Two newly developed models for predicting intraoperative cardiovascular events showed good discrimination (AUC 0.709 and 0.707) compared to ASA and RCRI, but lacked acceptable calibration.
Observational (n=58,458)
Do newly developed prognostic models better predict intraoperative cardiovascular events compared to RCRI and ASA classification in patients undergoing noncardiac surgery?
While new prognostic models offer better discrimination than RCRI and ASA classification for predicting intraoperative cardiovascular events, poor calibration limits their clinical utility.
Effect estimate: AUC 0.709 and 0.707
In Brief The objective of this study was to evaluate prognostic models for quality assurance purposes in predicting automatically detected intraoperative cardiovascular events (CVE) in 58,458 patients undergoing noncardiac surgery. To this end, we assessed the performance of two established models for risk assessment in anesthesia, the Revised Cardiac Risk Index (RCRI) and the ASA physical status classification. We then developed two new models. CVEs were detected from the database of an electronic anesthesia record-keeping system. Logistic regression was used to build a complex and a simple predictive model. Performance of the prognostic models was assessed using analysis of discrimination and calibration. In 5249 patients (17.8%) of the evaluation (n = 29,437) and 5031 patients (17.3%) of the validation cohorts (n = 29,021), a minimum of one CVE was detected. CVEs were associated with significantly more frequent hospital mortality (2.1% versus 1.0%; P < 0.01). The new models demonstrated good discriminative power, with an area under the receiver operating characteristic curve (AUC) of 0.709 and 0.707 respectively. Discrimination of the ASA classification (AUC 0.647) and the RCRI (AUC 0.620) were less. Neither the two new models nor ASA classification nor the RCRI showed acceptable calibration. ASA classification and the RCRI alone both proved unsuitable for the prediction of intraoperative CVEs. IMPLICATIONS: The objective of this study was to evaluate prognostic models for quality assurance purposes to predict the occurrence of automatically detected intraoperative cardiovascular events in 58,458 patients undergoing noncardiac surgery. Two newly developed models showed good discrimination but, because of reduced calibration, their clinical use is limited. The ASA physical status classification and the Revised Cardiac Risk Index are unsuitable for the prediction of intraoperative cardiovascular events.
hrig et al. (Mon,) conducted a observational in Noncardiac surgery (n=58,458). Two new predictive models vs. Revised Cardiac Risk Index (RCRI) and ASA physical status classification was evaluated on Automatically detected intraoperative cardiovascular events (CVE) (AUC 0.709 and 0.707). Two newly developed models for predicting intraoperative cardiovascular events showed good discrimination (AUC 0.709 and 0.707) compared to ASA and RCRI, but lacked acceptable calibration.