National risk prediction model for perioperative mortality in non-cardiac surgery

Author:

Campbell D1ORCID,Boyle L2,Soakell-Ho M3,Hider P4,Wilson L5,Koea J6,Merry A F17,Frampton C8,Short T G17

Affiliation:

1. Department of Anaesthesia and Perioperative Medicine, Auckland City Hospital, Auckland, New Zealand

2. Orion Health, North Shore Hospital, Auckland, New Zealand

3. Pegasus Health, University of Otago, Christchurch, New Zealand

4. Department of Population Health, University of Otago, Christchurch, New Zealand

5. Department of Anaesthesia and Pain Management, Wellington Regional Hospital, Wellington, New Zealand

6. Upper Gastrointestinal Unit, Department of Surgery, North Shore Hospital, Auckland, New Zealand

7. Department of Anaesthesiology, University of Auckland, Auckland, New Zealand

8. Department of Biostatistics, University of Otago, Christchurch, New Zealand

Abstract

Abstract 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. Methods 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.

Funder

Precision Driven Health

Publisher

Oxford University Press (OUP)

Subject

Surgery

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