BMC anesthesiology · 2022
Validation of the PreOperative Score to predict Post-Operative Mortality (POSPOM) in Dutch non-cardiac surgery patients.
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Stolze Annick, van de Garde Ewoudt M W, Posthuma Linda M, Hollmann Markus W, de Korte-de Boer Dianne, Smit-Fun Valérie M, Buhre Wolfgang F F A, Boer Christa, Noordzij Peter G, TRACE Study investigators
Аннотация
BACKGROUND: Standardized risk assessment tools can be used to identify patients at higher risk for postoperative complications and death. In this study, we validate the PreOperative Score to predict Post-Operative Mortality (POSPOM) for in-hospital mortality in a large cohort of non-cardiac surgery patients. In addition, the performance of POSPOM to predict postoperative complications was studied.
METHODS: Data from the control cohort of the TRACE (routine posTsuRgical Anesthesia visit to improve patient outComE) study was analysed. POSPOM scores for each patient were calculated post-hoc. Observed in-hospital mortality was compared with predicted mortality according to POSPOM. Discrimination was assessed by receiver operating characteristic curves with C-statistics for in-hospital mortality and postoperative complications. To describe the performance of POSPOM sensitivity, specificity, negative predictive values, and positive predictive values were calculated. For in-hospital mortality, calibration was assessed by a calibration plot.
RESULTS: In 2490 patients, the observed in-hospital mortality was 0.5%, compared to 1.3% as predicted by POSPOM. 27.1% of patients had at least one postoperative complication of which 22.4% had a major complication. For in-hospital mortality, POSPOM showed strong discrimination with a C-statistic of 0.86 (95% CI, 0.78-0.93). For the prediction of complications, the discrimination was poor to fair depending on the severity of the complication. The calibration plot showed poor calibration of POSPOM with an overestimation of in-hospital mortality.
CONCLUSION: Despite the strong discriminatory performance, POSPOM showed poor calibration with an overestimation of in-hospital mortality. Performance of POSPOM for the prediction of any postoperative complication was poor but improved according to severity.
METHODS: Data from the control cohort of the TRACE (routine posTsuRgical Anesthesia visit to improve patient outComE) study was analysed. POSPOM scores for each patient were calculated post-hoc. Observed in-hospital mortality was compared with predicted mortality according to POSPOM. Discrimination was assessed by receiver operating characteristic curves with C-statistics for in-hospital mortality and postoperative complications. To describe the performance of POSPOM sensitivity, specificity, negative predictive values, and positive predictive values were calculated. For in-hospital mortality, calibration was assessed by a calibration plot.
RESULTS: In 2490 patients, the observed in-hospital mortality was 0.5%, compared to 1.3% as predicted by POSPOM. 27.1% of patients had at least one postoperative complication of which 22.4% had a major complication. For in-hospital mortality, POSPOM showed strong discrimination with a C-statistic of 0.86 (95% CI, 0.78-0.93). For the prediction of complications, the discrimination was poor to fair depending on the severity of the complication. The calibration plot showed poor calibration of POSPOM with an overestimation of in-hospital mortality.
CONCLUSION: Despite the strong discriminatory performance, POSPOM showed poor calibration with an overestimation of in-hospital mortality. Performance of POSPOM for the prediction of any postoperative complication was poor but improved according to severity.