• Annick Stolze, van de GardeEwoudt M WEMWDepartment of Clinical Pharmacy, St. Antonius Hospital Nieuwegein, Nieuwegein, The Netherlands., Linda M Posthuma, Markus W Hollmann, de Korte-de BoerDianneDDepartment of Anesthesiology and Pain Medicine, Maastricht University Medical Centre+, Maastricht, The Netherlands., Valérie M Smit-Fun, BuhreWolfgang F F AWFFADepartment of Anesthesiology and Pain Medicine, Maastricht University Medical Centre+, Maastricht, The Netherlands., Christa Boer, Peter G Noordzij, and TRACE Study investigators.
• Department of Anesthesiology, Amsterdam University Medical Centre, VU University Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands. a.stolze@amsterdamumc.nl.
• BMC Anesthesiol. 2022 Mar 3; 22 (1): 58.

BackgroundStandardized 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.MethodsData 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.ResultsIn 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.ConclusionDespite 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.© 2022. The Author(s).

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