Linking preoperative and early intensive care unit data for prolonged intubation prediction

Abstract

ObjectivesProlonged intubation (PI) is a frequently encountered severe complication among patients following cardiac surgery (CS). Solely concentrating on preoperative data, devoid of sufficient consideration for the ongoing impact of surgical, anesthetic, and cardiopulmonary bypass procedures on subsequent respiratory system function, could potentially compromise the predictive accuracy of disease prognosis. In response to this challenge, we formulated and externally validated an intelligible prediction model tailored for CS patients, leveraging both preoperative information and early intensive care unit (ICU) data to facilitate early prophylaxis for PI.MethodsWe conducted a retrospective cohort study, analyzing adult patients who underwent CS and utilizing data from two publicly available ICU databases, namely, the Medical Information Mart for Intensive Care and the eICU Collaborative Research Database. PI was defined as necessitating intubation for over 24 h. The predictive model was constructed using multivariable logistic regression. External validation of the model's predictive performance was conducted, and the findings were elucidated through visualization techniques.ResultsThe incidence rates of PI in the training, testing, and external validation cohorts were 11.8%, 12.1%, and 17.5%, respectively. We identified 11 predictive factors associated with PI following CS: plateau pressure [odds ratio (OR), 1.133; 95% confidence interval (CI), 1.111–1.157], lactate level (OR, 1.131; 95% CI, 1.067–1.2), Charlson Comorbidity Index (OR, 1.166; 95% CI, 1.115–1.219), Sequential Organ Failure Assessment score (OR, 1.096; 95% CI, 1.061–1.132), central venous pressure (OR, 1.052; 95% CI, 1.033–1.073), anion gap (OR, 1.075; 95% CI, 1.043–1.107), positive end-expiratory pressure (OR, 1.087; 95% CI, 1.047–1.129), vasopressor usage (OR, 1.521; 95% CI, 1.23–1.879), Visual Analog Scale score (OR, 0.928; 95% CI, 0.893–0.964), pH value (OR, 0.757; 95% CI, 0.629–0.913), and blood urea nitrogen level (OR, 1.011; 95% CI, 1.003–1.02). The model exhibited an area under the receiver operating characteristic curve (AUROC) of 0.853 (95% CI, 0.840–0.865) in the training cohort, 0.867 (95% CI, 0.853–0.882) in the testing cohort, and 0.704 (95% CI, 0.679–0.727) in the external validation cohort.ConclusionsThrough multicenter internal and external validation, our model, which integrates early ICU data and preoperative information, exhibited outstanding discriminative capability. This integration allows for the accurate assessment of PI risk in the initial phases following CS, facilitating timely interventions to mitigate adverse outcomes.