Evidence map›Paper›PMID 39577876›Full record

ArticleBMJ open diabetes research & care2024

Clinical utility of novel diabetes subgroups in predicting vascular complications and mortality: up to 25 years of follow-up of the HUNT Study.

Vera Vik Bjarkø, Eirin Beate Haug, Arnulf Langhammer, Paz Lopez-Doriga Ruiz, Sofia Carlsson, Kare I Birkeland, Tore Julsrud Berg, Elin Pettersen Sørgjerd, Valeriya Lyssenko, Bjørn Olav Åsvold

Abstract read
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Article in BMJ open diabetes research & care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

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0cells of the map it votes in
8citing 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

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Vera Vik BjarkøHUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway vera.v.bjarko@ntnu.no.ORCID 0000-0002-7769-8780
Eirin Beate HaugHUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.
Arnulf LanghammerHUNT Research Center, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.
Paz Lopez-Doriga RuizDepartment of Chronic Diseases, Norwegian Institute of Public Health, Oslo, Norway.ORCID 0000-0002-3404-2060
Sofia CarlssonInstitute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden.
Kare I BirkelandInstitute of Clinical Medicine, University of Oslo, Oslo, Norway.
Tore Julsrud BergInstitute of Clinical Medicine, University of Oslo, Oslo, Norway.
Elin Pettersen SørgjerdHUNT Research Center, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.
Valeriya LyssenkoDepartment of Clinical Science, Center for Diabetes Research, University of Bergen, Bergen, Norway.
Bjørn Olav ÅsvoldHUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.ORCID 0000-0003-3837-2101

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCluster analysis has previously revealed five reproducible subgroups of diabetes, differing in risks of diabetic complications. We aimed to examine the clusters' predictive ability for vascular complications as compared with established risk factors in a general adult diabetes population. RESEARCH DESIGN AND

methodsParticipants from the second (HUNT2, 1995-1997) and third (HUNT3, 2006-2008) surveys of the Norwegian population-based Trøndelag Health Study (HUNT Study) with adult-onset diabetes were included (n=1899). To identify diabetes subgroups, we used the same variables (age at diagnosis, body mass index, HbA1c, homeostasis model assessment estimates of beta cell function and insulin resistance, and glutamic acid decarboxylase antibodies) and the same data-driven clustering technique as in previous studies. We used Cox proportional hazards models to investigate associations between clusters and risks of vascular complications and mortality. We estimated the C-index and R

resultsWe reproduced five subgroups with similar key characteristics as identified in previous studies. During median follow-up of 9-13 years (differing between outcomes), the clusters were associated with different risks of vascular complications and all-cause mortality. However, in prediction models, individual established risk factors were at least as good predictors as cluster assignment for all outcomes. For example, for retinopathy, the C-index for the model including clusters (0.65 (95% CI 0.63 to 0.68)) was similar to that of HbA1c (0.65 (95% CI 0.63 to 0.68)) or fasting C-peptide (0.66 (95% CI 0.63 to 0.68)) alone. For chronic kidney disease, the C-index for clusters (0.74 (95% CI 0.72 to 0.76)) was similar to that of triglyceride/high-density lipoprotein ratio (0.74 (95% CI 0.71 to 0.76)) or fasting C-peptide (0.74 (95% CI 0.72 to 0.76)), and baseline estimated glomerular filtration rate yielded a C-index of 0.76 (95% CI 0.74 to 0.78).

conclusionsCluster assignment did not provide better prediction of vascular complications or all-cause mortality compared with established risk factors.

Indexed as

Diabetic AngiopathiesAdultAgedCluster AnalysisDiabetes MellitusDiabetes Mellitus, Type 2FemaleFollow-Up StudiesHumansMaleMiddle AgedNorwayPrognosisRisk FactorsClassificationDiabetes ComplicationsDiabetes Mellitus, Type 2Mortality

Identifiers

PMID39577876
PMCPMC11590787

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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.