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本文引用的文献

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Clin Pharmacol Ther. 2021 Oct;110(4):1011-1017. doi: 10.1002/cpt.2314. Epub 2021 Jun 27.
2
Acceptance of Drug Use Mediates Future Hard Drug Use Among At-Risk Adolescent Marijuana, Tobacco, and Alcohol Users.药物使用的接受程度在高危青少年大麻、烟草和酒精使用者中预示着未来硬毒品的使用。
Prev Sci. 2021 Jul;22(5):545-554. doi: 10.1007/s11121-020-01165-9. Epub 2020 Sep 15.
3
Screening to identify signals of opioid drug interactions leading to unintentional traumatic injury.筛选以识别阿片类药物相互作用导致意外伤害的信号。
Biomed Pharmacother. 2020 Oct;130:110531. doi: 10.1016/j.biopha.2020.110531. Epub 2020 Jul 30.
4
Bias in case-crossover studies of medications due to persistent use: A simulation study.因持续用药导致的药物病例交叉研究中的偏倚:一项模拟研究。
Pharmacoepidemiol Drug Saf. 2020 Sep;29(9):1079-1085. doi: 10.1002/pds.5031. Epub 2020 Jun 16.
5
ICD-10-CM-Based Definitions for Emergency Department Opioid Poisoning Surveillance: Electronic Health Record Case Confirmation Study.基于 ICD-10-CM 的急诊阿片类药物中毒监测定义:电子健康记录病例确认研究。
Public Health Rep. 2020 Mar/Apr;135(2):262-269. doi: 10.1177/0033354920904087. Epub 2020 Feb 10.
6
Role of Opioid-Involved Drug Interactions in Chronic Pain Management.阿片类药物相关药物相互作用在慢性疼痛管理中的作用。
J Am Osteopath Assoc. 2019 Dec 1;119(12):839-847. doi: 10.7556/jaoa.2019.136.
7
A Case-Crossover-Based Screening Approach to Identifying Clinically Relevant Drug-Drug Interactions in Electronic Healthcare Data.基于病例交叉研究的电子医疗数据中临床相关药物相互作用的筛选方法
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When and How Can Real World Data Analyses Substitute for Randomized Controlled Trials?真实世界数据分析何时以及如何能够替代随机对照试验?
Clin Pharmacol Ther. 2017 Dec;102(6):924-933. doi: 10.1002/cpt.857. Epub 2017 Sep 25.
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Drug Alcohol Depend. 2017 Sep 1;178:501-511. doi: 10.1016/j.drugalcdep.2017.05.047. Epub 2017 Jul 4.
10
Matching Weights to Simultaneously Compare Three Treatment Groups: Comparison to Three-way Matching.匹配权重以同时比较三个治疗组:与三重匹配的比较。
Epidemiology. 2017 May;28(3):387-395. doi: 10.1097/EDE.0000000000000627.

长期接受阿片类药物治疗的患者在开始使用抗生素治疗尿路感染时发生阿片类药物过量的比较风险。

Comparative risk of opioid overdose in patients who initiated antibiotics for urinary tract infection while on long-term opioid therapy.

作者信息

Khan Nazleen F, Bykov Katsiaryna, Glynn Robert J, Vine Seanna M, Gagne Joshua J

机构信息

Department of Epidemiology, Harvard T.H. Chan School of Public Health.

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School.

出版信息

Am J Epidemiol. 2025 Mar 4;194(3):674-679. doi: 10.1093/aje/kwae248.

DOI:10.1093/aje/kwae248
PMID:39098822
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12187061/
Abstract

Sulfamethoxazole/trimethoprim, a commonly used antibiotic, has been associated with opioid overdose in patients with long-term opioid use, based on a prior drug-drug interaction screening study. To evaluate whether this finding represents a false-positive signal due to potential confounding, we assessed the safety of sulfamethoxazole/trimethoprim relative to 2 comparable antibiotic treatments in patients receiving long-term opioid therapy. We used data from 4 large administrative claims databases spanning 2000-2019. The study population was restricted to patients aged 18 years or older with urinary tract infection and at least 90 days of continuous prescription opioid use who initiated sulfamethoxazole/trimethoprim, nitrofurantoin, or fluoroquinolone therapy. We used propensity score matching weights to adjust for confounding and Cox proportional hazards models to estimate weighted hazard ratios (HRs) and 95% CIs in a 30-day intention-to-treat analysis. Cumulative 30-day opioid overdose risk ranged between 0.04% and 0.12% across databases and did not differ between antibiotics. Relative to sulfamethoxazole/trimethoprim, the weighted HR of opioid overdose was 1.09 (95% CI, 0.79-1.50) for nitrofurantoin and 0.94 (95% CI, 0.68-1.31) for fluoroquinolones. Potential safety signals identified in high-throughput screening studies, especially for medication combinations with limited biologic plausibility of drug-drug interaction and high frequency of use, should be interpreted with caution. .

摘要

根据先前的药物相互作用筛查研究,常用抗生素磺胺甲恶唑/甲氧苄啶与长期使用阿片类药物的患者阿片类药物过量有关。为了评估这一发现是否由于潜在的混杂因素而代表假阳性信号,我们评估了磺胺甲恶唑/甲氧苄啶相对于另外两种可比抗生素治疗对接受长期阿片类药物治疗患者的安全性。我们使用了2000年至2019年期间4个大型行政索赔数据库的数据。研究人群仅限于年龄在18岁及以上、患有尿路感染且至少连续90天使用阿片类药物处方并开始使用磺胺甲恶唑/甲氧苄啶、呋喃妥因或氟喹诺酮治疗的患者。我们使用倾向评分匹配权重来调整混杂因素,并使用Cox比例风险模型在30天意向性分析中估计加权风险比(HR)和95%置信区间(CI)。各数据库中30天阿片类药物过量累积风险在0.04%至0.12%之间,且抗生素之间无差异。相对于磺胺甲恶唑/甲氧苄啶,呋喃妥因的阿片类药物过量加权HR为1.09(95%CI,0.79-1.50),氟喹诺酮为0.94(95%CI,0.68-1.31)。在高通量筛查研究中确定的潜在安全信号,尤其是对于药物相互作用生物学合理性有限且使用频率高的药物组合,应谨慎解读。