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Drug-drug interactions and their predictors: Results from Indian elderly inpatients

BACKGROUND: In view of the multiple co-morbidities, the elderly patients receiving drugs are prone to suffer with drug interactions since they receive a greater number of drugs. OBJECTIVE: The study was undertaken to determine the prevalence of drug interactions, as well as their predictors. METHODS...

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Detalles Bibliográficos
Autores principales: Kashyap, Mandavi, D’Cruz, Sanjay, Sachdev, Atul, Tiwari, Pramil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Centro de Investigaciones y Publicaciones Farmaceuticas 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3869634/
https://www.ncbi.nlm.nih.gov/pubmed/24367458
Descripción
Sumario:BACKGROUND: In view of the multiple co-morbidities, the elderly patients receiving drugs are prone to suffer with drug interactions since they receive a greater number of drugs. OBJECTIVE: The study was undertaken to determine the prevalence of drug interactions, as well as their predictors. METHODS: The prescriptions of a total of 1510 inpatients were collected prospectively for 1.5 years from inpatients wards of public tertiary care teaching hospital. All the prescriptions were checked for drug interactions using the Micromedex® Drug-Reax database-2010 and Stockley’s Drug Interactions. Regression analyses sought to determine predictors for the drug interaction. RESULTS: The patients, with the average age of 67.2 ±0.2 years, were prescribed an average of 9.15 ±0.03 medications. It was found that out of 1510 prescriptions of inpatients, 126 (8.3%) prescriptions had one or more than one drug interaction. All the identified interactions were severe in nature. The top most interacting drugs were acetylsalicylic acid and anticoagulant (n=59). The second top most interacting drug combination was clopidogrel and proton pump inhibitors (n=51). The most commonly involved drugs in interactions were C (cardiovascular system) and A (alimentary tract and metabolism). Using multivariate binary logistic regression, multiple drugs (Odds Ratio=4.5; 95% Confidence Interval: - 2.38 -9.47) and multiple diagnoses (Odds Ratio=2.6; 95%CI: -1.40 -5.57) were found to be significant predictors for drug interaction. CONCLUSIONS: The results of this study substantiate the occurrence of severe drug interactions among Indian elderly inpatients. In order to provide safer pharmaceutical care, the active involvement of clinical pharmacists is a potential option.