A novel prognostic model for predicting the mortality risk of patients with sepsis-related acute respiratory failure:...

Area of Science:

• Critical Care Medicine
• Pulmonology
• Infectious Diseases

Background:

• Acute respiratory failure significantly increases short-term mortality in sepsis patients.
• Accurate prediction of mortality risk is crucial for managing sepsis patients with acute respiratory failure.

Purpose of the Study:

• To develop and validate a novel predictive model for hospital mortality in sepsis patients experiencing acute respiratory failure.
• To identify independent risk factors associated with mortality in this patient cohort.

Main Methods:

• A matched cohort of adult sepsis patients with acute respiratory failure was established using the MIMIC-IV database.
• Multivariate COX regression analysis was employed to identify risk factors and develop a nomogram.
• The predictive ability of the nomogram was assessed using the area under the receiver operating characteristic (ROC) curve.

Main Results:

• The study included 663 sepsis patients with acute respiratory failure.
• Independent risk factors for mortality included systolic blood pressure, neutrophil percentage, white blood cell count, mechanical ventilation, low partial pressure of oxygen, abdominal cavity infection, *Klebsiella pneumoniae* and *Acinetobacter baumannii* infections, and immunosuppressive diseases.
• The nomogram achieved an area under the ROC curve of 0.880, demonstrating superior discrimination compared to the simplified acute physiology score II (0.656).

Conclusions:

• The developed nomogram demonstrates good performance in predicting mortality risk for patients with sepsis-related acute respiratory failure.
• This model can effectively evaluate the short-term prognosis of critically ill patients with sepsis and acute respiratory failure.