抗精神病药物与静脉血栓栓塞复发风险的关联:来自日本住院患者数据库数据的回顾性研究。

IF 1.9 Q3 PHARMACOLOGY & PHARMACY
Drugs - Real World Outcomes Pub Date : 2024-03-01 Epub Date: 2023-11-28 DOI:10.1007/s40801-023-00401-2
Hiroyuki Hashimoto, Shinobu Imai, Ryoka Yamashita, Anna Kiyomi, Munetoshi Sugiura
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引用次数: 0

摘要

背景:自从将静脉血栓栓塞添加到抗精神病药物的重大不良反应列表中以来,大约已经过去了十年。然而,只有少数研究调查了抗精神病药物使用与日本人群静脉血栓栓塞之间的关系。目的:我们旨在评估抗精神病药物使用者静脉血栓栓塞复发的风险,并更新日本人群静脉血栓栓塞的证据。方法:对由Medical data Vision Co. Ltd管理的大型日本理赔数据库中的数据进行横断面回顾性分析。2014年10月至2018年9月在急性护理医院发生静脉血栓栓塞的成年患者。使用人口统计学变量进行logistic回归评估静脉血栓栓塞复发的风险。在特定治疗类别中使用抗精神病药物的患者数据也进行了评估。结果:纳入8960例患者(平均年龄69岁;59.2%的女性)。复发性静脉血栓栓塞686例(7.7%)。年轻患者(14天)静脉血栓栓塞复发的风险明显高于短期处方(≤14天)(OR 1.56, 95% CI 1.04-2.34, p = 0.03)。结论:在有静脉血栓栓塞史的患者中,应特别注意年轻患者的复发。如果有静脉血栓栓塞史的患者服用抗精神病药物超过14天,应根据报告结果谨慎用药。需要使用不同的数据库或人群进行进一步的评估,以概括本研究的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Association of Antipsychotic Drugs with the Risk of Recurrent Venous Thromboembolism: A Retrospective Study of Data from a Japanese Inpatient Database.

Background: Approximately a decade has passed since the addition of venous thromboembolism to the list of significant adverse reactions of antipsychotic drugs. However, only a few studies have investigated the relationship between antipsychotic use and venous thromboembolism in the Japanese population.

Purpose: We aimed to evaluate the risk of recurrent venous thromboembolism in users of antipsychotic drugs and update the evidence on venous thromboembolism in the Japanese population.

Methods: A cross-sectional retrospective analysis of data from a large Japanese claims database, managed by Medical Data Vision Co. Ltd., was conducted. Adult patients who experienced venous thromboembolism between October 2014 and September 2018 in acute care hospitals were identified. The risk of recurrent venous thromboembolism was evaluated with logistic regression using demographic variables. The data of patients using antipsychotic drugs within specific therapeutic classes were also evaluated.

Results: We included 8960 patients (mean age, 69 years; 59.2% female). Recurrent venous thromboembolism was observed in 686 patients (7.7%). The risk of recurrent venous thromboembolism was significantly higher in younger patients [< 65 years: reference; 65-74 years: odds ratio (OR) 0.81, 95% confidence interval (CI) 0.66-0.99, p = 0.04; ≥ 75 years: OR 0.77, 95% CI 0.64-0.94, p = 0.01], those with history of surgery (OR 1.39, 95% CI 1.18-1.65, p = 0.01), and anticoagulant users (OR 2.25, 95% CI 1.46-3.48, p = 0.01) and was significantly lower in the presence of comorbidities (OR 0.68, 95% CI 0.58-0.81, p< 0.01) and fractures (OR 0.49, 95% CI 0.26-0.94, p = 0.03). Long-term antipsychotic drug prescriptions (> 14 days) were associated with a higher risk of venous thromboembolism than short-term prescriptions (≤ 14 days) (OR 1.56, 95% CI 1.04-2.34, p = 0.03).

Conclusions: In patients with a history of venous thromboembolism, particular attention should be paid to recurrence in younger patients. If antipsychotic drugs are prescribed for > 14 days to patients with a history of venous thromboembolism, they should be administered carefully, guided by reported findings. Further evaluations using different databases or populations are required to generalize the findings of this study.

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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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