The PERCEIVE quantitative study: PrEdiction of Risk and Communication of outcome following major lower-limb amputation: protocol for a collaboratiVE study

Gwilym, Brenig Llwyd; Waldron, Cherry-Ann; Thomas-Jones, Emma; Preece, Ryan; Milosevic, Sarah; Brookes‐Howell, Lucy; Pallmann, Philip; Harris, Dylan; Massey, Ian; Burton, Jo; Stewart, Philippa; Samuel, Katie; Jones, Siân; Cox, David; Edwards, Adrian; Twine, Christopher P.; Bosanquet, David C.; Ambler, Graeme K.; Benson, Ruth A.; Dattani, Nikesh; Dovell, George; Forsythe, Rachael; Hitchman, Louise; Nandhra, Sandip; Onida, Sarah; Saratzis, Athanasios; Shalhoub, Joseph

doi:10.1093/bjsopen/zrab118

Cited by 4 publications

(4 citation statements)

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“…Datapoints were selected based on variables required to calculate outcome probabilities for risk prediction tools (full details are reported in the protocol). 14 All participating centres were required to validate both case ascertainment and data accuracy. Case ascertainment for each centre was determined by comparing the number of cases uploaded to REDCap with the number of eligible MLLA cases performed (identified by examining theatre logs or registry data).…”

Section: Data Collection Management and Validationmentioning

confidence: 99%

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

Gwilym

Pallmann

Waldron

et al. 2022

British Journal of Surgery

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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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Section: Data Collection Management and Validationmentioning

confidence: 99%

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

Gwilym

Pallmann

Waldron

et al. 2022

British Journal of Surgery

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“…Ambulation was categorized as: bedbound/chairbound; able to use prosthesis to stand/transfer only (SIGAM mobility grade B); able to use prosthesis to ambulate (SIGAM mobility grade C or higher) 20 . Accuracy evaluation included measures of discrimination, calibration and overall performance (Brier score) as appropriate 16 , 17 , 26 .…”

Section: Methodsmentioning

confidence: 99%

Long-term risk prediction after major lower limb amputation: 1-year results of the PERCEIVE study

Gwilym,

Pallmann,

Waldron

et al. 2024

BJS Open

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Background Decision-making when considering major lower limb amputation is complex and requires individualized outcome estimation. It is unknown how accurate healthcare professionals or relevant outcome prediction tools are at predicting outcomes at 1-year after major lower limb amputation. Methods An international, multicentre prospective observational study evaluating healthcare professional accuracy in predicting outcomes 1 year after major lower limb amputation and evaluation of relevant outcome prediction tools identified in a systematic search of the literature was undertaken. Observed outcomes at 1 year were compared with: healthcare professionals’ preoperative predictions of death (surgeons and anaesthetists), major lower limb amputation revision (surgeons) and ambulation (surgeons, specialist physiotherapists and vascular nurse practitioners); and probabilities calculated from relevant outcome prediction tools. Results A total of 537 patients and 2244 healthcare professional predictions of outcomes were included. Surgeons and anaesthetists had acceptable discrimination (C-statistic = 0.715), calibration and overall performance (Brier score = 0.200) when predicting 1-year death, but performed worse when predicting major lower limb amputation revision and ambulation (C-statistics = 0.627 and 0.662 respectively). Healthcare professionals overestimated the death and major lower limb amputation revision risks. Consultants outperformed trainees, especially when predicting ambulation. Allied healthcare professionals marginally outperformed surgeons in predicting ambulation. Two outcome prediction tools (C-statistics = 0.755 and 0.717, Brier scores = 0.158 and 0.178) outperformed healthcare professionals’ discrimination, calibration and overall performance in predicting death. Two outcome prediction tools for ambulation (C-statistics = 0.688 and 0.667) marginally outperformed healthcare professionals. Conclusion There is uncertainty in predicting 1-year outcomes following major lower limb amputation. Different professional groups performed comparably in this study. Two outcome prediction tools for death and two for ambulation outperformed healthcare professionals and may support shared decision-making.

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“…), along with others, are undertaking PERCEIVE (PrEdiction of Risk and Communication of outcome following MLLA, a collaboratiVE study), a prospective, observational study looking at the accuracy of the clinicians' predictions of outcomes after MLLA. 5 PERCEIVE will also externally validate all identified risk prediction tools. This international, multicentre study has examined 537 patients undergoing MLLA, from 41 centers.…”

Section: Dear Editor(s)mentioning

confidence: 99%