ArticleFood science & nutrition2025
Evaluating the Oxidative Balance Score for Peripheral Artery Disease Risk: Integrating Epidemiologic Modeling and SHAP-Interpretable Machine Learning in NHANES.
Article in Food science & nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- The role of diet and periodontitis in preserved ratio impaired spirometry: a mediation analysis.Frontiers in nutrition · 2026Article
- Evaluating the Oxidative Balance Score for Peripheral Artery Disease Risk: Integrating Epidemiologic Modeling and SHAP-Interpretable Machine Learning in NHANES.Food science & nutrition · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Oxidative stress plays a central role in the development of peripheral artery disease (PAD), yet composite indices quantifying its impact remain underutilized. The oxidative balance score (OBS), integrating dietary and lifestyle exposures, may offer a comprehensive approach to vascular risk stratification. We analyzed data from 7249 U.S. adults in NHANES 1999-2004 to examine the association between OBS and PAD, defined by an ankle-brachial index ≤ 0.9. Multivariable logistic regression and restricted cubic spline models were used to assess both linear and nonlinear associations. Twelve machine learning models were constructed to predict PAD status; the top-performing model (GLMNet) was interpreted using SHapley Additive exPlanations (SHAP) to identify key predictors. Higher OBS levels were significantly associated with reduced PAD prevalence (fully adjusted OR per unit increase: 0.963; 95% CI: 0.944-0.983;
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.