Development and validation of a predictive model for hospital mortality in patients with community-acquired pneumonia admitted to the intensive care unit.

ObjectiveThis retrospective cohort study aimed to develop and validate a nomogram for predicting in-hospital mortality among patients with community-acquired pneumonia admitted to the intensive care unit.MethodsData of patients meeting the inclusion criteria were extracted from the Medical Information Mart for Intensive Care-IV database, and the patients were randomly allocated into training (n = 3798, 70%) and validation (n = 1629, 30%) cohorts. First-day intensive care unit admission parameters were averaged. Least Absolute Shrinkage and Selection Operator regression and multivariate logistic regression analyses were used to identify mortality risk factors in the training cohort, followed by nomogram construction. Model performance was evaluated based on discrimination (area under the curve), calibration (Hosmer-Lemeshow test and bootstrap resampling), and clinical utility (decision curve analysis). Data from emergency intensive care unit were used to perform external validation of the value of the model.ResultsIn total, 5427 patients were included. Age, red cell distribution width, Sequential Organ Failure Assessment, Acute Physiology Score-III, blood urea nitrogen-to-serum creatinine ratio, anion gap, osmolarity, and sepsis were identified as independent risk factors for hospital mortality. The nomogram demonstrated superior discrimination compared with Sequential Organ Failure Assessment and Acute Physiology Score-III in the validation (area under the curve: 0.772 vs. 0.685-0.724) and training (area under the curve: 0.787 vs. 0.708-0.740;