Background: Multiple drug therapies are commonly used to achieve a desired therapeutic goal, especially in hospitalized patients. However, drug-drug interactions might occur and threaten the patients' safety.
Objective: This study aims to assess the prevalence and severity of potential drug-drug interactions (PDDIs) in the internal medicine ward at Soba Teaching Hospital.
Methods: A retrospective cross-sectional hospital-based study was carried out in the internal medicine ward at Soba Teaching Hospital from June 2021 to December 2021. The data was collected from patients' medical records. PDDIs were identified using Lexicomp drug interaction software.
Results: A total of 377 patients were included in this study, and overall prevalence of PDDIs was 62.9%. We have identified 989 potential DDIs and 345 pairs of interacting drugs, the mean of the PDDIs per patient was 4.17 ± 4.079. Among 345 PDDIs most were of moderate interactions 70.1% (n=242) followed by Minor interactions 19.1% (n=66). The most common type of interaction was of category C representing 63.5% (n=219). A significant association was observed between the occurrence of PDDIs with patients' age, presence of chronic diseases, length of hospital stay, and number of medications received by the patients.
Conclusion: Drug-drug interactions were highly prevalent in the internal medicine ward. Therefore, certain attempts are required to increase the awareness of the physicians about these interactions and minimize their occurrence.
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http://dx.doi.org/10.2147/DHPS.S436458 | DOI Listing |
J Oncol Pharm Pract
January 2025
Department of Pharmacy, Shaukat Khanum Memorial Cancer Hospital and Research Centre, Lahore, Pakistan.
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Navarra University Hospital, Pamplona, Navarra, Spain. Electronic address:
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View Article and Find Full Text PDFInterdiscip Sci
January 2025
School of Computer Science, Qufu Normal University, Rizhao, 276826, China.
Combination therapy, which synergistically enhances treatment efficacy and inhibits disease progression through the combined effects of multiple drugs, has emerged as a mainstream approach for treating complex diseases and alleviating symptoms. However, drug-drug interactions (DDIs) can sometimes lead to adverse reactions, potentially endangering lives. Therefore, developing efficient and accurate DDI prediction methods is crucial for elucidating drug mechanisms and preventing side effects.
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February 2025
Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida College of Pharmacy, Gainesville, Florida, USA.
Tramadol, the 41st most prescribed drug in the United States in 2021 is a prodrug activated by CYP2D6, which is highly polymorphic. Previous studies showed enzyme-inhibitor affinity varied between different CYP2D6 allelic variants with dextromethorphan and atomoxetine metabolism. However, no study has compared tramadol metabolism in different CYP2D6 alleles with different CYP2D6 inhibitors.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Industrial and Molecular Pharmaceutics, Purdue University, West Lafayette, Indiana 47907, United States.
Drug-drug interaction can lead to diminished therapeutic effects or increased toxicity, posing significant risks, especially in polypharmacy, and cytochrome P450 plays an indispensable role in this interaction. Cytochrome P450, responsible for the metabolism and detoxification of most drugs, metabolizes about 90% of Food and Drug Administration-approved drugs, making early detection of potential drug-drug interactions. Over the years, in-silico modeling has become a valuable tool for predicting drug-drug interactions.
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