ArticleCirculation. Cardiovascular interventions2022
Ankle- and Toe-Brachial Index for Peripheral Artery Disease Identification: Unlocking Clinical Data Through Novel Methods.
Article in Circulation. Cardiovascular interventions, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 8 citations in OpenAlex.
- Statins Use in Veterans With Peripheral Artery Disease: Insights From the PEARLS Study.Circulation. Population health and outcomes · 2026Article
- Cumulative Metabolic Exposure to Hyperglycemia and Risk of Cardiovascular and Limb Events in Peripheral Artery Disease.medRxiv : the preprint server for health sciences · 2026Article
- Artificial Intelligence in Peripheral Artery Disease: A Science Advisory From the American Heart Association.Circulation. Population health and outcomes · 2026Review
- Article
- Blood Pressure and Risk of Clinical Events in Peripheral Artery Disease.medRxiv : the preprint server for health sciences · 2025Article
- Long-Term Outcomes of Peripheral Artery Disease in Veterans: Analysis of the Peripheral Artery Disease Long-Term Survival Study (PEARLS).Journal of the American Heart Association · 2025Article
- Development of Mathematical Model for Understanding Microcirculation in Diabetic Foot Ulcers Based on Ankle-Brachial Index.Bioengineering (Basel, Switzerland) · 2025Article
- Global, regional, and national burdens of lower extremity peripheral arterial disease from 1990 to 2021 and projections to 2050: global burden of disease study 2021.Frontiers in cardiovascular medicine · 2025Article
- Long-term Outcomes of Peripheral Artery Disease In Veterans: Analysis of the PEripheral ARtery Disease Long-term Survival Study (PEARLS).medRxiv : the preprint server for health sciences · 2024Article
- Heart disease risk factors detection from electronic health records using advanced NLP and deep learning techniques.Scientific reports · 2023Article
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Authors and funding
14 authors at 8 institutions in 1 country.
Funding
Abstract
backgroundDespite its high prevalence and clinical impact, research on peripheral artery disease (PAD) remains limited due to poor accuracy of billing codes. Ankle-brachial index (ABI) and toe-brachial index can be used to identify PAD patients with high accuracy within electronic health records.
methodsWe developed a novel natural language processing (NLP) algorithm for extracting ABI and toe-brachial index values and laterality (right or left) from ABI reports. A random sample of 800 reports from 94 Veterans Affairs facilities during 2015 to 2017 was selected and annotated by clinical experts. We trained the NLP system using random forest models and optimized it through sequential iterations of 10-fold cross-validation and error analysis on 600 test reports and evaluated its final performance on a separate set of 200 reports. We also assessed the accuracy of NLP-extracted ABI and toe-brachial index values for identifying patients with PAD in a separate cohort undergoing ABI testing.
resultsThe NLP system had an overall precision (positive predictive value) of 0.85, recall (sensitivity) of 0.93, and F1 measure (accuracy) of 0.89 to correctly identify ABI/toe-brachial index values and laterality. Among 261 patients with ABI testing (49% PAD), the NLP system achieved a positive predictive value of 92.3%, sensitivity of 83.1%, and specificity of 93.1% to identify PAD when compared with a structured chart review. The above findings were consistent in a range of sensitivity analysis.
conclusionsWe successfully developed and validated an NLP system for identifying patients with PAD within the Veterans Affairs electronic health record. Our findings have broad implications for PAD research and quality improvement.
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