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

Vascular and Endovascular Research Network (VERN) and PERCEIVE study group; 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

doi:10.1093/bjs/znac309

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

Vascular and Endovascular Research Network (VERN) and PERCEIVE study group, 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

^*Corresponding author for this work

Applied Health Sciences

Research output: Contribution to journal › Article › peer-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 language	English
Pages (from-to)	1300-1311
Number of pages	12
Journal	British Journal of Surgery
Volume	109
Issue number	12
Early online date	6 Sept 2022
DOIs	https://doi.org/10.1093/bjs/znac309
Publication status	Published - 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).

Copyright:
© The Author(s) 2022. Published by Oxford University Press on behalf of BJS Society Ltd. All rights reserved. For permissions, please e-mail: [email protected].

Keywords

Adult
Humans
Amputation, Surgical
Peripheral Arterial Disease
Morbidity
Lower Extremity/surgery
Risk Assessment

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1093/bjs/znac309

Cite this

Vascular and Endovascular Research Network (VERN) and PERCEIVE study group, Gwilym, B. L., Pallmann, P., Waldron, C.-A., 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, C. P., & Bosanquet, D. C. (2022). Short-term risk prediction after major lower limb amputation: PERCEIVE study. British Journal of Surgery, 109(12), 1300-1311. https://doi.org/10.1093/bjs/znac309

@article{19dda6fe7de74d7ab3b2a19791672a55,

title = "Short-term risk prediction after major lower limb amputation: PERCEIVE study",

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.",

keywords = "Adult, Humans, Amputation, Surgical, Peripheral Arterial Disease, Morbidity, Lower Extremity/surgery, Risk Assessment",

author = "{Vascular and Endovascular Research Network (VERN) and PERCEIVE study group} and Gwilym, {Brenig L} and Philip Pallmann and Cherry-Ann Waldron and Emma Thomas-Jones and Sarah Milosevic and Lucy Brookes-Howell and Debbie Harris and Ian Massey and Jo Burton and Phillippa Stewart and Katie Samuel and Sian Jones and David Cox and Annie Clothier and Adrian Edwards and Twine, {Christopher P} and Bosanquet, {David C} and Ruth Benson",

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). Copyright: {\textcopyright} The Author(s) 2022. Published by Oxford University Press on behalf of BJS Society Ltd. All rights reserved. For permissions, please e-mail: [email protected].",

year = "2022",

month = dec,

doi = "10.1093/bjs/znac309",

language = "English",

volume = "109",

pages = "1300--1311",

journal = "British Journal of Surgery",

issn = "0007-1323",

publisher = "Wiley",

number = "12",

}

Vascular and Endovascular Research Network (VERN) and PERCEIVE study group, Gwilym, BL, Pallmann, P, Waldron, C-A, 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 2022, 'Short-term risk prediction after major lower limb amputation: PERCEIVE study', British Journal of Surgery, vol. 109, no. 12, pp. 1300-1311. https://doi.org/10.1093/bjs/znac309

TY - JOUR

T1 - Short-term risk prediction after major lower limb amputation

T2 - PERCEIVE study

AU - Vascular and Endovascular Research Network (VERN) and PERCEIVE study group

AU - Gwilym, Brenig L

AU - Pallmann, Philip

AU - Waldron, Cherry-Ann

AU - Thomas-Jones, Emma

AU - Milosevic, Sarah

AU - Brookes-Howell, Lucy

AU - Harris, Debbie

AU - Massey, Ian

AU - Burton, Jo

AU - Stewart, Phillippa

AU - Samuel, Katie

AU - Jones, Sian

AU - Cox, David

AU - Clothier, Annie

AU - Edwards, Adrian

AU - Twine, Christopher P

AU - Bosanquet, David C

AU - Benson, Ruth

N1 - 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). Copyright: © The Author(s) 2022. Published by Oxford University Press on behalf of BJS Society Ltd. All rights reserved. For permissions, please e-mail: [email protected].

PY - 2022/12

Y1 - 2022/12

N2 - 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.

AB - 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.

KW - Adult

KW - Humans

KW - Amputation, Surgical

KW - Peripheral Arterial Disease

KW - Morbidity

KW - Lower Extremity/surgery

KW - Risk Assessment

U2 - 10.1093/bjs/znac309

DO - 10.1093/bjs/znac309

M3 - Article

C2 - 36065602

SN - 0007-1323

VL - 109

SP - 1300

EP - 1311

JO - British Journal of Surgery

JF - British Journal of Surgery

IS - 12

ER -

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

Abstract

Bibliographical note

Keywords

UN SDGs

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