title: Extubation outcome after a successful spontaneous breathing trial: A multicenter validation of a 3-factor prediction model.
abstract: The aim of the present study was to validate, and if necessary update, a predictive model previously developed using a classification and regression tree (CART) algorithm for predicting successful extubation (ES) using a new cohort. This prospective cohort study enrolled adults admitted to 10 intensive care units, who had successfully passed a spontaneous breathing trial (SBT) and were considered ready for extubation. After extubation, the patients were followed up for 48 h. The primary outcome measure was ES, defined as the ability to maintain spontaneous unassisted breathing for >48 h after extubation. The 3-factor CART model was applied to patients in this cohort. The predicted probability of ES for each patient in this validation cohort was calculated based on the original CART model using the Laplace correction method. The performance was assessed by discrimination and calibration. A decision curve analysis was used assess the clinical net benefit (NB). Extubation failure (EF) occurred in 90/530 patients (17%). Among the 90 patients, 72 (13.6%) were reintubated, while 18 patients remained on rescue noninvasive ventilation within 48 h after extubation. The original CART model showed high discrimination but only moderate calibration with predicted probabilities that were systematically lower than expected. The original CART model was updated, and the updated model preserved excellent discrimination (area under the receiver operating characteristic curve, 0.91; 95% confidence interval, 0.87 to 0.93), but exhibited near-perfect calibration (calibration slope, 1; intercept, 0). Between threshold probabilities of 50 and 80%, the NB of using this updated model is significantly improved compared with the current strategy. The updated CART model may be used to estimate the predicted probability of ES after a successful SBT for individual patients. Applying this model appears to produce a substantial clinical consequence with regard to potential reduction in unexpected EFs.
authors.affiliation: Medical Intensive Care Unit, Pingjin Hospital, Logistics College of The Chinese People's Armed Police Forces, Tianjin 300162, P.R. China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Coronary Care Unit, Tianjin Chest Hospital, Teaching Hospital of Tianjin Medical University, Tianjin 300051, P.R. China.
authors.forename: Y U
authors.initials: YU
authors.lastname: Mu
authors.affiliation: Medical Intensive Care Unit, Pingjin Hospital, Logistics College of The Chinese People's Armed Police Forces, Tianjin 300162, P.R. China.
authors.forename: Guo-Qiang
authors.initials: GQ
authors.lastname: Li
authors.affiliation: Surgical Intensive Care Unit, Pingjin Hospital, Logistics College of The Chinese People's Armed Police Forces, Tianjin 300162, P.R. China.
authors.forename: Xin
authors.initials: X
authors.lastname: Yu
authors.affiliation: General Intensive Care Unit, Tianjin Chest Hospital, Teaching Hospital of Tianjin Medical University, Tianjin 300051, P.R. China.
authors.forename: Pei-Jun
authors.initials: PJ
authors.lastname: Li
authors.affiliation: Coronary Care Unit, General Hospital of Chinese People's Armed Police Forces, Beijing 100039, P.R. China.
authors.forename: Zhi-Qi
authors.initials: ZQ
authors.lastname: Shen
authors.affiliation: General Intensive Care Unit, Xizang Corps Hospital, Teaching Hospital of Tibet University, Lhasa, Tibet 850000, P.R. China.
authors.forename: Hao-Xun
authors.initials: HX
authors.lastname: Wang
authors.affiliation: Medical Intensive Care Unit, Pingjin Hospital, Logistics College of The Chinese People's Armed Police Forces, Tianjin 300162, P.R. China.
authors.forename: Lu-Qing
authors.initials: LQ
authors.lastname: Wei
keywords: calibration; decision curve analysis; decision trees; endotracheal extubation; model updating