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An electronic health records cohort study on heart failure following myocardial infarction in England: incidence and predictors
  1. Johannes M I H Gho1,2,
  2. Amand F Schmidt2,3,4,
  3. Laura Pasea1,
  4. Stefan Koudstaal1,2,
  5. Mar Pujades-Rodriguez1,5,
  6. Spiros Denaxas1,
  7. Anoop D Shah1,
  8. Riyaz S Patel1,3,
  9. Chris P Gale6,
  10. Arno W Hoes7,
  11. John G Cleland8,
  12. Harry Hemingway1,
  13. Folkert W Asselbergs1,2,3,9
  1. 1 Farr Institute of Health Informatics Research, UCL Institute of Health Informatics, University College London, London, UK
  2. 2 Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
  3. 3 Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK
  4. 4 Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands
  5. 5 Medical Research Council Bioinformatics Centre, Leeds Institute of Biomedical and Clinical Sciences, University of Leeds, Leeds, UK
  6. 6 Medical Research Council Bioinformatics Centre, Leeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
  7. 7 Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
  8. 8 National Heart & Lung Institute, Royal Brompton & Harefield Hospitals, Imperial College London, London, UK
  9. 9 Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, The Netherlands
  1. Correspondence to Dr Amand F Schmidt; amand.schmidt{at}ucl.ac.uk

Abstract

Objectives To investigate the incidence and determinants of heart failure (HF) following a myocardial infarction (MI) in a contemporary cohort of patients with MI using routinely collected primary and hospital care electronic health records (EHRs).

Methods Data were used from the CALIBER programme, linking EHRs in England from primary care, hospital admissions, an MI registry and mortality data. Subjects were eligible if they were 18 years or older, did not have a history of HF and survived a first MI. Factors associated with time to HF were examined using Cox proportional hazard models.

Results Of the 24 479 patients with MI, 5775 (23.6%) developed HF during a median follow-up of 3.7 years (incidence rate per 1000 person-years: 63.8, 95% CI 62.2 to 65.5). Baseline characteristics significantly associated with developing HF were: atrial fibrillation (HR 1.62, 95% CI 1.51 to 1.75), age (per 10 years increase: 1.45, 1.41 to 1.49), diabetes (1.45, 1.35 to 1.56), peripheral arterial disease (1.38, 1.26 to 1.51), chronic obstructive pulmonary disease (1.28, 1.17 to 1.40), greater socioeconomic deprivation (5th vs 1st quintile: 1.27, 1.13 to 1.41), ST-segment elevation MI at presentation (1.19, 1.11 to 1.27) and hypertension (1.16, 1.09 to 1.23). Results were robust to various sensitivity analyses such as competing risk analysis and multiple imputation.

Conclusion In England, one in four survivors of a first MI develop HF within 4 years. This contemporary study demonstrates that patients with MI are at considerable risk of HF. Baseline patient characteristics associated with time until HF were identified, which may be used to target preventive strategies.

  • heart failure
  • myocardial infarction
  • electronic health records

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/

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Footnotes

  • Contributors JMIHG, AFS, LP, SK, MPR, SD, ADS, RSP, CPG, AWH, JGC, HH and FWA contributed to the idea and design of the study. JMIHG extracted and prepared the data for analysis. AFS and JMIHG performed the analysis. JMIHG drafted the manuscript, with revisions from AFS, LP, SK, MPR, SD, ADS, RSP, CPG, AWH, JGC, HH and FWA. FWA is guarantor

  • Funding This study was supported by the National Institute for Health Research (RP-PG-0407-10314), the Wellcome Trust (086091/Z/08/Z), the Medical Research Council Prognosis Research Strategy Partnership (G0902393/99558) and the Farr Institute of Health Informatics Research, funded by the Medical Research Council (MR/K006584/1), in partnership with the Arthritis Research UK, the British Heart Foundation, the Cancer Research UK, the Economic and Social Research Council, the Engineering and Physical Sciences Research Council, the National Institute of Health Research, the National Institute for Social Care and Health Research (Welsh Assembly Government), the Chief Scientist Office (Scottish Government Health Directorates) and the Wellcome Trust. Part of this work is funded through the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement no 116074, BigData@Heart. AFS is funded by UCLH NIHR Biomedical Research Centre and is a UCL Springboard Population Health Sciences Fellow. HH is an NIHR Senior Investigator and receives support from the NIHR University College Hospitals/University College London Biomedical Research Centre. FWA is supported by a Dekker scholarship-Junior Staff Member 2014T001-Netherlands Heart Foundation and UCL Hospitals NIHR Biomedical Research Centre.

  • Competing interests None declared.

  • Patient consent Obtained.

  • Ethics approval CALIBER has received ethics approval (supplementary methods). This study is in compliance with the Declaration of Helsinki, was approved by the ISAC (Independent Scientific Advisory Committee) for MHRA Database Research (protocol no 14_198R) and the MINAP Academic Group and is registered with ClinicalTrials.gov (NCT02384213).

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

  • Data sharing statement Access to raw data can be requested from the CPRD (http://cprd.com).

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