• Brenig L Gwilym, Philip Pallmann, Cherry-Ann Waldron, Emma Thomas-Jones, Sarah Milosevic, Lucy Brookes-Howell, Debbie Harris, Ian Massey, Jo Burton, Phillippa Stewart, Katie Samuel, Sian Jones, David Cox, Annie Clothier, Adrian Edwards, Christopher P Twine, David C Bosanquet, and Vascular and Endovascular Research Network (VERN) and PERCEIVE study group.
• South East Wales Vascular Network, Aneurin Bevan University Health Board, Royal Gwent Hospital, Newport, UK.
• Br J Surg. 2022 Nov 22; 109 (12): 130013111300-1311.

BackgroundThe accuracy with which healthcare professionals (HCPs) and risk prediction tools predict outcomes after major lower limb amputation (MLLA) is uncertain. The aim of this study was to evaluate the accuracy of predicting short-term (30 days after MLLA) mortality, morbidity, and revisional surgery.MethodsThe PERCEIVE (PrEdiction of Risk and Communication of outcomE following major lower limb amputation: a collaboratIVE) study was launched on 1 October 2020. It was an international multicentre study, including adults undergoing MLLA for complications of peripheral arterial disease and/or diabetes. Preoperative predictions of 30-day mortality, morbidity, and MLLA revision by surgeons and anaesthetists were recorded. Probabilities from relevant risk prediction tools were calculated. Evaluation of accuracy included measures of discrimination, calibration, and overall performance.ResultsSome 537 patients were included. HCPs had acceptable discrimination in predicting mortality (931 predictions; C-statistic 0.758) and MLLA revision (565 predictions; C-statistic 0.756), but were poor at predicting morbidity (980 predictions; C-statistic 0.616). They overpredicted the risk of all outcomes. All except three risk prediction tools had worse discrimination than HCPs for predicting mortality (C-statistics 0.789, 0.774, and 0.773); two of these significantly overestimated the risk compared with HCPs. SORT version 2 (the only tool incorporating HCP predictions) demonstrated better calibration and overall performance (Brier score 0.082) than HCPs. Tools predicting morbidity and MLLA revision had poor discrimination (C-statistics 0.520 and 0.679).ConclusionClinicians predicted mortality and MLLA revision well, but predicted morbidity poorly. They overestimated the risk of mortality, morbidity, and MLLA revision. Most short-term risk prediction tools had poorer discrimination or calibration than HCPs. The best method of predicting mortality was a statistical tool that incorporated HCP estimation.© The Author(s) 2022. Published by Oxford University Press on behalf of BJS Society Ltd. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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