Evidence mapPaperPMID 41438296Full record

ArticleFrontiers in endocrinology2025

Analysis of risk factors and predictive value of a nomogram for peripheral arterial disease in patients with type 2 diabetes.

Yi-Zhi Zu, Cai Tang

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Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Molecular Mechanisms of Mangiferin on Neuroinflammation for Treating Major Depressive Disorder Based on Network Pharmacology and Bioinformatics Analysis.Journal of neuroimmune pharmacology : the official journal of the Society on NeuroImmune Pharmacology · 2026
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5 · Who and what money

Authors and funding

2 authors.

Yi-Zhi ZuDepartment of Endocrinology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China.
Cai TangDepartment of Endocrinology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Peripheral arterial disease (PAD) is a common macrovascular complication of type 2 diabetes mellitus (T2DM) that contributes to lower-limb morbidity and increased cardiovascular mortality. Early risk stratification is essential to guide screening and preventive measures; however, no comprehensive tool currently integrates demographic, clinical and hematologic factors to predict PAD in T2DM. Methods: In this retrospective cohort study, 426 adults with T2DM treated between January 2020 and December 2024 were stratified by PAD status (PAD, n = 136; non-PAD, n = 290). Risk factors were identified by multivariable logistic regression. A nomogram was constructed using the rms package in R and internally validated via bootstrap resampling (n = 1 000). Discrimination was assessed by area under the receiver operating characteristic curve (AUC) and concordance index (C-index), and calibration by Hosmer-Lemeshow goodness-of-fit and calibration plots. Results: Eleven independent predictors were incorporated: age; smoking; alcohol use; diabetes duration; systolic blood pressure; high-density lipoprotein cholesterol (HDL-C); low-density lipoprotein cholesterol (LDL-C); antihypertensive use; white blood cell count; platelet distribution width (PDW); and large platelet ratio (LPR). The nomogram achieved an AUC of 0.826 (95% CI 0.768-0.895), sensitivity of 78.6% and specificity of 89.6%. Internal validation yielded a bias-corrected C-index of 0.795 (95% CI 0.756-0.893), and Hosmer-Lemeshow P = 0.913, indicating good calibration. Conclusions: The proposed nomogram demonstrates robust discrimination and calibration for individualized PAD risk prediction in T2DM, supporting its potential to optimize targeted screening and preventive strategies pending external validation.

Indexed as

Diabetes Mellitus, Type 2NomogramsPeripheral Arterial DiseaseAgedFemaleHumansMaleMiddle AgedPredictive Value of TestsRetrospective StudiesRisk AssessmentRisk FactorsROC Curvenomogramperipheral arterial diseasepredictive modelingrisk factorstype 2 diabetes mellitus

Identifiers

PMID41438296
PMCPMC12719262

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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 Socratic graph.