Evidence map›Paper›PMID 39913381›Full record

ArticlePloS one2025

Differential risk of cardiovascular complications in patients with type-2 diabetes mellitus in Ghana: A hospital-based cross-sectional study.

Christian Obirikorang, Evans Asamoah Adu, Anthony Afum-Adjei Awuah, Samuel Nkansah Darko, Frank Naku Ghartey, Samuel Ametepe, Eric N Y Nyarko, Enoch Odame Anto, William Kwame Boakye Ansah Owiredu

Abstract read
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Review
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

9 authors.

Christian ObirikorangDepartment of Molecular Medicine, School of Medical Sciences, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana.ORCID 0000-0002-6128-1358
Evans Asamoah AduDepartment of Molecular Medicine, School of Medical Sciences, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana.
Anthony Afum-Adjei AwuahDepartment of Molecular Medicine, School of Medical Sciences, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana.
Samuel Nkansah DarkoDepartment of Molecular Medicine, School of Medical Sciences, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana.ORCID 0000-0002-0750-4311
Frank Naku GharteyDepartment of Chemical Pathology, School of Medical Sciences, University of Cape Coast, Cape Coast, Ghana.
Samuel AmetepeDepartment of Molecular Medicine, School of Medical Sciences, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana.
Eric N Y NyarkoDepartment of Chemical Pathology, University of Ghana Medical School, University of Ghana, Accra, Ghana.ORCID 0000-0002-3757-2569
Enoch Odame AntoDepartment of Medical Diagnostics, Faculty of Allied Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.ORCID 0000-0001-9023-6612
William Kwame Boakye Ansah OwireduDepartment of Molecular Medicine, School of Medical Sciences, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo characterize clinically relevant subgroups of patients with type-2 diabetes mellitus (T2DM) based on adiposity, insulin secretion, and resistance indices.

methodsA cross-sectional study was conducted at Eastern Regional Hospital in Ghana from July to October 2021 to investigate long-term patients with T2DM. To select participants, a systematic random sampling method was employed. Demographic data was collected using a structured questionnaire and fasting blood samples were taken to measure glycemic and lipid levels. Blood pressure and adiposity indices were measured during recruitment. The risk of cardiovascular disease (CVD) was defined using Framingham scores and standard low-density lipoprotein thresholds. To analyze the data, k-means clustering algorithms and regression analysis were used.

resultsThe study identified three groups in female patients according to body mass index, relative fat mass, glycated hemoglobin, and triglyceride-glucose index. These groups included the obesity-related phenotype, the severe insulin resistance phenotype, and the normal weight phenotype with improved insulin resistance. Among male patients with T2DM, two groups were identified, including the obesity-related phenotype with severe insulin resistance and the normal weight phenotype with improved insulin sensitivity. The severe insulin resistance phenotype in female patients was associated with an increased risk of high CVD (OR = 5.34, 95%CI:2.11-13.55) and metabolic syndrome (OR = 7.07; 95%CI:3.24-15.42). Among male patients, the obesity-related phenotype with severe insulin resistance was associated with an increased intermediate (OR = 21.78, 95%CI:4.17-113.78) and a high-risk CVD (OR = 6.84, 95%CI:1.45-32.12).

conclusionsThe findings highlight significant cardiometabolic heterogeneity among T2DM patients. The subgroups of T2DM patients characterized by obesity and/or severe insulin resistance with or without poor glycemic control, have increased risk of CVD. This underscores the importance of considering differences in adiposity, insulin secretion, and sensitivity indices when making clinical decisions for patients with T2DM.

Indexed as

Cardiovascular DiseasesDiabetes Mellitus, Type 2AdiposityAdultAgedBlood GlucoseBody Mass IndexCross-Sectional StudiesFemaleGhanaGlycated HemoglobinHumansInsulin ResistanceMaleMiddle AgedObesityBlood GlucoseGlycated Hemoglobin

Identifiers

PMID39913381
PMCPMC11801548

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.