Key result
The POSPOM score showed strong discrimination for predicting in-hospital mortality with a C-statistic of 0.86, but demonstrated poor calibration by overestimating mortality risk.
Why the study?
Standardized risk assessment tools can identify patients at higher risk for postoperative complications and death, prompting validation of POSPOM for in-hospital mortality and postoperative complications in non-cardiac surgery patients.
Cohort (n=2,490)
Yes
The POSPOM score demonstrated strong discrimination but poor calibration for predicting in-hospital mortality in Dutch non-cardiac surgery patients, systematically overestimating risk.
Overestimation by POSPOM warrants caution in preoperative risk assessment; leaves open whether recalibration improves utility in similar cohorts.
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.
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Stolze et al. (2022) conducted a cohort in Non-cardiac surgery (n=2,490). PreOperative Score to predict Post-Operative Mortality (POSPOM) vs. Observed outcomes was evaluated on In-hospital mortality (C-statistic 0.86, 95% CI 0.78-0.93). The POSPOM score showed strong discrimination for predicting in-hospital mortality with a C-statistic of 0.86, but demonstrated poor calibration by overestimating mortality risk.
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