A novel prognostic model for predicting the mortality risk of patients with sepsis-related acute respiratory failure: a cohort study using the MIMIC-IV database

Acute respiratory failure increases short-term mortality in sepsis patients. Hence, in this study, we aimed to develop a novel model for predicting the risk of hospital mortality in sepsis patients with acute respiratory failure. From the Medical Information Mart for Intensive Care (MIMIC)-IV database, we developed a matched cohort of adult sepsis patients with acute respiratory failure. After applying a multivariate COX regression analysis, we developed a nomogram based on the identified risk factors of mortality. Further, we evaluated the ability of the nomogram in predicting individual hospital death by the area under a receiver operating characteristic (ROC) curve. A total of 663 sepsis patients with acute respiratory failure were included in this study. Systolic blood pressure, neutrophil percentage, white blood cells count, mechanical ventilation, partial pressure of oxygen &lt; 60 mmHg, abdominal cavity infection, <i>Klebsiella pneumoniae</i> and <i>Acinetobacter baumannii</i> infection, and immunosuppressive diseases were the independent risk factors of mortality in sepsis patients with acute respiratory failure. The area under the ROC curve of the nomogram was 0.880 (95% CI: 0.851–0.908), which provided significantly higher discrimination compared to that of the simplified acute physiology score II [0.656 (95% CI: 0.612–0.701)]. The model shows a good performance in predicting the mortality risk of patients with sepsis-related acute respiratory failure. Hence, this model can be used to evaluate the short-term prognosis of critically ill patients with sepsis and acute respiratory failure.