Evidence map›Paper›PMID 42662675›Full record

ArticleACS omega2026

Development of a Shapley Additive Explanations (SHAP)-Interpretable Model for Cardiovascular Risk Stratification in Type 2 Diabetes Mellitus: Implications of MDA-Modified Protein Adducts and Autoantibodies.

Chien-Yi Hsu, Shou-Cheng Lu, Liang-Wei Lin, Chu-Heng Yen, Hung-Tse Lin, Shao-Chun Lin, Ching-Yu Lin, Chao-Lien Liu

Abstract read
In one paragraph

Article in ACS omega, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Chien-Yi HsuDivision of Cardiology, Department of Internal Medicine, School of Medicine, College of Medicine,Taipei Heart Institute, Taipei Medical University, Taipei 11031, Taiwan.
Shou-Cheng LuDepartment of Laboratory Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City 23561, Taiwan.
Liang-Wei LinDepartment of Laboratory Medicine, Taiwan Adventist Hospital, Taipei 10556, Taiwan.
Chu-Heng YenDepartment of Laboratory Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City 23561, Taiwan.
Hung-Tse LinDepartment of Laboratory Medicine, LinKou Chang Gung Memorial Hospital, Taoyuan 33305, Taiwan.
Shao-Chun LinDepartment of Pharmacy, Chia Nan University of Pharmacy & Science, Tainan City 717301, Taiwan.
Ching-Yu LinSchool of Medical Laboratory Science and Biotechnology, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan.
Chao-Lien LiuSchool of Medical Laboratory Science and Biotechnology, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronary artery disease (CAD) is the leading cause of mortality in type 2 diabetes mellitus (T2DM). This study explores the two-hit oxidative-immune hypothesis by evaluating malondialdehyde (MDA)-modified protein (MDA-protein) adducts and their corresponding autoantibodies for precise and fair CAD severity stratification and classification. Novel MDA-peptide epitopes (apolipoprotein B-100 (ApoB-100), fibronectin (FINC), and complement C4A/C4B (C4A/C4B)) were identified via proteomics, and plasma levels of MDA, adducts, and autoantibodies were measured in 165 Taiwanese T2DM patients. Multivariate logistic regression estimated odds ratios (ORs) per 1-SD increase. Machine learning with Shapley additive explanations (SHAP)-interpretable analysis and nested cross validation distinguished obstructive from nonobstructive CAD. Fairness was assessed across age and sex subgroups. MDA (OR 3.148) and MDA-protein adducts (OR 2.090) were independent markers associated with advanced CAD severity, while IgG anti-ApoB-100

Identifiers

PMID42662675
PMCPMC13520431

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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.