Risk Model of Prolonged Intensive Care Unit Stay in Chinese Patients Undergoing Heart Valve Surgery

摘要: Background The aim of this study was to develop a preoperative risk prediction model and an scorecard for prolonged intensive care unit length stay (PrlICULOS) in adult patients undergoing heart valve surgery. Methods This is retrospective observational collected data on 3925 consecutive older than 18 years, who had undergone surgery between January 2000 December 2010. Data were randomly split into development dataset (n = 2401) validation (n = 1524). A multivariate logistic regression analysis undertaken using the identify independent factors PrlICULOS. Performance then assessed by observed expected rates PrlICULOS dataset. Model calibration discriminatory ability analysed Hosmer–Lemeshow goodness-of-fit statistic area under receiver operating characteristic (ROC) curve, respectively. Results There 491 that required (12.5%). Preoperative predictors are shown with odds ratio as follows: (1) age, 1.4; (2) chronic obstructive pulmonary disease (COPD), 1.8; (3) atrial fibrillation, (4) left bundle branch block, 2.7; (5) ejection fraction, (6) ventricle weight, 1.5; (7) New York Heart Association class III–IV, (8) critical state, 2.0; (9) perivalvular leakage, 6.4; (10) tricuspid replacement, 3.8; (11) concurrent CABG, 2.8; (12) other cardiac surgery, 1.8. not statistically significant both (P = 0.365 vs P = 0.310). ROC curve 0.717 0.700, Conclusion We developed validated local after can be used calculate patient-specific equivalent predicted at our centre future clinical practice.