ArticleiScience2024
A machine learning algorithm for peripheral artery disease prognosis using biomarker data.
Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Enhanced Prediction of Peripheral Artery Disease Using Plasma Proteomics Among Individuals Without Diabetes.Journal of the American Heart Association · 2026Article
- Growth Differentiation Factor 15 Predicts Cardiovascular Events in Peripheral Artery Disease.Biomolecules · 2025Article
- The Prognostic Potential of Insulin-like Growth Factor-Binding Protein 1 for Cardiovascular Complications in Peripheral Artery Disease.Journal of cardiovascular development and disease · 2025Article
- Interferon Gamma and Tumor Necrosis Factor Alpha Are Inflammatory Biomarkers for Major Adverse Cardiovascular Events in Patients with Peripheral Artery Disease.Biomedicines · 2025Article
- Association of Hepatocyte Growth Factor and Angiopoietin-2 with Systemic Cardiovascular Risk in Patients with Peripheral Artery Disease.Journal of clinical medicine · 2025Article
- Predicting Transvaginal Surgical Mesh Exposure Outcomes Using an Integrated Dataset of Blood Cytokine Levels and Medical Record Data: Machine Learning Approach.JMIR formative research · 2025Article
- Prediction of Major Adverse Limb Events in Females with Peripheral Artery Disease using Blood-Based Biomarkers and Clinical Features.Journal of cardiovascular translational research · 2025Article
- Current Prognostic Biomarkers for Peripheral Arterial Disease: A Comprehensive Systematic Review of the Literature.Metabolites · 2025Review
- Investigating the Prognostic Potential of Plasma ST2 in Patients with Peripheral Artery Disease: Identification and Evaluation.Proteomes · 2024Article
- Revolutionizing Cardiology through Artificial Intelligence-Big Data from Proactive Prevention to Precise Diagnostics and Cutting-Edge Treatment-A Comprehensive Review of the Past 5 Years.Diagnostics (Basel, Switzerland) · 2024Review
- Prediction of Peripheral Artery Disease Prognosis Using Clinical and Inflammatory Biomarker Data.Journal of inflammation research · 2024Article
- Machine Learning in Vascular Medicine: Optimizing Clinical Strategies for Peripheral Artery Disease.Current cardiovascular risk reports · 2024Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Peripheral artery disease (PAD) biomarkers have been studied in isolation; however, an algorithm that considers a protein panel to inform PAD prognosis may improve predictive accuracy. Biomarker-based prediction models were developed and evaluated using a model development (n = 270) and prospective validation cohort (n = 277). Plasma concentrations of 37 proteins were measured at baseline and the patients were followed for 2 years. The primary outcome was 2-year major adverse limb event (MALE; composite of vascular intervention or major amputation). Of the 37 proteins tested, 6 were differentially expressed in patients with vs. without PAD (ADAMTS13, ICAM-1, ANGPTL3, Alpha 1-microglobulin, GDF15, and endostatin). Using 10-fold cross-validation, we developed a random forest machine learning model that accurately predicts 2-year MALE in a prospective validation cohort of PAD patients using a 6-protein panel (AUROC 0.84). This algorithm can support PAD risk stratification, informing clinical decisions on further vascular evaluation and management.
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