New models to predict survival of patients with difficult ventilator-weaning diagnosed with community-acquired pneumonia

Background High mortality is common in mechanically ventilated patients with severe community-acquired pneumonia (CAP). This study sought to create prediction models and determine factors for the pneumonia patients under difficult ventilator weaning in a respiratory care center. Methods In total, 353 CAP and hospital-acquired pneumonia (HAP) patients admitted to a respiratory care center (RCC) from January 1, 2015 to December 31, 2017 were included in this retrospective cohort study. Mortality and weaning risks factors were collected and analyzed for validating the prediction models. The study focuses primarily on CAP patients, with HAP data used to external validation. Results Among 270 CAP patients in model testing and validation, CURB-65 (Confusion, Uremia, Respiratory rate, Blood pressure, aged ≥65 years) and CUB-65 similarly predicted RCC survival (AUROCs ~65%). Three new RCC survival prediction models incorporated age ≥65, hypotension, BUN >19 mg/dl, ventilator type (replacing respiratory rate), and GCS ≤ 8 (replacing confusion), and either white blood cells (WBCs) or hemoglobin (Hb) were additionally included in model 1 or model 2. In CAP test samples, AUROCs with CAP test sample were 77.51% (model 1), 75.99% (model 2), and 77.97% (model 3). All three new models showed higher AUROCs than CURB-65, with significantly improved predictability in models 1 ( p = 0.0354) and 3 ( p = 0.0383). All three models demonstrated satisfactory performance (AUROC ≥ 80%) for predicting RCC survival in the CAP validation sample. Conclusions These new models more accurately predicted survival during RCC admission. Furthermore, they offer clinicians a better predictive tool for survival in CAP patients facing difficult ventilator weaning.