Prescribing Practices, Polypharmacy, and Drug Interaction Risks in Anticoagulant...

연구 요약

Prescribing Practices, Polypharmacy, and Drug Interaction Risks in Anticoagulant Therapy: Insights from a Secondary Care Hospital.

Journal of clinical medicine 학술지에 발표된 이 연구는 Shareef J, Sridhar SB, Hamouda SA 외 연구팀이 수행하였습니다.

이 연구는 'Prescribing Practices, Polypharmacy, and Drug Interaction Risks in Anticoagulant Therapy: Insights from a Secondary Care Hospital.'에 대한 과학적 분석을 제공합니다.

핵심 내용

Background/Objectives: Blood thinners (anticoagulants) remain the first line pharmacotherapy for the management of cardiovascular and thromboembolic disorders. The increased utilization of polypharmacy, likely driven by the greater burden of comorbidities, elevates the risk of potential drug-drug interactions (pDDIs) and creates a significant challenge in anticoagulant management. The aim of the study was to assess the prescribing trend and impact of polypharmacy and pDDIs in patients receiving anticoagulant drug therapy in a public hospital providing secondary care. Methods: A cross-sectional observational study was undertaken between January-June 2023. Data from electronic medical records of prescriptions for anticoagulants were collected, analyzed for prescribing patterns, and checked for pDDIs using Micromedex database 2.0®. Utilizing binary logistic regression, the relationship between polypharmacy and sociodemographic factors was assessed. Multivariate logistic regression analysis served to uncover determinants linked to pDDIs. Results: Of the total 130 patients, females were predominant (58.46%), with a higher prevalence among those aged 61-90 years. Atrial fibrillation emerged as the main clinical reason and apixaban (51.53%) ranked as the top prescribed anticoagulant in our cohort. Among the 766 pDDIs identified, the majority [401 (52.34%)] were categorized as moderate in severity. Polypharmacy was strongly linked to age (p = 0.001), the Charlson comorbidity index (CCI) (p = 0.040), and comorbidities (p = 0.005) in the binary logistic regression analysis. In the multivariable analysis, the number of medications remain a strong predictor of pDDIs (adjusted OR: 30.514, p = 0.001). Conclusions: Polypharmacy and pDDIs were exhibited in a significant segment of cohort receiving anticoagulant therapy, with strong correlations to age, CCI, comorbidities, and the number of medications. A multidimensional approach involving collaboration among healthcare providers assisted by clinical decision support systems can help optimize the management of polypharmacy, minimize the risks of pDDIs, and ultimately enhance health outcomes.

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