Assessment of potential drug interactions among psychiatric inpatients receiving antipsychotic therapy of a secondary care hospital, United Arab Emirates

• Main Authors: Haneen A. R. Aburamadan (Author), Sathvik Belagodu Sridhar (Author), Talaat Matar Tadross (Author)
• Format: Book
• Published: Wolters Kluwer Medknow Publications, 2021-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2231-4040; 0976-2094; 10.4103/japtr.JAPTR_110_20
• Keywords: antipsychotics drug interactions; drug-drug interaction; drug-ethanol interaction; drug-tobacco interaction; Therapeutics. Pharmacology; RM1-950; Pharmacy and materia medica; RS1-441
• Source: Journal of Advanced Pharmaceutical Technology & Research, Vol 12, Iss 1, Pp 45-51 (2021)

The majority of the antipsychotic drugs are also known to interact with other co-administered drugs. Drug-drug interaction (DDI) reports among patients receiving antipsychotic medications are common. The study aims to identify the potential drug-drug, drug-tobacco, and drug-ethanol interactions associated with antipsychotics and significant predictors of potential DDIs (pDDIs). A prospective observational study was conducted among psychiatric inpatients receiving antipsychotic therapy and met the inclusion criteria that were reviewed for the presence of pDDIs using DRUGDEX-Micromedex database 2.0. The identified pDDIs were graded according to the severity and type of documentation. A total of 110 patients had a minimum of a single interaction, and the overall frequency of pDDIs reported was 64.7%. Of 158 pDDIs, 92 interactions (58.2%) were of major severity, while 66 interactions were of moderate severity (41.8%). Olanzapine with valproate (40 [25.3%]) was the most commonly documented pDDIs, followed by risperidone with valproate (20 [12.6%]). Olanzapine with tobacco (20 [69%]) was the most common drug-tobacco interaction. Simultaneously, olanzapine with ethanol was the most common potential drug and ethanol interaction (9 [50%]). Variables such as the number of drugs and polypharmacy statistically significantly predicted pDDIs (F[7, 162] = 8.155, P < 0.05, R2 = 0.26). Knowing the severity of different pDDIs will help clinicians and prescribers monitor patient safety through regular monitoring for interactions and adverse drug effects in future. The number of medications and polypharmacy was found to be the most significant predictor of pDDIs.