Evidence map›Paper›PMID 31345214›Full record

ArticleBMC medicine2019

The comorbidity burden of type 2 diabetes mellitus: patterns, clusters and predictions from a large English primary care cohort.

Magdalena Nowakowska, Salwa S Zghebi, Darren M Ashcroft, Iain Buchan, Carolyn Chew-Graham, Tim Holt, Christian Mallen, Harm Van Marwijk, Niels Peek, Rafael Perera-Salazar and 6 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in BMC medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 147 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
147citing papers in PubMed, 4 pooled it
21.7field-weighted citation impact, top 1% of its field
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

147 citing papers in PubMed, 4 syntheses or guidelines pooled it, 323 citations in OpenAlex.

  1. Pooled it
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  12. Implementing SGLT2 Inhibitor Therapy in Line with the New NICE Guidelines for Type 2 Diabetes Management.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2026
    Review
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87 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 6 institutions in 1 country.

Magdalena NowakowskaNIHR School for Primary Care Research, Centre for Primary Care and Health Services Research, Manchester Academic Health Science Centre (MAHSC), University of Manchester, 5th floor Williamson Building, Manchester, M13 9PL, UK. magdalena.nowakowska@manchester.ac.uk.ORCID http://orcid.org/0000-0003-1386-2534
Salwa S ZghebiNIHR School for Primary Care Research, Centre for Primary Care and Health Services Research, Manchester Academic Health Science Centre (MAHSC), University of Manchester, 5th floor Williamson Building, Manchester, M13 9PL, UK.
Darren M AshcroftNIHR School for Primary Care Research, Centre for Primary Care and Health Services Research, Manchester Academic Health Science Centre (MAHSC), University of Manchester, 5th floor Williamson Building, Manchester, M13 9PL, UK.
Iain BuchanDivision of Informatics, Imaging, and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, M13 9PL, UK.
Carolyn Chew-GrahamResearch Institute for Primary Care and Health Sciences, Faculty of Medicine and Health Sciences, Keele University, DJW 1.54a, Staffordshire, ST5 5BJ, UK.
Tim HoltNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
Christian MallenResearch Institute for Primary Care and Health Sciences, Faculty of Medicine and Health Sciences, Keele University, DJW 1.54a, Staffordshire, ST5 5BJ, UK.
Harm Van MarwijkDivision of Primary Care and Public Health, Brighton and Sussex Medical School, University of Sussex, Brighton, BN1 9PH, UK.
Niels PeekNIHR Greater Manchester Patient Safety Translational Research Centre, University of Manchester, Manchester, M13 9PL, UK.
Rafael Perera-SalazarNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
David ReevesNIHR School for Primary Care Research, Centre for Primary Care and Health Services Research, Manchester Academic Health Science Centre (MAHSC), University of Manchester, 5th floor Williamson Building, Manchester, M13 9PL, UK.
Martin K RutterDivision of Diabetes, Endocrinology and Gastroenterology, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, M13 9PL, UK.
Stephen F WengPrimary Care Stratified Medicine (PRISM), Division of Primary Care, School of Medicine, University of Nottingham, Nottingham, NG7 2RD, UK.
Nadeem QureshiPrimary Care Stratified Medicine (PRISM), Division of Primary Care, School of Medicine, University of Nottingham, Nottingham, NG7 2RD, UK.
Mamas A MamasKeele Cardiovascular Research Group, Centre for Prognosis Research, Institute for Primary Care and Health Sciences, Keele University, Stoke-on-Trent, ST4 7QB, UK.
Evangelos KontopantelisNIHR School for Primary Care Research, Centre for Primary Care and Health Services Research, Manchester Academic Health Science Centre (MAHSC), University of Manchester, 5th floor Williamson Building, Manchester, M13 9PL, UK.
Manchester Academic Health Science Centre · GBKeele University · GBUniversity of Nottingham · GBUniversity of Oxford · GBBrighton and Sussex Medical School · GBUniversity of Liverpool · GB

Funding

Department of Health RP_2014-04-026Department of Health RP-PG-0617-20005Medical Research Council MC_PC_13042Medical Research Council MR/K006665/1
6 · The paper itself

Abstract

backgroundThe presence of additional chronic conditions has a significant impact on the treatment and management of type 2 diabetes (T2DM). Little is known about the patterns of comorbidities in this population. The aims of this study are to quantify comorbidity patterns in people with T2DM, to estimate the prevalence of six chronic conditions in 2027 and to identify clusters of similar conditions.

methodsWe used the Clinical Practice Research Datalink (CPRD) linked with the Index of Multiple Deprivation (IMD) data to identify patients diagnosed with T2DM between 2007 and 2017. 102,394 people met the study inclusion criteria. We calculated the crude and age-standardised prevalence of 18 chronic conditions present at and after the T2DM diagnosis. We analysed longitudinally the 6 most common conditions and forecasted their prevalence in 2027 using linear regression. We used agglomerative hierarchical clustering to identify comorbidity clusters. These analyses were repeated on subgroups stratified by gender and deprivation.

resultsMore people living in the most deprived areas had ≥ 1 comorbidities present at the time of diagnosis (72% of females; 64% of males) compared to the most affluent areas (67% of females; 59% of males). Depression prevalence increased in all strata and was more common in the most deprived areas. Depression was predicted to affect 33% of females and 15% of males diagnosed with T2DM in 2027. Moderate clustering tendencies were observed, with concordant conditions grouped together and some variations between groups of different demographics.

conclusionsComorbidities are common in this population, and high between-patient variability in comorbidity patterns emphasises the need for patient-centred healthcare. Mental health is a growing concern, and there is a need for interventions that target both physical and mental health in this population.

Indexed as

AdultAgedChronic DiseaseCluster AnalysisCohort StudiesComorbidityDiabetes ComplicationsDiabetes Mellitus, Type 2EnglandFemaleForecastingHumansMaleMiddle AgedPrevalencePrimary Health CareComorbidityCPRDPrevalencePrimary careType 2 diabetes mellitus

Identifiers

PMID31345214
PMCPMC6659216
OpenAlexW2955840062

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.