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National risk prediction model for perioperative mortality in non‐cardiac surgery.

Published: 6th August 2019

Authors: D. Campbell, L. Boyle, M. Soakell‐Ho, P. Hider, L. Wilson, J. Koea et al.

Background

Many multivariable models to calculate mortality risk after surgery are limited by insufficient sample size at development or by application to cohorts distinct from derivation populations. The aims of this study were to validate the Surgical Outcome Risk Tool (SORT) for a New Zealand population and to develop an extended NZRISK model to calculate 1‐month, 1‐year and 2‐year mortality after non‐cardiac surgery.

Method

Data from the New Zealand National Minimum Data Set for patients having surgery between January 2013 and December 2014 were used to validate SORT. A random 75 per cent split of the data was used to develop the NZRISK model, which was validated in the other 25 per cent of the data set.

Results

External validation of SORT in the 360 140 patients who underwent surgery in the study period showed good discrimination (area under the receiver operating characteristic curve (AUROC) value of 0·906) but poor calibration (McFadden's pseudo‐R2 0·137, calibration slope 5·32), indicating it was invalid in this national surgical population. Internal validation of the NZRISK model, which incorporates sex and ethnicity in addition to the variables used in SORT for 1‐month, 1‐year and 2‐year outcomes, demonstrated excellent discrimination with AUROC values of 0·921, 0·904 and 0·895 respectively, and excellent calibration (McFadden's pseudo‐R2 0·275, 0·308 and 0·312 respectively). Calibration slopes were 1·12, 1·02 and 1·02 respectively.

Conclusion

The SORT performed poorly in this national population. However, inclusion of sex and ethnicity in the NZRISK model improved performance. Calculation of mortality risk beyond 30 days after surgery adds to the utility of this tool for shared decision‐making.

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