naa a22 4500 510743099 CHVBK 20180411083035.0 cr unu---uuuuu 180411e20130901xx s 000 0 eng 10.1007/s12630-013-9988-5 doi (NATIONALLICENCE)springer-10.1007/s12630-013-9988-5 The Revised Cardiac Risk Index in the new millennium: a single-centre prospective cohort re-evaluation of the original variables in 9,519 consecutive elective surgical patients [Elektronische Daten] [Christopher Davis, Gordon Tait, Jo Carroll, Duminda Wijeysundera, W. Beattie] L'indice de risque cardiaque modifié dans le nouveau millénaire: une réévaluation prospective et unicentrique de cohorte des variables originales chez 9519 patients consécutifs devant subir une chirurgie non urgente Purpose: Cardiac complications following non-cardiac surgery are major causes of morbidity and mortality. The Revised Cardiac Risk Index (RCRI) has become a standard for predicting post-surgical cardiac complications. This study re-examined the original six risk factors to confirm their validity in a large modern prospective database. Methods: Using the definitions in the original risk index, this study included 9,519 patients aged≥50 undergoing elective non-cardiac surgery with an expected length of stay≥two days at two major tertiary-care teaching hospitals. The validity of the original predictors was tested in this population using binomial logistic regression modelling, area under the receiver operator curve (ROC) analysis, and the net reclassification index. Results: Rates of major cardiac complications with 0, 1, 2,≥3 of the predictors were 0.5%, 2.6%, 7.2%, and 14.4%, respectively, in our patient cohort compared with 0.4%, 1.1%, 4.6%, and 9.7%, respectively, in the original cohort. Similar to the original report, binary logistic regression analysis showed that both preoperative treatment with insulin (odds ratio [OR] 1.4; 95% confidence interval [CI] 0.7 to 2.6) and preoperative creatinine>176.8mmol·L−1 (OR 1.7; 95% CI 0.8 to 3.6) did not improve the predictive ability of the index. Analysis of the remaining four factors resulted in an area under the curve (AUC) identical to that seen for the reconstructed six-factor RCRI (AUC=0.79). We found that a glomerular filtration rate (GFR)<30mL·min−1 was a better predictor of major cardiac complications (OR 2.2; 95% CI 1.2 to 4.3) than creatinine>176.8mmol·L−1. The receiver operating characteristic analysis of this resultant 5-Factor model resulted in an AUC of 0.79, with 0, 1, 2,≥3 of the predictors representing 0.5%, 2.9%, 7.4%, and 17.0% risk, respectively, among our patient cohort. Conclusion: Compared with the RCRI, a simplified 5-Factor model using a high-risk type of surgery, a history of ischemic heart disease, congestive heart failure, cerebrovascular disease, and a preoperative GFR<30mL·min−1 results in superior prediction of major cardiac complications following elective non-cardiac surgery. Canadian Anesthesiologists' Society, 2013 Davis Christopher Department of Anesthesia, University of Toronto and the Peter Munk Cardiac Centre, Toronto, ON, Canada aut Tait Gordon Department of Anesthesia and Pain Management, University Health Network, 200 Elizabeth Street, M5G 2C4, Toronto, ON, Canada aut Carroll Jo Department of Anesthesia and Pain Management, University Health Network, 200 Elizabeth Street, M5G 2C4, Toronto, ON, Canada aut Wijeysundera Duminda Department of Anesthesia and Pain Management, University Health Network, 200 Elizabeth Street, M5G 2C4, Toronto, ON, Canada aut Beattie W. Department of Anesthesia and Pain Management, University Health Network, 200 Elizabeth Street, M5G 2C4, Toronto, ON, Canada aut Canadian Journal of Anesthesia/Journal canadien d'anesthésie Springer US; http://www.springer-ny.com 60/9(2013-09-01), 855-863 0832-610X 60:9<855 2013 60 12630 https://doi.org/10.1007/s12630-013-9988-5 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s12630-013-9988-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Davis Christopher Department of Anesthesia, University of Toronto and the Peter Munk Cardiac Centre, Toronto, ON, Canada aut NATIONALLICENCE 700 1- Tait Gordon Department of Anesthesia and Pain Management, University Health Network, 200 Elizabeth Street, M5G 2C4, Toronto, ON, Canada aut NATIONALLICENCE 700 1- Carroll Jo Department of Anesthesia and Pain Management, University Health Network, 200 Elizabeth Street, M5G 2C4, Toronto, ON, Canada aut NATIONALLICENCE 700 1- Wijeysundera Duminda Department of Anesthesia and Pain Management, University Health Network, 200 Elizabeth Street, M5G 2C4, Toronto, ON, Canada aut NATIONALLICENCE 700 1- Beattie W. Department of Anesthesia and Pain Management, University Health Network, 200 Elizabeth Street, M5G 2C4, Toronto, ON, Canada aut NATIONALLICENCE 773 0- Canadian Journal of Anesthesia/Journal canadien d'anesthésie Springer US; http://www.springer-ny.com 60/9(2013-09-01), 855-863 0832-610X 60:9<855 2013 60 12630 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer