Evidence map›Paper›PMID 35942273›Full record

ArticleEClinicalMedicine2022

Variations in comorbidity burden in people with type 2 diabetes over disease duration: A population-based analysis of real world evidence.

Jonathan Pearson-Stuttard, Sara Holloway, Rosie Polya, Rebecca Sloan, Linxuan Zhang, Edward W Gregg, Katy Harrison, Jamie Elvidge, Pall Jonsson, Thomas Porter

Abstract read
In one paragraph

Article in EClinicalMedicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 4 pooled it
–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

48 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Trial
  6. Biochemical and Molecular Markers Among Prediabetic and Type 2 Diabetes Mellitus Patients.International journal of endocrinology and metabolism · 2026
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  7. Article
  8. Observational
  9. Review
  10. Osteoarthritis among individuals with diabetes mellitus in Saudi Arabia.Journal of family medicine and primary care · 2026
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  11. Observational
  12. Article
  13. Article
  14. Article
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  20. Observational
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

10 authors.

Jonathan Pearson-StuttardHealth Analytics, Lane Clark & Peacock LLP, London, UK.
Sara HollowayHealth Analytics, Lane Clark & Peacock LLP, London, UK.
Rosie PolyaHealth Analytics, Lane Clark & Peacock LLP, London, UK.
Rebecca SloanHealth Analytics, Lane Clark & Peacock LLP, London, UK.
Linxuan ZhangHealth Analytics, Lane Clark & Peacock LLP, London, UK.
Edward W GreggDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
Katy HarrisonNational Institute for Health and Care Excellence, Manchester, UK.
Jamie ElvidgeNational Institute for Health and Care Excellence, Manchester, UK.
Pall JonssonNational Institute for Health and Care Excellence, Manchester, UK.
Thomas PorterHealth Analytics, Lane Clark & Peacock LLP, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The prevalence of type 2 diabetes (T2DM) is increasing, but increasing longevity among persons with diagnosed diabetes may be is associated with more extensive and diverse types of morbidity. The extent and breadth of morbidity and how this varies across sub-groups is unclear and could have important clinical and public health implications. We aimed to estimate comorbidity profiles in people with T2DM and variations across sub-groups and over time. Methods: We identified approximately 224,000 people with T2DM in the Discover-NOW dataset, a real-world primary care database from 2000 to 2020 covering 2.5 million people across North-West London, England, linked to hospital records. We generated a mixed prevalence and incidence study population through repeated annual cross sections, and included a broad set of 35 comorbidities covering traditional T2DM conditions, emerging T2DM conditions and other common conditions.We estimated annual age-standardised prevalence of comorbidities, over the course of the disease in people with T2DM and several sub-groups. Findings: Multimorbidity (two or more chronic conditions) is common in people with T2DM and increasing, but the comorbidity profiles of people with T2DM vary substantially. Nearly 30% of T2DM patients had three or more comorbidities at diagnosis, increasing to 60% of patients ten years later. Two of the five commonest comorbidities at diagnosis were traditional T2DM conditions (hypertension (37%) and ischaemic heart disease (10%)) the other three were not (depression (15%), back pain (25%) and osteoarthritis (11%)). The prevalence of each increased during the course of the disease, with more than one in three patients having back pain and one in four having depression ten years post diagnosis.People with five or more comorbidities at diagnosis had higher prevalence of each of the 35 comorbidities. Hypertension (73%) was the commonest comorbidity at diagnosis in this group; followed by back pain (69%), depression (67%), asthma (45%) and osteoarthritis (36%). People with obesity at diagnosis had substantially different comorbidity profiles to those without, and the five commonest comorbidities were 50% more common in this group. Interpretation: Preventative and clinical interventions alongside care pathways for people with T2DM should transition to reflect the diverse set of causes driving persistent morbidity. This would benefit both patients and healthcare systems alike. Funding: The study was funded by the National Institute for Health and Care Excellence (NICE).

Indexed as

DiabetesEpidemiologyMultimorbidity

Identifiers

PMID35942273
PMCPMC9356197

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.