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      Impact of ACEIs and ARBs-related adverse drug reaction on patients’ clinical outcomes: a cohort study in UK primary care

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          Abstract

          Background

          Adverse drug reaction (ADR) related to angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) may negatively affect patients’ treatment outcomes.

          Aim

          To investigate the impact of ACEIs/ARBs-related ADR consultation on cardiovascular disease (CVD) events and all-cause mortality.

          Design and setting

          Propensity score-matched cohort study of ACEIs/ARBs between 2004 and 2019 using UK IQVIA medical research data.

          Method

          ADR consultations were identified using standardised designated codes. Propensity scores were calculated based on comorbidities, concomitant medications, frailty, and polypharmacy. Cox’s proportional hazard regression model was used to compare the outcomes between patients in ADR and non-ADR groups. In the secondary analysis, treatment- pattern changes following the ADR were examined and the subsequent outcomes were compared.

          Results

          Among 1 471 906 eligible users of ACEIs/ARBs, 13 652 (0.93%) patients had ACEIs/ARBs- related ADR consultation in primary care. Patients with ACEIs/ARBs-related ADR consultation had an increased risk of subsequent CVD events and all- cause mortality in both primary prevention (CVD events: adjusted hazard ratio [aHR] 1.22, 95% confidence interval [CI] = 1.05 to 1.43; all-cause mortality: aHR 1.14, 95% CI = 1.01 to 1.27) and secondary prevention cohorts (CVD events: aHR 1.13, 95% CI = 1.05 to 1.21; all-cause mortality: aHR 1.15, 95% CI = 1.09 to 1.21). Half (50.19%) of patients with ADR continued to use ACEIs/ARBs, and these patients had a reduced risk of mortality (aHR 0.88, 95% CI = 0.82 to 0.95) compared with those who discontinued using ACEIs/ARBs.

          Conclusion

          This study provides information on the burden of ADR on patients and the health system. The findings call for additional monitoring and treatment strategies for patients affected by ADR to mitigate the risks of adverse clinical outcomes.

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          Most cited references65

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          2018 ESC/ESH Guidelines for the management of arterial hypertension

          Bryan P. Williams, Giuseppe Mancia, Wilko Spiering … (2018)
          Article 0 comments Cited 3082 times – based on 0 reviews     Review now
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            Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples

            Peter C Austin (2009)
            The propensity score is a subject's probability of treatment, conditional on observed baseline covariates. Conditional on the true propensity score, treated and untreated subjects have similar distributions of observed baseline covariates. Propensity-score matching is a popular method of using the propensity score in the medical literature. Using this approach, matched sets of treated and untreated subjects with similar values of the propensity score are formed. Inferences about treatment effect made using propensity-score matching are valid only if, in the matched sample, treated and untreated subjects have similar distributions of measured baseline covariates. In this paper we discuss the following methods for assessing whether the propensity score model has been correctly specified: comparing means and prevalences of baseline characteristics using standardized differences; ratios comparing the variance of continuous covariates between treated and untreated subjects; comparison of higher order moments and interactions; five-number summaries; and graphical methods such as quantile–quantile plots, side-by-side boxplots, and non-parametric density plots for comparing the distribution of baseline covariates between treatment groups. We describe methods to determine the sampling distribution of the standardized difference when the true standardized difference is equal to zero, thereby allowing one to determine the range of standardized differences that are plausible with the propensity score model having been correctly specified. We highlight the limitations of some previously used methods for assessing the adequacy of the specification of the propensity-score model. In particular, methods based on comparing the distribution of the estimated propensity score between treated and untreated subjects are uninformative. Copyright © 2009 John Wiley & Sons, Ltd.
            Article 0 comments Cited 1544 times – based on 0 reviews     Review now
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              2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines

