Two-stage prediction model for postoperative delirium in patients in the intensive care unit after cardiac surgery

Abstract

Abstract OBJECTIVES Postoperative delirium is a common severe complication in patients in the intensive care unit after cardiac surgery. We developed a two-stage prediction model and quantified the risk of developing postoperative delirium to assist in early prevention before and after surgery. METHODS We conducted a prospective cohort study and consecutively recruited adult patients after cardiac surgery. The Confusion Assessment Method for patients in the intensive care unit was used to diagnose delirium 5 days postoperatively. The stage I model was constructed using patient demographics, health conditions and laboratory results obtained preoperatively, whereas the stage II model was built on both pre- and postoperative predictors. The model was validated internally using the bootstrap method and externally using data from an external cohort. RESULTS The two-stage model was developed with 654 patients and was externally validated with 214 patients undergoing cardiac surgery. The stage I model contained 6 predictors, whereas the stage II model included 10 predictors. The stage I model had an area under the receiver operating characteristic curve of 0.76 (95% confidence interval: 0.68–0.81), and the stage II model’s area under the receiver operating characteristic curve increased to 0.85 [95% confidence interval (CI): 0.81–0.89]. The external validation resulted in an area under the curve of 0.76 (95% CI: 0.67–0.86) for the stage I model and 0.78 (95% CI: 0.69–0.86) for the stage II model. CONCLUSIONS The two-stage model assisted medical staff in identifying patients at high risk for postoperative delirium before and 24 h after cardiac surgery. This model showed good discriminative power and predictive accuracy and can be easily accessed in clinical settings. Trial registration The study was registered with the US National Institutes of Health ClinicalTrials.gov (NCT03704324; registered 11 October 2018).