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Gwilym BL, Pallmann P, Waldron CA, Thomas-Jones E, Milosevic S, Brookes-Howell L, Harris D, Massey I, Burton J, Stewart P, Samuel K, Jones S, Cox D, Clothier A, Edwards A, Twine CP, Bosanquet DC, Benson R, Birmpili P, Blair R, Bosanquet DC, Dattani N, Dovell G, Forsythe R, Gwilym BL, Hitchman L, Machin M, Nandhra S, Onida S, Preece R, Saratzis A, Shalhoub J, Singh A, Forget P, Gannon M, Celnik A, Duguid M, Campbell A, Duncan K, Renwick B, Moore J, Maresch M, Kamal D, Kabis M, Hatem M, Juszczak M, Dattani N, Travers H, Shalan A, Elsabbagh M, Rocha-Neves J, Pereira-Neves A, Teixeira J, Lyons O, Lim E, Hamdulay K, Makar R, Zaki S, Francis CT, Azer A, Ghatwary-Tantawy T, Elsayed K, Mittapalli D, Melvin R, Barakat H, Taylor J, Veal S, Hamid HKS, Baili E, Kastrisios G, Maltezos C, Maltezos K, Anastasiadou C, Pachi A, Skotsimara A, Saratzis A, Vijaynagar B, Lau S, Velineni R, Bright E, Montague-Johnstone E, Stewart K, King W, Karkos C, Mitka M, Papadimitriou C, Smith G, Chan E, Shalhoub J, Machin M, Agbeko AE, Amoako J, Vijay A, Roditis K, Papaioannou V, Antoniou A, Tsiantoula P, Bessias N, Papas T, Dovell G, Goodchild F, Nandhra S, Rammell J, Dawkins C, Lapolla P, Sapienza P, Brachini G, Mingoli A, Hussey K, Meldrum A, Dearie L, Nair M, Duncan A, Webb B, Klimach S, Hardy T, Guest F, Hopkins L, Contractor U, Clothier A, McBride O, Hallatt M, Forsythe R, Pang D, Tan LE, Altaf N, Wong J, Thurston B, Ash O, Popplewell M, Grewal A, Jones S, Wardle B, Twine C, Ambler G, Condie N, Lam K, Heigberg-Gibbons F, Saha P, Hayes T, Patel S, Black S, Musajee M, Choudhry A, Hammond E, Costanza M, Shaw P, Feghali A, Chawla A, Surowiec S, Encalada RZ, Benson R, Cadwallader C, Clayton P, Van Herzeele I, Geenens M, Vermeir L, Moreels N, Geers S, Jawien A, Arentewicz T, Kontopodis N, Lioudaki S, Tavlas E, Nyktari V, Oberhuber A, Ibrahim A, Neu J, Nierhoff T, Moulakakis K, Kakkos S, Nikolakopoulos K, Papadoulas S, D'Oria M, Lepidi S, Lowry D, Ooi S, Patterson B, Williams S, Elrefaey GH, Gaba KA, Williams GF, Rodriguez DU, Khashram M, Gormley S, Hart O, Suthers E, French S. Short-term risk prediction after major lower limb amputation: PERCEIVE study. Br J Surg 2022; 109:1300-1311. [PMID: 36065602 DOI: 10.1093/bjs/znac309] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 05/06/2022] [Accepted: 07/31/2022] [Indexed: 01/22/2023]
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.
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Affiliation(s)
- Brenig L Gwilym
- South East Wales Vascular Network, Aneurin Bevan University Health Board, Royal Gwent Hospital, Newport, UK
| | | | | | | | | | | | - Debbie Harris
- Centre for Trials Research, Cardiff University, Cardiff, UK
| | - Ian Massey
- Artificial Limb and Appliance Centre, Rookwood Hospital, Cardiff and Vale University Health Board, Cardiff, UK
| | - Jo Burton
- Artificial Limb and Appliance Centre, Rookwood Hospital, Cardiff and Vale University Health Board, Cardiff, UK
| | - Phillippa Stewart
- Artificial Limb and Appliance Centre, Rookwood Hospital, Cardiff and Vale University Health Board, Cardiff, UK
| | - Katie Samuel
- Department of Anaesthesia, North Bristol NHS Trust, Bristol, UK
| | - Sian Jones
- c/o INVOLVE Health and Care Research Wales, Cardiff, UK
| | - David Cox
- c/o INVOLVE Health and Care Research Wales, Cardiff, UK
| | - Annie Clothier
- South East Wales Vascular Network, Aneurin Bevan University Health Board, Royal Gwent Hospital, Newport, UK
| | - Adrian Edwards
- Division of Population Medicine, Cardiff University, Cardiff, UK
| | - Christopher P Twine
- Bristol, Bath and Weston Vascular Network, North Bristol NHS Trust, Southmead Hospital, Bristol, UK
| | - David C Bosanquet
- South East Wales Vascular Network, Aneurin Bevan University Health Board, Royal Gwent Hospital, Newport, UK
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