Pujades-Rodriguez, M orcid.org/0000-0002-1375-1028, Guttmann, OP, Gonzalez-Izquierdo, A et al. (4 more authors) (2018) Identifying unmet clinical need in hypertrophic cardiomyopathy using national electronic health records. PLoS ONE, 13 (1). 0191214. ISSN 1932-6203
Abstract
Introduction: To evaluate unmet clinical need in unselected hypertrophic cardiomyopathy (HCM) patients to determine the risk of a wide range of subsequent cardiovascular disease endpoints and safety endpoints relevant for trial design. Methods: Population based cohort (CALIBER, linked primary care, hospital and mortality records in England, period 1997–2010), all people diagnosed with HCM were identified and matched by age, sex and general practice with ten randomly selected people without HCM. Random-effects Poisson models were used to assess the associations between HCM and cardiovascular diseases and bleeding. Results: Among 3,290,455 eligible people a diagnosis of hypertrophic cardiomyopathy was found in 4 per 10,000. Forty-one percent of the 1,160 individuals with hypertrophic cardiomyopathy were women and the median age was 57 years. The median follow-up was 4.0 years. Compared to general population controls, people with HCM had higher risk of ventricular arrhythmia (incidence rate ratio = 23.53, [95% confidence interval 12.67–43.72]), cardiac arrest or sudden cardiac death (6.33 [3.69–10.85]), heart failure (4.31, [3.30–5.62]), and atrial fibrillation (3.80 [3.04–4.75]). HCM was also associated with a higher incidence of myocardial infarction ([MI] 1.90 [1.27–2.84]) and coronary revascularisation (2.32 [1.46–3.69]).The absolute Kaplan-Meier risks at 3 years were 8.8% for the composite endpoint of cardiovascular death or heart failure, 8.4% for the composite of cardiovascular death, stroke or myocardial infarction, and 1.5% for major bleeding. Conclusions: Our study identified major unmet need in HCM and highlighted the importance of implementing improved cardiovascular prevention strategies to increase life-expectancy of the contemporary HCM population. They also show that national electronic health records provide an effective method for identifying outcomes and clinically relevant estimates of composite efficacy and safety endpoints essential for trial design in rare diseases.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018, Pujades-Rodriguez et al. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Inst of Biomed & Clin Sciences (LIBACS) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 09 Jan 2018 10:33 |
Last Modified: | 16 Mar 2018 09:05 |
Status: | Published |
Publisher: | Public Library of Science |
Identification Number: | 10.1371/journal.pone.0191214 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:125868 |