Department of Pharmacy, Laboratory of Teaching and Research in Social Pharmacy (LEPFS), Federal University of Sergipe, São Cristóvão, Sergipe, Brazil.
Universitary Hospital, Investigative Pathology Laboratory, Federal University of Sergipe, Aracaju, Brazil.
PLoS One. 2020 Jul 1;15(7):e0235353. doi: 10.1371/journal.pone.0235353. eCollection 2020.
This review aims to determine the prevalence of clinically manifested drug-drug interactions (DDIs) in hospitalized patients.
PubMed, Scopus, Embase, Web of Science, and Lilacs databases were used to identify articles published before June 2019 that met specific inclusion criteria. The search strategy was developed using both controlled and uncontrolled vocabulary related to the following domains: "drug interactions," "clinically relevant," and "hospital." In this review, we discuss original observational studies that detected DDIs in the hospital setting, studies that provided enough data to allow us to calculate the prevalence of clinically manifested DDIs, and studies that described the drugs prescribed or provided DDI adverse reaction reports, published in either English, Portuguese, or Spanish.
From the initial 5,999 articles identified, 10 met the inclusion criteria. The pooled prevalence of clinically manifested DDIs was 9.2% (CI 95% 4.0-19.7). The mean number of medications per patient reported in six studies ranged from 4.0 to 9.0, with an overall average of 5.47 ± 1.77 drugs per patient. The quality of the included studies was moderate. The main methods used to identify clinically manifested DDIs were evaluating medical records and ward visits (n = 7). Micromedex® (27.7%) and Lexi-Comp® (27.7%) online reference databases were commonly used to detect DDIs and none of the studies evaluated used more than one database for this purpose.
This systematic review showed that, despite the significant prevalence of potential DDIs reported in the literature, less than one in ten patients were exposed to a clinically manifested drug interaction. The use of causality tools to identify clinically manifested DDIs as well as clinical adoption of DDI lists based on actual adverse outcomes that can be identified through the implementation of real DDI notification systems is recommended to reduce the incidence of alert fatigue, enhance decision-making for DDI prevention or resolution, and, consequently, contribute to patient safety.
本综述旨在确定住院患者中临床明显药物相互作用(DDI)的发生率。
使用 PubMed、Scopus、Embase、Web of Science 和 Lilacs 数据库,检索 2019 年 6 月前发表的符合特定纳入标准的文章。搜索策略使用与以下领域相关的受控和非受控词汇开发:“药物相互作用”、“临床相关”和“医院”。在本综述中,我们讨论了在医院环境中检测 DDI 的原始观察性研究、提供足够数据以允许我们计算临床明显 DDI 发生率的研究,以及描述在英语、葡萄牙语或西班牙语发表的药物处方或提供 DDI 不良反应报告的研究。
从最初确定的 5999 篇文章中,有 10 篇符合纳入标准。临床明显 DDI 的总发生率为 9.2%(95%CI 4.0-19.7)。6 项研究报告的每位患者平均用药数为 4.0-9.0,总体平均每位患者 5.47±1.77 种药物。纳入研究的质量为中等。用于识别临床明显 DDI 的主要方法是评估病历和病房查房(n=7)。Micromedex®(27.7%)和 Lexi-Comp®(27.7%)在线参考数据库常用于检测 DDI,而没有一项研究为此目的使用超过一个数据库。
本系统综述表明,尽管文献中报告的潜在 DDI 发生率很高,但不到十分之一的患者出现临床明显的药物相互作用。建议使用因果关系工具来识别临床明显的 DDI,以及基于实际不良后果的 DDI 清单来进行临床采用,这些不良后果可以通过实施实际的 DDI 通知系统来识别,以减少警报疲劳的发生率,增强 DDI 预防或解决的决策能力,并最终有助于患者安全。