Chourasiya Sadhnakumari, Patel Pratixa
Department of Pharmacology, ROFEL, Shri G.M. Bilakhia College of Pharmacy, Rajju Shroff Rofel University, Vapi, Gujarat, 396191, India.
Naunyn Schmiedebergs Arch Pharmacol. 2025 May 19. doi: 10.1007/s00210-025-04262-0.
Despite the extensive research on medication-related adverse events (MRAEs) in healthcare, the assessment of the present scenario is made more difficult by the high degree of variability in study results. This study's primary goal was to create a current picture of what is currently known about the prevalence, risk factors, and surveillance of MRAEs in healthcare and overview of pharmacovigilance in preventing MRAEs. In order to find specific research on the prevalence, risk factors, economic effects, and monitoring techniques of medication-related adverse events, a comprehensive search was conducted using relevant search terms across electronic databases. Only research/review published after 2015 were considered in this analysis in order to provide the most current picture of the scenario. Patients who are elderly and have reduced liver or renal function, polypharmacy, or have several other comorbidities are more likely to experience medication-related side effects. Nevertheless, the use of high-risk medications and specific care settings also significantly raises the risk of MRAEs. Computerized techniques may open up new opportunities for event forecasting across all MRAE subtypes when paired with machine learning. Supporting collaborative research between computer science and medicine should be a top priority for pharmacovigilance research and patient safety initiatives in the future in order to provide prospects for the creation of clever preventative work strategies. However, the creation of effective real-time detection techniques may lead to significant advancements in predicting and incident avoidance in the future.
尽管在医疗保健领域对药物相关不良事件（MRAEs）进行了广泛研究，但研究结果的高度变异性使得对当前情况的评估变得更加困难。本研究的主要目标是呈现一幅关于医疗保健中MRAEs的患病率、风险因素和监测的现有认知现状图，并概述药物警戒在预防MRAEs方面的情况。为了找到关于药物相关不良事件的患病率、风险因素、经济影响和监测技术的具体研究，我们使用相关搜索词在电子数据库中进行了全面搜索。为了提供该情况的最新图景，本分析仅考虑2015年以后发表的研究/综述。老年人以及肝肾功能减退、使用多种药物或患有其他多种合并症的患者更有可能经历药物相关的副作用。然而，使用高风险药物和特定的护理环境也会显著增加MRAEs的风险。当与机器学习相结合时，计算机技术可能为所有MRAE亚型的事件预测开辟新的机会。支持计算机科学与医学之间的合作研究应成为未来药物警戒研究和患者安全倡议的首要任务，以便为制定明智的预防工作策略提供前景。然而，有效的实时检测技术的创建可能会在未来的预测和事件避免方面带来重大进展。
