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本文引用的文献

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PLoS One. 2023 Jan 24;18(1):e0276277. doi: 10.1371/journal.pone.0276277. eCollection 2023.
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Combined Multimorbidity and Polypharmacy Patterns in the Elderly: A Cross-Sectional Study in Primary Health Care.老年人合并多种疾病和多重用药模式:初级卫生保健中的横断面研究。
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Neurol Res. 2021 Dec;43(12):1023-1030. doi: 10.1080/01616412.2021.1948767. Epub 2021 Jul 7.
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Analysis of interaction risks of patients with polypharmacy and the pharmacist interventions performed to solve them-A multicenter descriptive study according to medication reviews in Hungarian community pharmacies.多药治疗患者的相互作用风险分析及药师干预措施以解决这些问题-一项基于匈牙利社区药房药物重整的多中心描述性研究。
PLoS One. 2021 Jun 22;16(6):e0253645. doi: 10.1371/journal.pone.0253645. eCollection 2021.
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Ir J Med Sci. 2020 Aug;189(3):1123-1125. doi: 10.1007/s11845-019-02155-9. Epub 2019 Dec 5.
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10
2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk.2019年欧洲心脏病学会/欧洲动脉粥样硬化学会血脂异常管理指南:通过血脂修饰降低心血管风险
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血脂异常门诊患者潜在药物相互作用的危险因素

Risk Factors for Potential Drug-Drug Interactions in Outpatients with Dyslipidemia.

作者信息

Lalatović Ninoslava, Pantović Snežana, Nedović-Vuković Mirjana, Kostić Marina

机构信息

Faculty of Medicine, University of Montenegro, Podgorica, Montenegro.

Department of Health Statistics and Informatics, Center for Health System Development, Institute of Public Health, Podgorica, Montenegro.

出版信息

Iran J Public Health. 2023 Jul;52(7):1466-1475. doi: 10.18502/ijph.v52i7.13248.

DOI:10.18502/ijph.v52i7.13248
PMID:37593497
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10430412/
Abstract

BACKGROUND

Patients with dyslipidemia are usually multimorbid and require polypharmacy. Therefore, it is important to identify potential drug-drug interactions (pDDIs) in time to prevent their consequences. We aimed to identify and analyze risk factors contributing to their occurrence to guide health professionals.

METHODS

A prospective cross-sectional study of 216 outpatients with dyslipidemia was conducted from May 2021 to April 2022 in Podgorica, the capital of Montenegro. pDDIs were identified using Medscape, Epocrates, and Drugs online interaction checkers. Multivariate regression analysis was performed to evaluate the potential predictors of interactions.

RESULTS

pDDIs were detected in 212 (98.1%) participants, whereas pDDIs with high clinical significance were detected in 25.46%, 40.74%, and 58.8% of subjects by Drugs, Epocrates, and Medscape, respectively. Polypharmacy emerged as a risk factor for the occurrence of pDDIs in all three checkers in each category of clinical significance. The use of non-steroidal anti-inflammatory drugs and antiplatelet drugs contributes to the incidence of severe pDDIs B=1.014, 95%CI 0.681-1.346, =0.000 and B=0.492, 95%CI 0.286-0.698, =0.000, by Epocrates and Medscape respectively. The number of prescribers per patient was a protective factor against moderate pDDI B= -0.858, 95%CI -1.572-(-0.144), =0.019 and B= -0.956, 95%CI -1.671-(-0.241), =0.009, by Medscape and Epocrates, respectively, but a risk factor for the occurrence of minor pDDIs B=0.373, 95%CI 0.033-0.712 =0.032 and B=0.143, 95%CI 0.042-0.244, =0.006, by the same checkers.

CONCLUSION

Knowledge of the risk factors contributing to the occurrence of pDDIs is important for the development and implementation of strategies for their prevention, and given the high prevalence of dyslipidemia, understanding these factors seems crucial nowadays.

摘要

背景

血脂异常患者通常患有多种疾病,需要联合使用多种药物。因此,及时识别潜在的药物相互作用(pDDIs)以预防其后果非常重要。我们旨在识别和分析导致其发生的风险因素,以指导卫生专业人员。

方法

2021年5月至2022年4月在黑山首都波德戈里察对216名血脂异常门诊患者进行了一项前瞻性横断面研究。使用Medscape、Epocrates和在线药物相互作用检查器识别pDDIs。进行多变量回归分析以评估相互作用的潜在预测因素。

结果

212名(98.1%)参与者检测到pDDIs,而根据Drugs、Epocrates和Medscape分别在25.46%、40.74%和58.8%的受试者中检测到具有高临床意义的pDDIs。在每种临床意义类别中,联合用药在所有三种检查器中均成为pDDIs发生的风险因素。使用非甾体抗炎药和抗血小板药物分别导致Epocrates和Medscape严重pDDIs发生率升高(B=1.014,95%CI 0.681-1.346,P=0.000和B=0.492,95%CI 0.286-0.698,P=0.000)。每位患者的开方医生数量是预防中度pDDI的保护因素(Medscape和Epocrates的B分别为-0.858,95%CI -1.572-(-0.144),P=0.019和B=-0.956,95%CI -1.671-(-0.241),P=0.009),但根据相同检查器,是轻微pDDIs发生的风险因素(B=0.373,95%CI 0.033-0.712,P=0.032和B=0.143,95%CI 0.042-0.244,P=0.006)。

结论

了解导致pDDIs发生的风险因素对于制定和实施预防策略很重要,鉴于血脂异常的高患病率,如今了解这些因素似乎至关重要。