Objective  To explore independent risk factors for 30-day mortality in critical patients with pulmonary infection and sepsis, and build a prediction model. Methods  Patients diagnosed with pulmonary infection and sepsis in the MIMIC-Ⅲ database were analyzed. The CareVue database was the training cohort (n=934), and the Metavision database was the external validation cohort (n=687). A COX proportional hazards regression model was established to screen independent risk factors and draw a nomogram. We conducted internal cross-validation and external validation of the model. Using the receiver operator characteristic (ROC) curve, Calibration chart, and decision curve analysis, we detected the discrimination, calibration, and benefit of the model respectively, comparing with the SOFA scoring model. Results  Age, SOFA score, white blood cell count≤4×10⁹/L, neutrophilic granulocyte percentage (NEU%)>85%, platelet count (PLT)≤100×10⁹/L, PLT>300×10⁹/L, red cell distribution width >15%, blood urea nitrogen, and lactate dehydrogenase were independent risk factors. The areas under the ROC curve of the model were 0.747 (training cohort) and 0.708 (external validation cohort), respectively, which was superior to the SOFA scoring model in terms of discrimination, calibration, and benefit. Conclusion  The model established in this study can accurately and effectively predict the risk of the disease mortality, and provide a visual assessment method for early identification of high-risk patients.

Citation： YAO Miaoen, CHEN Ruilan. A prediction model for the 30-day mortality of the critical patients with pulmonary infection and sepsis. Chinese Journal of Respiratory and Critical Care Medicine, 2024, 23(6): 381-389. doi: 10.7507/1671-6205.202312066 Copy