The impact of the COVID-19 pandemic on cardiovascular disease prevention and management.
Journal
Nature medicine
ISSN: 1546-170X
Titre abrégé: Nat Med
Pays: United States
ID NLM: 9502015
Informations de publication
Date de publication:
01 2023
01 2023
Historique:
received:
18
03
2022
accepted:
28
11
2022
pubmed:
20
1
2023
medline:
27
1
2023
entrez:
19
1
2023
Statut:
ppublish
Résumé
How the Coronavirus Disease 2019 (COVID-19) pandemic has affected prevention and management of cardiovascular disease (CVD) is not fully understood. In this study, we used medication data as a proxy for CVD management using routinely collected, de-identified, individual-level data comprising 1.32 billion records of community-dispensed CVD medications from England, Scotland and Wales between April 2018 and July 2021. Here we describe monthly counts of prevalent and incident medications dispensed, as well as percentage changes compared to the previous year, for several CVD-related indications, focusing on hypertension, hypercholesterolemia and diabetes. We observed a decline in the dispensing of antihypertensive medications between March 2020 and July 2021, with 491,306 fewer individuals initiating treatment than expected. This decline was predicted to result in 13,662 additional CVD events, including 2,281 cases of myocardial infarction and 3,474 cases of stroke, should individuals remain untreated over their lifecourse. Incident use of lipid-lowering medications decreased by 16,744 patients per month during the first half of 2021 as compared to 2019. By contrast, incident use of medications to treat type 2 diabetes mellitus, other than insulin, increased by approximately 623 patients per month for the same time period. In light of these results, methods to identify and treat individuals who have missed treatment for CVD risk factors and remain undiagnosed are urgently required to avoid large numbers of excess future CVD events, an indirect impact of the COVID-19 pandemic.
Identifiants
pubmed: 36658423
doi: 10.1038/s41591-022-02158-7
pii: 10.1038/s41591-022-02158-7
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
219-225Subventions
Organisme : Medical Research Council
ID : MR/L006758/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/V028367/1
Pays : United Kingdom
Organisme : British Heart Foundation
ID : SP/19/3/34678
Pays : United Kingdom
Organisme : Department of Health
Pays : United Kingdom
Organisme : Chief Scientist Office
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_PC_20030
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_PC_20059
Pays : United Kingdom
Organisme : Department of Health
ID : MR/V015737/1
Pays : United Kingdom
Commentaires et corrections
Type : CommentIn
Informations de copyright
© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.
Références
Katsoulis, M. et al. Estimating the effect of reduced attendance at emergency departments for suspected cardiac conditions on cardiac mortality during the COVID-19 pandemic. Circ. Cardiovasc. Qual. Outcomes 14, e007085 (2021).
doi: 10.1161/CIRCOUTCOMES.120.007085
Watt, T., Firth, Z., Fisher, R., Thorlby, R. & Kelly, E. Use of primary care during the COVID-19 pandemic: patient-level data analysis of the impact of COVID-19 on primary care activity in England. https://www.health.org.uk/news-and-comment/charts-and-infographics/use-of-primary-care-during-the-covid-19-pandemic (The Health Foundation, 2020).
Watt, T., Kelly, E. & Fisher, R. Use of primary care during the COVID-19 pandemic: May 2021 update: patient-level data analysis of the impact of COVID-19 on primary care activity in England. https://www.health.org.uk/news-and-comment/charts-and-infographics/use-of-primary-care-during-the-covid-19-pandemic-may-2021 (The Health Foundation, 2021).
Curtis, H. J. et al. OpenSAFELY NHS Service Restoration Observatory 1: primary care clinical activity in England during the first wave of COVID-19. Br. J. Gen. Pract. 72, e63–e74 (2022).
doi: 10.3399/BJGP.2021.0380
Carr, M. J. et al. Impact of COVID-19 on diagnoses, monitoring, and mortality in people with type 2 diabetes in the UK. Lancet Diabetes Endocrinol. 9, 413–415 (2021).
doi: 10.1016/S2213-8587(21)00116-9
Health Data Research UK. BHF Data Science Centre. https://www.hdruk.ac.uk/helping-with-health-data/bhf-data-science-centre/
Health Data Research UK. CVD-COVID-UK/COVID-IMPACT. https://www.hdruk.ac.uk/projects/cvd-covid-uk-project/
Wood, A. et al. Linked electronic health records for research on a nationwide cohort of more than 54 million people in England: data resource. BMJ 373, n826 (2021).
doi: 10.1136/bmj.n826
Institute for Government Analysis. Timeline of UK coronavirus lockdowns, March 2020 to March 2021. https://www.instituteforgovernment.org.uk/sites/default/files/timeline-lockdown-web.pdf
National Institute for Health and Care Excellence. Hypertension in adults: diagnosis and management. Evidence review for initiating treatment. NICE guideline NG136. Intervention evidence review underpinning recommendations 1.4.9 to 1.4.14 in the guideline. https://www.nice.org.uk/guidance/ng136/evidence/c-initiating-treatment-pdf-6896748208 (2019).
Thygesen, J. H. et al. COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records. Lancet Digit. Health 4, e542–e557 (2022).
Torabi, F. et al. Impact of COVID-19 pandemic on community medication dispensing: a national cohort analysis in Wales, UK. Int. J. Popul. Data Sci. 5, 1715 (2022).
Mazidi, M., Leeming, E. R. & Merino, J. Diet and lifestyle behaviour disruption related to the pandemic was varied and bidirectional among US and UK adults participating in the ZOE COVID Study. Nat. Food 2, 957–969 (2021).
doi: 10.1038/s43016-021-00398-3
ZOE COVID Study. https://covid.joinzoe.com/
Laffin, L. J. et al. Rise in blood pressure observed among US adults during the COVID-19 pandemic. Circulation 145, 235–237 (2022).
