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Coronary artery disease
Original research
Assessing the severity of cardiovascular disease in 213 088 patients with coronary heart disease: a retrospective cohort study
  1. Salwa S Zghebi1,2,
  2. Mamas A Mamas2,3,
  3. Darren M Ashcroft1,4,5,6,
  4. Martin K Rutter7,8,
  5. Harm VanMarwijk9,
  6. Chris Salisbury10,
  7. Christian D Mallen11,
  8. Caroline A Chew-Graham11,
  9. Nadeem Qureshi12,
  10. Stephen F Weng13,
  11. Tim Holt14,
  12. Iain Buchan2,15,16,
  13. Niels Peek5,6,16,
  14. Sally Giles2,5,
  15. David Reeves1,2,17 and
  16. Evangelos Kontopantelis1,2,16
  1. 1NIHR 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
  2. 2Division 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
  3. 3Keele Cardiovascular Research Group, Centre for Prognosis Research, School of Primary, Community and Social Care, Keele University, Stoke-on-Trent, UK
  4. 4Division of Pharmacy and Optometry, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), The University of Manchester, Manchester, UK
  5. 5NIHR Greater Manchester Patient Safety Translational Research Centre, The University of Manchester, Manchester, UK
  6. 6NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre (MAHSC), Manchester, UK
  7. 7Division 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
  8. 8Diabetes, Endocrinology and Metabolism Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre (MAHSC), Manchester, UK
  9. 9Division of Primary Care and Public Health, Brighton and Sussex Medical School, University of Brighton, Brighton, UK
  10. 10Centre for Academic Primary Care, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
  11. 11School of Primary, Community and Social Care, Faculty of Medicine and Health Sciences, Keele University, Staffordshire, UK
  12. 12Primary Care Stratified Medicine (PRISM) Research Group, Division of Primary Care, School of Medicine, University of Nottingham, Nottingham, UK
  13. 13Statistical Decision Sciences, Cardiovascular and Metabolism, Janssen Research and Development, High Wycombe, UK
  14. 14Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
  15. 15Institute of Population Health Sciences, University of Liverpool, Liverpool, UK
  16. 16Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), The University of Manchester, Manchester, UK
  17. 17Centre for Biostatistics, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), The University of Manchester, Manchester, UK
  1. Correspondence to Dr Salwa S Zghebi; salwa.zghebi{at}manchester.ac.uk

Abstract

Objective Most 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.

Methods Primary 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.

Results Mean 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.

Conclusions Higher 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.

  • coronary artery disease
  • myocardial infarction
  • electronic health records

Data availability statement

Clinical code lists are available from clinicalcodes.org. Electronic health records are, by definition, considered sensitive data in the UK by the Data Protection Act and cannot be shared via public deposition because of information governance restriction in place to protect patient confidentiality. Access to data is available only once approval has been obtained through the individual constituent entities controlling access to the data. The primary care data can be requested via application to the Clinical Practice Research Datalink, secondary care data can be requested via application to the Hospital Episode Statistics from the UK Health and Social Care Information Centre, and mortality data are available by application to the UK Office for National Statistics.

https://creativecommons.org/licenses/by/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

https://doi.org/10.1136/openhrt-2020-001498

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    Data availability statement

    Clinical code lists are available from clinicalcodes.org. Electronic health records are, by definition, considered sensitive data in the UK by the Data Protection Act and cannot be shared via public deposition because of information governance restriction in place to protect patient confidentiality. Access to data is available only once approval has been obtained through the individual constituent entities controlling access to the data. The primary care data can be requested via application to the Clinical Practice Research Datalink, secondary care data can be requested via application to the Hospital Episode Statistics from the UK Health and Social Care Information Centre, and mortality data are available by application to the UK Office for National Statistics.

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    Footnotes

    • Twitter @mmamas1973

    • Contributors EK, MM and SZ designed the study. SZ extracted and analysed the data and drafted the manuscript. MM, DR and EK critically revised the initial versions, and all authors contributed to interpretation of data and revised the paper for important intellectual content. All authors agreed on the final version of the paper before submission. SZ is the guarantor of the paper.

    • Funding This study is funded by the National Institute for Health Research (NIHR) School for Primary Care Research (NIHR SPCR – grant number 331).

    • Disclaimer The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. The funder of the study had no role in study design, data collection, data analysis, data interpretation or writing of the report. The lead author had full access to the data in the study, takes responsibility for its integrity and the data analysis and had final responsibility for the decision to submit for publication.

    • Competing interests DMA reports research grants from Abbvie, Almirall, Celgene, Eli Lilly, Novartis, UCB and the Leo Foundation and is funded by the NIHR Greater Manchester Patient Safety Translational Research Centre, the NIHR School for Primary Care Research, and the NIHR Manchester Biomedical Research Centre. MKR has received educational grant support from MSD and Novo Nordisk; has modest stock ownership in GSK; and has consulted for Roche. CS reports grants from NIHR School for Primary Care Research during the conduct of the study, is partially supported by NHS ARC West and is an NIHR Senior Investigator. CDM is funded by the NIHR Collaborations for Leadership in Applied Health Research and Care West Midlands, the NIHR School for Primary Care Research and a NIHR Research Professorship in General Practice (NIHR-RP-2014-04-026). He has provided support for a Bristol Myer Squibb non-pharmacological Atrial Fibrillation study (funding to School). NQ reports grants from the NIHR SPCR and NIHR HTA, during the conduct of the study. SFW is an employee of Janssen R NIHR Senior Investigator grant. NP’s time was partially funded by the NIHR Manchester Biomedical Research Centre. Other coauthors have no disclosures.

    • Provenance and peer review Not commissioned; externally peer reviewed.