Evidence map›Paper›PMID 33196309›Full record

Trial reportCirculation2020

Risk Factor Control and Cardiovascular Event Risk in People With Type 2 Diabetes in Primary and Secondary Prevention Settings.

Alison K Wright, Milton Fabian Suarez-Ortegon, Stephanie H Read, Evangelos Kontopantelis, Iain Buchan, Richard Emsley, Naveed Sattar, Darren M Ashcroft, Sarah H Wild, Martin K Rutter

Open access · hybridAbstract readClinical TrialComparative StudyMulticenter Study
In one paragraph

Trial report in Circulation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed
6.7field-weighted citation impact, top 2% 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

62 citing papers in PubMed, 122 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Cancer as a novel risk factor for major cardiovascular adverse events in secondary prevention.International journal of cardiology. Cardiovascular risk and prevention · 2025
    Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article

2 more citing papers are in PubMed but not listed here.

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 at 8 institutions in 3 countries.

Alison K Wright *Division of Diabetes, Endocrinology and Gastroenterology, School of Medical Sciences, University of Manchester, United Kingdom (A.K.W., M.K.R.).
Milton Fabian Suarez-Ortegon *Departamento de Alimentación y Nutrición, Facultad de Ciencias de la Salud, Pontificia Universidad Javeriana Seccional Cali, Colombia (M.F.S.-O.).
Stephanie H ReadUsher Institute of Population Health Sciences and Informatics, University of Edinburgh, United Kingdom (S.H.R., S.H.W.).
Evangelos KontopantelisDivision of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, United Kingdom (E.K.).
Iain BuchanDepartment of Public Health and Policy, Institute of Population Health Sciences, University of Liverpool, United Kingdom (I.B.).
Richard EmsleyDepartment of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom (R.E.).
Naveed SattarInstitute of Cardiovascular & Medical Sciences, University of Glasgow, United Kingdom (N.S.).
Darren M Ashcroft *Centre for Pharmacoepidemiology and Drug Safety, Division of Pharmacy and Optometry, School of Health Sciences, University of Manchester, United Kingdom (A.K.W., D.M.A.).
Sarah H Wild *Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, United Kingdom (S.H.R., S.H.W.).
Martin K Rutter *Division of Diabetes, Endocrinology and Gastroenterology, School of Medical Sciences, University of Manchester, United Kingdom (A.K.W., M.K.R.).
Manchester Academic Health Science Centre · GBHealth Data Research UK · GBHewlett-Packard (United Kingdom) · GBKing's College London · GBPontificia Universidad Javeriana · COUniversity of Glasgow · GBUniversity of Liverpool · GBWomen's College Hospital · CA

Funding

Diabetes UK 14/0004971Medical Research Council MR/K006665/1Medical Research Council MR/T025085/1
6 · The paper itself

Abstract

backgroundTo examine the association between the degree of risk factor control and cardiovascular disease (CVD) risk in type 2 diabetes and to assess if the presence of cardio-renal disease modifies these relationships.

methodsA retrospective cohort study using data from English practices from CPRD GOLD (Clinical Practice Research Datalink) and the SCI-Diabetes dataset (Scottish Care Information-Diabetes), with linkage to hospital and mortality data. We identified 101 749 with type 2 diabetes (T2D) in CPRD matched with 378 938 controls without diabetes and 330 892 with type 2 diabetes in SCI-Diabetes between 2006 and 2015. The main exposure was number of optimized risk factors: nonsmoker, total cholesterol ≤4 mmol/L, triglycerides ≤1.7 mmol/L, glycated haemoglobin (HbA1c) ≤53 mmol/mol (≤7.0%), systolic blood pressure <140mm Hg, or <130 mm Hg if high risk. Cox models were used to assess cardiovascular risk associated with levels of risk factor control.

resultsIn CPRD, the mean baseline age in T2D was 63 years and 28% had cardio-renal disease (SCI-Diabetes: 62 years; 35% cardio-renal disease). Over 3 years follow-up (SCI-Diabetes: 6 years), CVD events occurred among 27 900 (27%) CPRD-T2D, 101 362 (31%) SCI-Diabetes-T2D, and 75 520 (19%) CPRD-controls. In CPRD, compared with controls, T2D participants with optimal risk factor control (all risk factors controlled) had a higher risk of CVD events (adjusted hazard ratio, 1.21; 95% confidence interval, 1.12-1.29). In T2D participants from CPRD and SCI-Diabetes, pooled hazard ratios for CVD associated with 5 risk factors being elevated versus optimal risk factor control were 1.09 (95% confidence interval, 1.01-1.17) in people with cardio-renal disease but 1.96 (95% confidence interval, 1.82-2.12) in people without cardio-renal disease. People without cardio-renal disease were younger and more likely to have likely to have suboptimal risk factor control but had fewer prescriptions for risk factor modifying medications than those with cardio-renal disease.

conclusionsOptimally managed people with T2D have a 21% higher CVD risk when compared with controls. People with T2D without cardio-renal disease would be predicted to benefit greatly from CVD risk factor intervention.

Indexed as

Cardiovascular DiseasesModels, CardiovascularSecondary PreventionAgedAged, 80 and overCholesterolDiabetes Mellitus, Type 2Glycated HemoglobinHumansMiddle AgedRetrospective StudiesTriglyceridesCholesterolGlycated Hemoglobinhemoglobin A1c protein, humanTriglyceridescardiovascular risk factorsprimary careprimary preventionrisk assessmentsecondary caresecondary preventiontype 2 diabetes

Identifiers

PMID33196309
PMCPMC7664968
OpenAlexW3092100636

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.