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. (3rd April 2022)

• Record Type: Journal Article
• Authors: Zhao, Lina; Yang, Jing; Zhou, Cong; Wang, Yunying; Liu, Tao
• Is Part Of: Current medical research and opinion. Volume 38:Number 4(2022)
• Page Start: 629
• Page End: 636
• Publication Date: 2022-04-03
• Subjects: Acute respiratory failure -- sepsis -- hospital mortality -- model; Clinical medicine -- Periodicals; Therapeutics -- Periodicals; 615.5
• DOI: 10.1080/03007995.2022.2038490
• Languages: English
• ISSNs: 0300-7995

Abstract

Abstract: Objectives: 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. Methods: 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. Results: 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 < 60 mmHg, abdominal cavity infection, Klebsiella pneumoniae and Acinetobacter baumannii 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)]. Conclusion: 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.