Evidence map›Paper›PMID 41669544›Full record

ArticleFrontiers in endocrinology2026

Macrovascular complications in type 2 diabetes: a multiregional study in rural Bangladesh.

Bodrun Naher Siddiquea, Dianna J Magliano, Maima Matin, Afsana Afroz, Baki Billah

Abstract readMulticenter Study
In one paragraph

Article in Frontiers in endocrinology, 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Bodrun Naher SiddiqueaDepartment of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
Dianna J MaglianoDiabetes and Population Health, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
Maima MatinInstitute of Genetics and Animal Biotechnology of the Polish Academy of Sciences, Jastrzebiec, Poland.
Afsana AfrozDepartment of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
Baki BillahDepartment of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To assess the prevalence and determinants of macrovascular complications (coronary artery disease, stroke, and diabetic foot) among adults living with T2DM in rural Bangladesh. Methods: A population-based cross-sectional study was conducted between December 2023 and September 2024, involving 1094 adults with diagnosed T2DM from rural areas of three regions/divisions in Bangladesh. Data were collected through household interviews, physical examination, and medical record reviews. Macrovascular complications were identified using clinical criteria and documented diagnosis. The leverage of six machine learning (ML) algorithms were applied in identifying influential variables associated with these complications. Results: The prevalence of coronary artery disease (CAD), stroke, and diabetic foot was 11.2%, 5.3%, and 9.1%, respectively. The Light Gradient Boosting Machine algorithm performed best for CAD and diabetic foot, with ROC values of 98.8% and 92.6%, respectively, while Random Forest showed the best performance for stroke with a ROC of 99%. These models also outperformed others across accuracy, precision, F1 score, and calibration. Across models, common predictors included older age, longer diabetes duration, diabetes onset at age 45 years or above, and smoking. Hypertension and elevated cholesterol were linked to CAD and stroke. Coexisting microvascular complications were also identified. Conclusions: This study identified a substantial burden of macrovascular complications among rural adults with T2DM, with CAD, stroke, and diabetic foot emerging as the most prevalent outcomes. Advanced age, longer duration of diabetes, smoking, hypertension, and elevated cholesterol were consistently associated with these complications, highlighting the need for intensified cardiometabolic risk control within primary care. These findings underscore the urgency of strengthening integrated diabetes-cardiovascular management in rural Bangladesh to reduce the progression and impact of these major vascular outcomes.

Indexed as

Coronary Artery DiseaseDiabetes Mellitus, Type 2Diabetic AngiopathiesDiabetic FootStrokeAdultAgedBangladeshCross-Sectional StudiesFemaleHumansMaleMiddle AgedPrevalenceRisk FactorsRural PopulationBangladeshcoronary artery diseasediabetic footmachine learning algorithmmacrovascular complicationsstrokeType 2 diabetes

Identifiers

PMID41669544
PMCPMC12883369

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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.