              Paul A Heidenreich, Biykem Bozkurt, David Aguilar … (2022)
              The “2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure” replaces the “2013 ACCF/AHA Guideline for the Management of Heart Failure” and the “2017 ACC/AHA/HFSA Focused Update of the 2013 ACCF/AHA Guideline for the Management of Heart Failure.” The 2022 guideline is intended to provide patient-centric recommendations for clinicians to prevent, diagnose, and manage patients with heart failure. A comprehensive literature search was conducted from May 2020 to December 2020, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from MEDLINE (PubMed), EMBASE, the Cochrane Collaboration, the Agency for Healthcare Research and Quality, and other relevant databases. Additional relevant clinical trials and research studies, published through September 2021, were also considered. This guideline was harmonized with other American Heart Association/American College of Cardiology guidelines published through December 2021. Heart failure remains a leading cause of morbidity and mortality globally. The 2022 heart failure guideline provides recommendations based on contemporary evidence for the treatment of these patients. The recommendations present an evidence-based approach to managing patients with heart failure, with the intent to improve quality of care and align with patients’ interests. Many recommendations from the earlier heart failure guidelines have been updated with new evidence, and new recommendations have been created when supported by published data. Value statements are provided for certain treatments with high-quality published economic analyses.
              Article 0 comments Cited 1259 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Widya N Insani:
                ORCID: http://orcid.org/0000-0002-0066-9746
                Role: Doctoral student
                Cate Whittlesea:
                ORCID: http://orcid.org/0000-0002-4951-2272
                Role: Professor of pharmacy practice
                Chengsheng Ju:
                ORCID: http://orcid.org/0000-0001-7860-6262
                Role: Doctoral student
                Kenneth KC Man:
                ORCID: http://orcid.org/0000-0001-8645-1942
                Role: Senior lecturer in pharmacoepidemiology and medication safety
                Matthew Adesuyan:
                ORCID: http://orcid.org/0000-0002-2058-4096
                Role: Doctoral student
                Sarah Chapman:
                ORCID: http://orcid.org/0000-0002-7612-1605
                Role: Senior lecturer in behavioural medicine
                Li Wei:
                ORCID: http://orcid.org/0000-0001-8840-7267
                Role: Professor of pharmacoepidemiology and medication safety
                Journal
                Journal ID (nlm-ta): Br J Gen Pract
                Journal ID (iso-abbrev): Br J Gen Pract
                Journal ID (hwp): bjgp
                Journal ID (publisher-id): bjgp
                Title: The British Journal of General Practice
                Publisher: Royal College of General Practitioners
                ISSN (Print): 0960-1643
                ISSN (Electronic): 1478-5242
                Publication date Collection: November 2023
                Publication date (Electronic): 03 October 2023
                Publication date PMC-release: 03 October 2023
                Volume: 73
                Issue: 736
                Pages: e832-e842
                Affiliations
                Research Department of Practice and Policy, School of Pharmacy, University College London, London, UK; Centre of Excellence for Pharmaceutical Care Innovation, Department of Pharmacology and Clinical Pharmacy, Padjadjaran University, Bandung, Indonesia.
                Research Department of Practice and Policy, School of Pharmacy, University College London, London, UK.
                Research Department of Practice and Policy, School of Pharmacy, University College London, London, UK.
                Research Department of Practice and Policy, School of Pharmacy, University College London, London, UK; Laboratory of Data Discovery for Health, Hong Kong Science Park, Hong Kong Speical Administrative Region, China.
                Research Department of Practice and Policy, School of Pharmacy, University College London; Centre for Medicines Optimisation Research and Education, University College London Hospitals NHS Foundation Trust, London, UK.
                Institute of Pharmaceutical Science, King’s College London, London, UK.
                Research Department of Practice and Policy, School of Pharmacy, University College London; Centre for Medicines Optimisation Research and Education, University College London Hospitals NHS Foundation Trust, London, UK; Laboratory of Data Discovery for Health, Hong Kong Science Park, Hong Kong Speical Administrative Region, China.
                Author notes
                Correspondence Li Wei, Research Department of Practice and Policy, School of Pharmacy, University College London, BMA House, Tavistock Square, London WC1H 9JP, UK. Email: l.wei@ 123456ucl.ac.uk
                Author information
                http://orcid.org/0000-0002-0066-9746
                http://orcid.org/0000-0002-4951-2272
                http://orcid.org/0000-0001-7860-6262
                http://orcid.org/0000-0001-8645-1942
                http://orcid.org/0000-0002-2058-4096
                http://orcid.org/0000-0002-7612-1605
                http://orcid.org/0000-0001-8840-7267
                Article
                DOI: 10.3399/BJGP.2023.0153
                PMC ID: 10563001
                PubMed ID: 37783509
                SO-VID: 9e605ee6-4e0a-4724-aab6-b6d9b549756f
                Copyright © © The Authors
                License:

                This article is Open Access: CC BY 4.0 licence ( http://creativecommons.org/licences/by/4.0/).

                History
                Date received : 27 March 2023
                Date revision requested : 28 April 2023
                Date accepted : 26 June 2023
                Categories
                Subject: Research

                Keywords: adverse drug reaction,drug-related side effects and adverse reactions,primary health care
                Data availability:
                Keywords: adverse drug reaction, drug-related side effects and adverse reactions, primary health care

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