Background: Few cross-sectional studies involving adults and elderly patients with major DDIs have been conducted in the primary care setting. The study aimed to investigate the prevalence of potential drug-drug interactions (DDIs) in patients treated in primary care.
Methodology/principal Findings: A cross-sectional study involving patients aged 45 years or older was conducted at 25 Basic Health Units in the city of Maringá (southern Brazil) from May to December 2010. The data were collected from prescriptions at the pharmacy of the health unit at the time of the delivery of medication to the patient. After delivery, the researcher checked the electronic medical records of the patient. A total of 827 patients were investigated (mean age: 64.1; mean number of medications: 4.4). DDIs were identified in the Micromedex® database. The prevalence of potential DDIs and major DDIs was 63.0% and 12.1%, respectively. In both the univariate and multivariate analyses, the number of drugs prescribed was significantly associated with potential DDIs, with an increasing risk from three to five drugs (OR = 4.74; 95% CI: 2.90-7.73) to six or more drugs (OR = 23.03; 95% CI: 10.42-50.91). Forty drugs accounted for 122 pairs of major DDIs, the most frequent of which involved simvastatin (23.8%), captopril/enalapril (16.4%) and fluoxetine (16.4%).
Conclusions/significance: This is the first large-scale study on primary care carried out in Latin America. Based on the findings, the estimated prevalence of potential DDIs was high, whereas clinically significant DDIs occurred in a smaller proportion. Exposing patients to a greater number of prescription drugs, especially three or more, proved to be a significant predictor of DDIs. Prescribers should be more aware of potential DDIs. Future studies should assess potential DDIs in primary care over a longer period of time.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3468464 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0047062 | PLOS |
Sci Rep
December 2024
School of Public Health, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China.
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December 2024
Galapagos SASU, Romainville, France.
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CPT Pharmacometrics Syst Pharmacol
December 2024
Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California, USA.
Ritonavir (RTV) is a potent CYP3A inhibitor that is widely used as a pharmacokinetic (PK) enhancer to increase exposure to select protease inhibitors. However, as a strong and complex perpetrator of CYP3A interactions, RTV can also enhance the exposure of other co-administered CYP3A substrates, potentially causing toxicity. Therefore, the prediction of drug-drug interactions (DDIs) and estimation of dosing requirements for concomitantly administered drugs is imperative.
View Article and Find Full Text PDFIdentifying potential drug-drug interactions (DDIs) before clinical use is essential for patient safety yet remains a significant challenge in drug development. We presented DDI-GPT, a deep learning framework that predicts DDIs by combining knowledge graphs (KGs) and pre-trained large language models (LLMs), enabling early detection of potential drug interactions. We demonstrated that DDI-GPT outperforms current state-of-the-art methods by capturing contextual dependencies between biomedical entities to infer potential DDIs.
View Article and Find Full Text PDFBMC Med Res Methodol
December 2024
Center of Clinical Pharmacology, Third Xiangya Hospital, Central South University, Changsha, Hunan, China.
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