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基于人群的苯二氮䓬类药物相互作用与意外伤害相关的信号。

Population-based signals of benzodiazepine drug interactions associated with unintentional traumatic injury.

作者信息

Pham Nguyen Thanh Phuong, Soprano Samantha E, Hennessy Sean, Brensinger Colleen M, Bilker Warren B, Miano Todd A, Acton Emily K, Horn John R, Chung Sophie P, Dublin Sascha, Oslin David W, Wiebe Douglas J, Leonard Charles E

机构信息

Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA; Translational Center of Excellence for Neuroepidemiology and Neurology Outcomes Research, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.

Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA; Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.

出版信息

J Psychiatr Res. 2022 Jul;151:299-303. doi: 10.1016/j.jpsychires.2022.04.033. Epub 2022 May 1.

Abstract

Benzodiazepine receptor agonists and related medications, such as Z-drugs and dual orexin receptor antagonists (BZDs), have been associated with unintentional traumatic injury due to their central nervous system (CNS)-depressant effects. Drug-drug interactions (DDIs) may contribute to the known relationship between BZD use and unintentional traumatic injury, yet evidence is still lacking. We conducted high-throughput pharmacoepidemiologic screening using the self-controlled case series design in a large US commercial health insurance database to identify potentially clinically relevant DDI signals among new users of BZDs. We used conditional Poisson regression to estimate rate ratios (RRs) between each co-exposure (vs. not) and unintentional traumatic injury (primary outcome), typical hip fracture (secondary outcome), and motor vehicle crash (secondary outcome). We identified 48 potential DDI signals (1.1%, involving 39 unique co-dispensed drugs), i.e., with statistically significant elevated adjusted RRs for injury. Signals were strongest for DDI pairs involving zolpidem, lorazepam, temazepam, alprazolam, eszopiclone, triazolam, and clonazepam. We also identified four potential DDI signals for typical hip fracture, but none for motor vehicle crash. Many signals have biologically plausible explanations through additive or synergistic pharmacodynamic effects of co-dispensed antidepressants, opioids, or muscle relaxants on CNS depression, impaired psychomotor and cognitive function, and/or somnolence. While other signals that lack an obvious mechanism may represent true associations that place patients at risk of injury, it is also prudent to consider the roles of chance, reverse causation, and/or confounding by indication, which merit further exploration. Given the high-throughput nature of our investigation, findings should be interpreted as hypothesis generating.

摘要

苯二氮䓬受体激动剂及相关药物,如Z类药物和双重食欲素受体拮抗剂(BZDs),因其对中枢神经系统(CNS)的抑制作用,与意外伤害有关。药物相互作用(DDIs)可能导致BZD使用与意外伤害之间的已知关联,但仍缺乏证据。我们在美国一个大型商业健康保险数据库中采用自控病例系列设计进行了高通量药物流行病学筛查,以识别BZDs新使用者中潜在的临床相关DDI信号。我们使用条件泊松回归来估计每种合并用药(与未合并用药相比)与意外伤害(主要结局)、典型髋部骨折(次要结局)和机动车碰撞(次要结局)之间的率比(RRs)。我们识别出48个潜在的DDI信号(1.1%,涉及39种独特的联合配药),即意外伤害的调整后RRs有统计学显著升高。涉及唑吡坦、劳拉西泮、替马西泮、阿普唑仑、艾司佐匹克隆、三唑仑和氯硝西泮的DDI对信号最强。我们还识别出4个典型髋部骨折的潜在DDI信号,但未识别出机动车碰撞的潜在DDI信号。许多信号通过联合配用的抗抑郁药、阿片类药物或肌肉松弛剂对CNS抑制、精神运动和认知功能受损及/或嗜睡的相加或协同药效学作用,具有生物学上合理的解释。虽然其他缺乏明显机制的信号可能代表使患者面临受伤风险的真正关联,但谨慎考虑机遇、反向因果关系和/或指征性混杂的作用也很有必要,这值得进一步探索。鉴于我们调查的高通量性质,研究结果应被解释为生成假设。

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