D Campbell1, L Boyle2, M Soakell-Ho3, P Hider4, L Wilson5, J Koea6, A F Merry1,7, C Frampton8, T G Short1,7. 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
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.
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.
Authors: Jiayi Gong; Alan Forbes Merry; Kebede A Beyene; Doug Campbell; Chris Frampton; Peter Jones; John McCall; Matthew Moore; Amy Hai Yan Chan Journal: BMJ Open Date: 2021-01-19 Impact factor: 2.692
Authors: Jason K Gurney; Melissa McLeod; James Stanley; Bridget Robson; Douglas Campbell; Elizabeth Dennett; Dick Ongley; Juliet Rumball-Smith; Diana Sarfati; Jonathan Koea Journal: ANZ J Surg Date: 2022-04-20 Impact factor: 2.025
Authors: Jason K Gurney; Melissa McLeod; James Stanley; Doug Campbell; Luke Boyle; Elizabeth Dennett; Sarah Jackson; Jonathan Koea; Dick Ongley; Diana Sarfati Journal: BMJ Open Date: 2020-09-24 Impact factor: 2.692