Evidence map›Paper›PMID 33879507›Full record

ArticleOpen heart2021

Assessing the severity of cardiovascular disease in 213 088 patients with coronary heart disease: a retrospective cohort study.

Salwa S Zghebi, Mamas A Mamas, Darren M Ashcroft, Martin K Rutter, Harm VanMarwijk, Chris Salisbury, Christian D Mallen, Caroline A Chew-Graham, Nadeem Qureshi, Stephen F Weng and 6 more

Abstract readMulticenter Study
In one paragraph

Article in Open heart, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

16 authors.

Salwa S ZghebiNIHR School for Primary Care Research, Centre for Primary Care and Health Services Research, Manchester Academic Health Science Centre (MAHSC), The University of Manchester, Manchester, UK salwa.zghebi@manchester.ac.uk.ORCID 0000-0002-7978-1094
Mamas A MamasDivision of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), The University of Manchester, Manchester, UK.ORCID 0000-0001-9241-8890
Darren M AshcroftNIHR School for Primary Care Research, Centre for Primary Care and Health Services Research, Manchester Academic Health Science Centre (MAHSC), The University of Manchester, Manchester, UK.
Martin K RutterDivision of Diabetes, Endocrinology and Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), The University of Manchester, Manchester, UK.
Harm VanMarwijkDivision of Primary Care and Public Health, Brighton and Sussex Medical School, University of Brighton, Brighton, UK.
Chris SalisburyCentre for Academic Primary Care, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Christian D MallenSchool of Primary, Community and Social Care, Faculty of Medicine and Health Sciences, Keele University, Staffordshire, UK.
Caroline A Chew-GrahamSchool of Primary, Community and Social Care, Faculty of Medicine and Health Sciences, Keele University, Staffordshire, UK.
Nadeem QureshiPrimary Care Stratified Medicine (PRISM) Research Group, Division of Primary Care, School of Medicine, University of Nottingham, Nottingham, UK.ORCID 0000-0003-4909-0644
Stephen F WengStatistical Decision Sciences, Cardiovascular and Metabolism, Janssen Research and Development, High Wycombe, UK.
Tim HoltNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Iain BuchanDivision of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), The University of Manchester, Manchester, UK.
Niels PeekNIHR Greater Manchester Patient Safety Translational Research Centre, The University of Manchester, Manchester, UK.
Sally GilesDivision of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), The University of Manchester, Manchester, UK.
David ReevesNIHR School for Primary Care Research, Centre for Primary Care and Health Services Research, Manchester Academic Health Science Centre (MAHSC), The University of Manchester, Manchester, UK.
Evangelos KontopantelisNIHR School for Primary Care Research, Centre for Primary Care and Health Services Research, Manchester Academic Health Science Centre (MAHSC), The University of Manchester, Manchester, UK.ORCID 0000-0001-6450-5815

Funding

Medical Research Council MR/S027750/1
6 · The paper itself

Abstract

objectiveMost current cardiovascular disease (CVD) risk stratification tools are for people without CVD, but very few are for prevalent CVD. In this study, we developed and validated a CVD severity score in people with coronary heart disease (CHD) and evaluated the association between severity and adverse outcomes.

methodsPrimary and secondary care data for 213 088 people with CHD in 398 practices in England between 2007 and 2017 were used. The cohort was randomly divided into training and validation datasets (80%/20%) for the severity model. Using 20 clinical severity indicators (each assigned a weight=1), baseline and longitudinal CVD severity scores were calculated as the sum of indicators. Adjusted Cox and competing-risk regression models were used to estimate risks for all-cause and cause-specific hospitalisation and mortality.

resultsMean age was 64.5±12.7 years, 46% women, 16% from deprived areas, baseline severity score 1.5±1.2, with higher scores indicating a higher burden of disease. In the training dataset, 138 510 (81%) patients were hospitalised at least once, and 39 944 (23%) patients died. Each 1-unit increase in baseline severity was associated with 41% (95% CI 37% to 45%, area under the receiver operating characteristics (AUROC) curve=0.79) risk for 1 year for all-cause mortality; 59% (95% CI 52% to 67%, AUROC=0.80) for cardiovascular (CV)/diabetes mortality; 27% (95% CI 26% to 28%) for any-cause hospitalisation and 37% (95% CI 36% to 38%) for CV/diabetes hospitalisation. Findings were consistent in the validation dataset.

conclusionsHigher CVD severity score is associated with higher risks for any-cause and cause-specific hospital admissions and mortality in people with CHD. Our reproducible score based on routinely collected data can help practitioners better prioritise management of people with CHD in primary care.

Indexed as

Cardiovascular DiseasesCause of DeathCoronary AngiographyCoronary DiseaseEnglandFemaleFollow-Up StudiesHumansMaleMiddle AgedMorbidityRetrospective StudiesRisk AssessmentRisk FactorsSurvival Ratecoronary artery diseaseelectronic health recordsmyocardial infarction

Identifiers

PMID33879507
PMCPMC8061853

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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.