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. 2022 Mar 3;22(1):58.
doi: 10.1186/s12871-022-01564-1.

Validation of the PreOperative Score to predict Post-Operative Mortality (POSPOM) in Dutch non-cardiac surgery patients

Annick Stolze  1 , Ewoudt M W van de Garde  2 , Linda M Posthuma  3 , Markus W Hollmann  3 , Dianne de Korte-de Boer  4 , Valérie M Smit-Fun  4 , Wolfgang F F A Buhre  4 , Christa Boer  5 , Peter G Noordzij  6 ; TRACE Study investigators
Collaborators, Affiliations

Validation of the PreOperative Score to predict Post-Operative Mortality (POSPOM) in Dutch non-cardiac surgery patients

Annick Stolze et al. BMC Anesthesiol. .

Abstract

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.

Keywords: Calibration; Complications; Discrimination; In-hospital mortality; Outcome; Peri-operative; Risk assessment; Validation.

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Conflict of interest statement

MWH reports grants from ZonMW & Zorgverzekeraars Nederland, grants from Dutch Society of Anesthesiology (NvA), grants from European Society of Anesthesiology and Intensive Care (ESAIC), during the conduct of the study. He is executive section editor for Pharmacology for Anesthesia & Analgesia, section editor for Anesthesiology of the Journal of Clinical Medicine, received grants, honoraria for lectures and is advisory board member for Eurocept BV, received grants and honoraria for lectures from BBraun, received grants and honoraria for lectures from Edwards and received grants and honoraria for lectures from Behring, outside the submitted work. WFFAB reports grants from ZonMW & Zorgverzekeraars Nederland and grants from ESAIC during the conduct of the study. He has received funding from the European Commission (EU-Horizon 2020) and InterReg EU outside the presented study. His department has received funding from Medtronic and WFFAB is member of an advice committee of Medtronic. All honorarium is directed to the department and not to him as a person. All other authors declare no conflict of interests.

Figures

Fig. 1
Fig. 1
Distribution of patients with mortality among POSPOM scores. No deaths were observed below a POSPOM score of 24 points and above a POSPOM score of 36 points. Abbreviations: POSPOM PreOperative Score to predict PostOperative Mortality
Fig. 2
Fig. 2
Distribution of patients with complications among POSPOM scores. Complications are classified according to the Clavien-Dindo classification of surgical complications. Abbreviations: POSPOM PreOperative Score to predict PostOperative Mortality, CD Clavien-Dindo
Fig. 3
Fig. 3
ROC curve: predicted versus observed in-hospital mortality for POSPOM. ROC curve with a corresponding C-statistic of 0.86 (95% CI, 0.78–0.93), which implies strong discriminating power. Abbreviations: ROC Receiver Operating Characteristics, POSPOM  PreOperative Score to predict PostOperative Mortality
Fig. 4
Fig. 4
C-statistic values for different outcomes. Complications are classified according to the Clavien-Dindo classification of surgical complications. Abbreviations: CD Clavien-Dindo
Fig. 5
Fig. 5
Calibration plot for in-hospital mortality. The slope of the fitted line is 0.1704 and the y-axis intercept is 0.00 (95% CI, − 0.001395-0.001345)
See this image and copyright information in PMC

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