OpenSAFELY Collaborative, Curtis, H. J. et al. OpenSAFELY: impact of national guidance on switching anticoagulant therapy during COVID-19 pandemic. Open Heart 8, e001784 (2020).
Handy, A. et al. Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort. Heart 108, 923–931 (2022).
Office for National Statistics. Population estimates for the UK, England and Wales, Scotland and Northern Ireland: mid-2020. https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/bulletins/annualmidyearpopulationestimates/mid2020
NHS Digital. Quality and Outcomes Framework. https://qof.digital.nhs.uk/
Welsh Government. Quality Assurance and Improvement Framework (QAIF): General Medical Services contract 2019 to 2020. https://gov.wales/sites/default/files/publications/2020-11/guidance-for-the-gms-contract-wales-2019-20.pdf
Scottish Government. Improving Together: a national framework for quality and GP clusters in Scotland. https://www.gov.scot/publications/improving-together-national-framework-quality-gp-clusters-scotland/
Mansfield, K. E. et al. Indirect acute effects of the COVID-19 pandemic on physical and mental health in the UK: a population-based study. Lancet Digit. Health 3, e217–e230 (2021).
doi: 10.1016/S2589-7500(21)00017-0
Ball, S. et al. Monitoring indirect impact of COVID-19 pandemic on services for cardiovascular diseases in the UK. Heart 106, 1890–1897 (2020).
doi: 10.1136/heartjnl-2020-317870
Nuffield Trust & The Health Foundation. NHS Health Check programme, https://www.nuffieldtrust.org.uk/resource/nhs-health-check-programme (2021).
Visseren, F. L. J. et al. 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice. Eur. Heart J. 42, 3227–3337 (2021).
doi: 10.1093/eurheartj/ehab484
Parker, R. F. et al. Inequalities in general practice remote consultations: a systematic review. BJGP Open 5, BJGPO.2021.0040 (2021).
Health and Social Care Information Centre. EPS Prescriptions Report. https://app.powerbi.com/view?r=eyJrIjoiNjVlNWY5M2MtY2E0Ny00NzczLThhOTgtMWUwMTVkMjRmZDAxIiwidCI6IjUwZjYwNzFmLWJiZmUtNDAxYS04ODAzLTY3Mzc0OGU2MjllMiIsImMiOjh9&pageName=ReportSectionec3fefdd11925031e801%20
National Institute for Health and Care Excellence. British National Formulary. https://bnf.nice.org.uk/
NHS Business Services Authority. Dispensing Data. https://www.nhsbsa.nhs.uk/prescription-data/dispensing-data
NHS Research Scotland. Data Safe Haven https://www.nhsresearchscotland.org.uk/research-in-scotland/data/safe-havens#:~:text=Safe%20Havens%20provide%20a%20platform,to%20agreed%20principles%20and%20standards
Bennie, M., Malcolm, W., McTaggart, S. & Mueller, T. Improving prescribing through big data approaches—ten years of the Scottish Prescribing Information System. Br. J. Clin. Pharm. 86, 250–257 (2020).
doi: 10.1111/bcp.14184
ISD Scotland Home. National Data Catalogue. https://www.ndc.scot.nhs.uk/National-Datasets/data.asp?SubID=9
Alvarez-Madrazo, S., McTaggart, S., Nangle, C., Nicholson, E. & Bennie, M. Data Resource Profile: the Scottish National Prescribing Information System (PIS). Int. J. Epidemiol. 45, 714–715f (2016).
doi: 10.1093/ije/dyw060
Lyons, R. A. et al. The SAIL databank: linking multiple health and social care datasets. BMC Med. Inf. Decis. Mak. 9, 3 (2009).
doi: 10.1186/1472-6947-9-3
Ford, D. V. et al. The SAIL Databank: building a national architecture for e-health research and evaluation. BMC Health Serv. Res. 9, 157 (2009).
doi: 10.1186/1472-6963-9-157
Health Data Research Innovation Gateway. Welsh Longitudinal GP Dataset. https://web.www.healthdatagateway.org/dataset/33fc3ffd-aa4c-4a16-a32f-0c900aaea3d2
Health Data Research Innovation Gateway. Welsh Dispensing Dataset (WDDS). https://web.www.healthdatagateway.org/dataset/50ef6443-ed4b-40f9-97fb-1cfd53be6579
NHS Business Services Authority. BNF SNOMED mapping. https://www.nhsbsa.nhs.uk/prescription-data/understanding-our-data/bnf-snomed-mapping
Bernal, J. L., Cummins, S. & Gasparrini, A. Interrupted time series regression for the evaluation of public health interventions: a tutorial. Int. J. Epidemiol. 46, 348–355 (2017).
Schaffer, A. L., Dobbins, T. A. & Pearson, S. A. Interrupted time series analysis using autoregressive integrated moving average (ARIMA) models: a guide for evaluating large-scale health interventions. BMC Med. Res. Methodol. 21, 58 (2021).
doi: 10.1186/s12874-021-01235-8
Ward, S. et al. Statins for the Prevention of Coronary Events: Technology Assessment Report Commissioned by the HTA Programme on Behalf of the National Institute for Clinical Excellence (National Institute for Health and Clinical Excellence, 2005).
Brunstrom, M. & Carlberg, B. Association of blood pressure lowering with mortality and cardiovascular disease across blood pressure levels: a systematic review and meta-analysis. JAMA Intern. Med. 178, 28–36(2018).
ClinRisk. Welcome to the QRISK