Accès ouvert déclaré
2022
article
Short-term risk prediction after major lower limb amputation: PERCEIVE study
Brenig Llwyd Gwilym, Philip Pallmann, Cherry-Ann Waldron, Emma Thomas‐Jones, Sarah Milosevic, Lucy Brookes‐Howell, Debbie Harris, Ian Massey, Jo Burton, Phillippa Stewart, Katie Samuel, Siân Jones, David Cox, Annie Clothier, Adrian Edwards, Christopher P. Twine, David C. Bosanquet, Graeme K. Ambler, Ruth Benson, Panagiota Birmpili, Robert Blair, Nikesh Dattani, George Dovell, Rachael O. Forsythe, Louise Hitchman, Matthew Machin, Sandip Nandhra, Sarah Onida, Ryan Preece, Athanasios Saratzis, Joseph Shalhoub, Aminder Singh, Patrice Forget, Maria Gannon, Anna Celnik, Mary Duguid, Amy Campbell, Karen A. Duncan, Bryce Renwick, Moore Jn, Martin Maresch, M Tolba, Diaa Kamal, Mohamed Kabis, Mohamed Hatem, Maciej Juszczak, Hannah Travers, Ahmed Shalan, Mohammed Elsabbagh, João Rocha‐Neves, António Pereira-Neves, José Teixeira, Oliver Lyons, Eric Lim, Khaleel Hamdulay, Ragai Makar, Shady Zaki, Chris Francis, Amanda Azer, Tamer Ghatwary-Tantawy, Khalid Elsayed, Devender Mittapalli, R Melvin, Hashem Barakat, James P. Taylor, Samantha Veal, Hytham K. S. Hamid, Efstratia Baili, Georgios Kastrisios, Chrisostomos Maltezos, Konstantinos Maltezos, Christiana Anastasiadou, A Pachı̀, Antonia Skotsimara, Badri Vijaynagar, Simon Lau, Rahul Velineni, E Bright, Elizabeth Montague-Johnstone, Kirsty Stewart, W. King, Christos D. Karkos, M Mitka, C Papadimitriou, George Smith, Erick Chan, Anita Eseenam Agbeko, Joachim Amoako, A Vijay, Konstantinos Roditis, Vasilios Papaioannou, A Antoniou, Paraskevi Tsiantoula, Nikolaos Bessias, Th. Papas, Fiona Goodchild, James Rammell, Claire Dawkins, Pierfrancesco Lapolla, Paolo Sapienza, Gioia Brachini, Andrea Mingoli, Keith Hussey, A Meldrum, Lara Dearie, Manoj S. Nair, Andrew Duncan, Benjamin Webb, Stefan Klimach, Thomas J. Hardy, Francesca Guest, Luke Hopkins, Ummul Contractor, Olivia McBride, Meghan Hallatt, D Pang, Li En Tan, Nishath Altaf, Jackie Wong, B Thurston, Owen Ash, Matthew Popplewell, A. Grewal, Bethany G. Wardle, Natalie Condie, Kit Lam, Francesca Heigberg-Gibbons, Prakash Saha, Tamara Hayes, S. Patel, Stephen Black, Mustafa Musajee, Asad Choudhry, Emmanuel Nii Boye Hammond, M Costanza, Palma M. Shaw, Anthony Feghali, Aditi Chawla, Sławomir Surowiec, Ronald Zerna Encalada, Claire J. Cadwallader, Peter Clayton, Isabelle Van Herzeele, Mia Geenens, Lina Vermeir, Nathalie Moreels, Sybille Geers, Arkadiusz Jawień, Tomasz Arentewicz, Nikolaos Kontopodis, Stella Lioudaki, Emmanouil Tavlas, V Nyktari, Alexander Oberhuber, Arwa Ibrahim, J. Neu, Teresa Nierhoff, Konstantinos G. Moulakakis, Stavros K. Kakkos, Κωνσταντίνος Νικολακόπουλος, Spyros Papadoulas, Mario D’Oria, Sandro Lepidi, Fiona Kent, Dana E. Lowry, Setthasorn Zhi Yang Ooi, Ibrahim Enemosah, Bruce W. Patterson, Simon Williams, Ghadeer Hesham Elrefaey, Kamran Gaba, Geoffrey F. Williams, D. Urriza Rodriguez, Manar Khashram, Sinead Gormley, O Hart, Elizabeth Suthers, Stephen French
14Citations signalées — pas une note de qualité
7Institutions déclarées
1Pays d’affiliation déclarés
Résumé fourni par la source
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.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Short-term risk prediction after major lower limb amputation: PERCEIVE study
- Date Crossref
- 06/09/2022
- Éditeur
- Oxford University Press (OUP)
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude et ne compte pas comme une seconde source scientifique indépendante.
Institutions déclarées
Une affiliation ne permet pas de déduire la nationalité d’un auteur.
Sujets associés
Prosthetics and Rehabilitation RoboticsDiabetic Foot Ulcer Assessment and ManagementPeripheral Artery Disease Management