Short-term risk prediction after major lower limb amputation: PERCEIVE study

Jolene Moore, Brenig L. Gwilym* (Corresponding Author), 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, Vascular and Endothelial Research Network (VERN) , PERCEIVE Study Group

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Background
The 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.

Methods
The 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.

Results
Some 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).

Conclusion
Clinicians 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.
Original languageEnglish
Pages (from-to)1300-1311
Number of pages13
JournalBritish Journal of Surgery
Volume109
Issue number12
Early online date6 Sept 2022
DOIs
Publication statusPublished - Dec 2022

Bibliographical note

Funding
The PERCEIVE study was awarded funding by the Research for Patient and Public Benefit (RfPPB) programme, Health and Care Research Wales (RfPPB-19-1642).

Data Availability Statement

Supplementary material is available at BJS online.

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