• WongD J NDJNUCL/UCLH Surgical Outcome Research Centre (SOuRCe), 3rd Floor, Maple Link Corridor, University College Hospital, 235 Euston Road, London NW1 2BU, UK.National Institute of Academic Anaesthesia Health Services Research Centre (NIAA HSRC), Royal , C M Oliver, and S R Moonesinghe.
• UCL/UCLH Surgical Outcome Research Centre (SOuRCe), 3rd Floor, Maple Link Corridor, University College Hospital, 235 Euston Road, London NW1 2BU, UK.
• Br J Anaesth. 2017 Jul 1; 119 (1): 95-105.

BackgroundThe Surgical Outcome Risk Tool (SORT) is a risk stratification instrument used to predict perioperative mortality. We wanted to evaluate and refine SORT for better prediction of the risk of postoperative morbidity.MethodsWe analysed prospectively collected data from a single-centre cohort of adult patients undergoing major elective surgery. The data set was split randomly into derivation and validation samples. We used logistic regression to construct a model in the derivation sample to predict postoperative morbidity as defined using the validated Postoperative Morbidity Survey (POMS) assessed at 1 week after surgery. Performance of this 'SORT-morbidity' model was then tested in the validation sample and compared against the Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (POSSUM).ResultsThe SORT-morbidity model was constructed using a derivation sample of 1056 patients and validated in a further 527 patients. SORT-morbidity was well calibrated in the validation sample, as assessed using calibration plots and the Hosmer-Lemeshow test (χ 2 =4.87, P =0.77). It showed acceptable discrimination by receiver operating characteristic curve analysis [area under the receiver operating characteristic curve (AUROC)=0.72, 95% confidence interval: 0.67-0.77]. This compared favourably with POSSUM (AUROC=0.66, 95% confidence interval: 0.60-0.71), whilst being simpler to use. Linear shrinkage factors were estimated, which allow the SORT-morbidity model to predict a range of alternative morbidity outcomes with greater accuracy, including low- and high-grade morbidity, and POMS at later time points.ConclusionsSORT-morbidity can be used before surgery, with clinical judgement, to predict postoperative morbidity risk in major elective surgery.© The Author 2017. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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