ArticleClinical cardiology2018
A risk score assessment tool for peripheral arterial disease in women: From the National Health and Nutrition Examination Survey.
Article in Clinical cardiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Diagnosis models to predict peripheral arterial disease: a systematic review and meta analysis.Scientific reports · 2025Pooled it
- A Glimpse Into the Black Box: Using Machine Learning to Prioritize Predictors of Vascular Disease.JACC. Advances · 2023Article
- Performance and usability testing of an automated tool for detection of peripheral artery disease using electronic health records.Scientific reports · 2022Article
- Sex Differences in Trends and In-Hospital Outcomes Among Patients With Critical Limb Ischemia: A Nationwide Analysis.Journal of the American Heart Association · 2021Article
- Novel Self-Report Tool for Cardiovascular Risk Assessment.Journal of the American Heart Association · 2019Article
- A risk score assessment tool for peripheral arterial disease in women: From the National Health and Nutrition Examination Survey.Clinical cardiology · 2018Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPeripheral arterial disease (PAD) carries a significant morbidity and mortality. Women are more commonly affected with this condition and are mostly asymptomatic, and undertreated. The objective of the study was to develop and validate a simple risk score to identify women with PAD. HYPOTHESIS: Identifying those at early stage of the disease could help reduce the risk of complications.
methodsUsing data from the National Health and Nutrition Examination Survey 1999-2004, we identified women who had data on ankle brachial index. The cohort was divided into development (70%) and validation (30%) groups. Using variables that are self-reported or measured without laboratory data, we developed a multivariable logistic regression to predict PAD, which was evaluated in the validation cohort.
resultsA total of 150.6 million women were included. A diagnosis of PAD was reported in 13.7%. Age, body mass index, hypertension, diabetes mellitus, smoking, non-oral contraceptive pill usage, and parity were all independently associated with PAD. The C-statistics was 0.74, with good calibration. The model showed good stability in the validation cohort (C-statistics 0.73).
conclusionThis parsimonious risk model is a valid tool for risk prediction of PAD in women, and could be easily applied in routine clinical practice.
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