Evaluating the prognostic performance of bedside tests used for peripheral arterial disease diagnosis in the prediction of diabetic foot ulcer healing
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Published version
Author(s)
Type
Journal Article
Abstract
Introduction:
Diabetic foot ulceration (DFU) is a common and challenging complication of diabetes. Risk stratification can guide further management. We aim to evaluate the prognostic performance of bedside tests used for peripheral arterial disease (PAD) diagnosis to predict DFU healing.
Research Design and Methods:
TrEAD was a prospective observational study comparing the diagnostic performance of commonly-used tests for PAD diagnosis. We performed a secondary analysis assessing whether these could predict DFU healing. Follow-up was performed prospectively for 12-months. The primary outcome was sensitivity for predicting ulcer healing. Secondary endpoints were specificity, predictive values, and likelihood ratios for ulcer healing.
Results:
123 of TrEAD participants with DFU were included. In 12-months, 52.8% of ulcers healed. The best negative diagnostic likelihood ratio was observed for the PAD-scan (mono or biphasic with adverse features) (NDLR 0.35, 95% CI 0.14-0.90). The highest positive likelihood ratios were observed for TBPI of 0.2 (PDLR 7.67, 95% CI 0.91-64.84) and TcPO2 of 20mmHg (PDLR 2.68, 95% CI 0.54-13.25). Cox proportional hazard modelling demonstrated significantly greater probabilities of healing with triphasic waveforms (HR = 2.54, 95% CI 1.23 – 5.3, p=0.012) and biphasic waveforms with non-adverse features (HR = 13.67, 95% CI 4.78 – 39.1, p<0.001) on PAD-scan.
Conclusions:
No single test performed well enough to be used in isolation as a prognostic marker for the prediction of DFU healing.
Diabetic foot ulceration (DFU) is a common and challenging complication of diabetes. Risk stratification can guide further management. We aim to evaluate the prognostic performance of bedside tests used for peripheral arterial disease (PAD) diagnosis to predict DFU healing.
Research Design and Methods:
TrEAD was a prospective observational study comparing the diagnostic performance of commonly-used tests for PAD diagnosis. We performed a secondary analysis assessing whether these could predict DFU healing. Follow-up was performed prospectively for 12-months. The primary outcome was sensitivity for predicting ulcer healing. Secondary endpoints were specificity, predictive values, and likelihood ratios for ulcer healing.
Results:
123 of TrEAD participants with DFU were included. In 12-months, 52.8% of ulcers healed. The best negative diagnostic likelihood ratio was observed for the PAD-scan (mono or biphasic with adverse features) (NDLR 0.35, 95% CI 0.14-0.90). The highest positive likelihood ratios were observed for TBPI of 0.2 (PDLR 7.67, 95% CI 0.91-64.84) and TcPO2 of 20mmHg (PDLR 2.68, 95% CI 0.54-13.25). Cox proportional hazard modelling demonstrated significantly greater probabilities of healing with triphasic waveforms (HR = 2.54, 95% CI 1.23 – 5.3, p=0.012) and biphasic waveforms with non-adverse features (HR = 13.67, 95% CI 4.78 – 39.1, p<0.001) on PAD-scan.
Conclusions:
No single test performed well enough to be used in isolation as a prognostic marker for the prediction of DFU healing.
Date Issued
2023-03-14
Date Acceptance
2022-12-21
Citation
BMJ Open Diabetes Research and Care, 2023, 11 (2), pp.1-11
ISSN
2052-4897
Publisher
BMJ Publishing Group
Start Page
1
End Page
11
Journal / Book Title
BMJ Open Diabetes Research and Care
Volume
11
Issue
2
Copyright Statement
© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
License URL
Identifier
https://drc.bmj.com/content/11/2/e003110
Publication Status
Published
Article Number
e003110
Date Publish Online
2023-03-14