Omeprazole and Risk of Hypertension: Analysis of Existing Literature and the WHO Global Pharmacovigilance Database.

IF 1.9 Q3 PHARMACOLOGY & PHARMACY
Merhawi Bahta, Natnael Russom, Amon Solomon Ghebrenegus, Yohana Tecleab Okubamichael, Mulugeta Russom
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引用次数: 0

Abstract

Introduction: The association between omeprazole and hypertension is poorly documented. The summary of product characteristics of omeprazole approved by major regulators did not mention hypertension as an adverse drug event. Triggered by a locally reported case, this study was conducted to assess the possible causal relationship between omeprazole and hypertension.

Methods: Globally reported cases of hypertension following use of omeprazole submitted to the World Health Organization global database, VigiBase, were retrieved on 5 March 2024 and analyzed descriptively. Besides this, a literature search was made to identify preclinical, clinical, and epidemiological information on the association between omeprazole and hypertension or increased blood pressure using different data sources. Relevant information, gathered from different data sources, was finally systematically organized into an Austin Bradford-Hill causality assessment framework to assess the causal relationship between omeprazole and hypertension.

Results: VigiBase indicated a total of 1043 cases of hypertension related to omeprazole from 36 different countries. In the global database, a statistical signal was triggered (IC025: 0.12) on association of omeprazole and hypertension. From the 1043 cases, 65.0% and 10.6% were reported as 'serious' and 'fatal', respectively. Hypertension resolved following withdrawal of omeprazole in 85 cases and recurred after re-introduction of the suspect drug in 14 cases. In 225 cases, omeprazole was the only suspected drug, while in 122 cases, omeprazole was the sole drug administered. When only these 122 cases were considered, 29 cases had positive dechallenge, four cases were with positive rechallenge and the median time-to-onset was 2 days. Literature search identified a possible biological mechanism and some experimental evidence that indicates omeprazole could possibly cause hypertension.

Conclusion: Currently available totality of evidence suggests there is a possible causal relationship between omeprazole and hypertension. Hence, it is recommended to monitor and report any incidence of hypertension related to omeprazole, and further epidemiological studies are recommended to corroborate the suggested causal association.

奥美拉唑与高血压风险:现有文献和世界卫生组织全球药物警戒数据库分析》。
简介关于奥美拉唑与高血压之间的关系,文献记载很少。主要监管机构批准的奥美拉唑产品特征概要中并未提及高血压是一种药物不良反应。本研究由当地报告的一个病例引发,旨在评估奥美拉唑与高血压之间可能存在的因果关系:方法:检索了 2024 年 3 月 5 日世界卫生组织全球数据库 VigiBase 中全球报告的使用奥美拉唑后出现高血压的病例,并进行了描述性分析。此外,还利用不同的数据来源进行文献检索,以确定奥美拉唑与高血压或血压升高之间关联的临床前、临床和流行病学信息。最后,将从不同数据来源收集到的相关信息系统地整理到奥斯汀-布拉德福德-希尔因果关系评估框架中,以评估奥美拉唑与高血压之间的因果关系:VigiBase显示,共有来自36个不同国家的1043例高血压患者与奥美拉唑有关。在全球数据库中,奥美拉唑与高血压的相关性触发了统计信号(IC025:0.12)。在 1043 个病例中,分别有 65.0% 和 10.6% 的病例被报告为 "严重 "和 "致命"。85 例高血压患者在停用奥美拉唑后症状缓解,14 例在重新使用可疑药物后复发。在 225 例病例中,奥美拉唑是唯一的可疑药物,而在 122 例病例中,奥美拉唑是唯一的用药。仅考虑这 122 个病例,29 个病例的去挑战试验呈阳性,4 个病例的再挑战试验呈阳性,中位发病时间为 2 天。文献检索发现了奥美拉唑可能导致高血压的生物学机制和一些实验证据:结论:现有的全部证据表明,奥美拉唑与高血压之间可能存在因果关系。因此,建议监测和报告任何与奥美拉唑有关的高血压发病率,并建议进一步开展流行病学研究,以证实所建议的因果关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Drugs - Real World Outcomes
Drugs - Real World Outcomes PHARMACOLOGY & PHARMACY-
CiteScore
3.60
自引率
5.00%
发文量
49
审稿时长
8 weeks
期刊介绍: Drugs - Real World Outcomes targets original research and definitive reviews regarding the use of real-world data to evaluate health outcomes and inform healthcare decision-making on drugs, devices and other interventions in clinical practice. The journal includes, but is not limited to, the following research areas: Using registries/databases/health records and other non-selected observational datasets to investigate: drug use and treatment outcomes prescription patterns drug safety signals adherence to treatment guidelines benefit : risk profiles comparative effectiveness economic analyses including cost-of-illness Data-driven research methodologies, including the capture, curation, search, sharing, analysis and interpretation of ‘big data’ Techniques and approaches to optimise real-world modelling.
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