle mass, a factor that warrants consideration by clinicians. The model has a high prognostic ability and might be applied in clinical practice after external validation.