Frequency and predictors of potential drug: Drug interactions in hospitalized patients with Parkinson's diseases

Author:

Aleksić DejanORCID,Stefanović SrđanORCID,Milosavljević MilošORCID,Milosavljević Jovana,Janković SlobodanORCID

Abstract

Introduction: Patients with Parkinson's disease are exposed to higher number of drugs on average than other elderly persons. Levodopa, of the mainstay of Parkinson's disease therapy, is frequently interacting with numerous drugs. Aim: The aim of this study was to identify predictors of potential drug-drug interactions (pDDIs) in hospitalized patients suffering from Parkinson's disease (PD). Material and Methods: This was a academic retrospective cross-sectional study in PD patients hospitalized at the Clinic of Neurology, Clinical Center Kragujevac. Medical records of hospitalized patients during the period 1.1.2017 - 31.12.2019 were analysed. The pDDIs were identified by means of Micromedex andLexi-Interact online softwares, and multivariate regression methods were used to reveal potential predictors of number of pDDIs per patient. Results: Micromedex detected 160 different pDDIs in 77.8% of 72 patients with PD. The most frequent pDDIs were those that involved aspirin (with bisoprolol, sertraline and perindopril). Predictors of pDDIs in general was total number of drugs, while use of antidepressants presented a significant risk factor for major pDDIs. Lexi-Interact revealed 310 pDDIs in 98.6% of patients. The three most common pDDIs were with levodopa (bisoprolol, clonazepam, perindopril). Total number of drugs, number of co-morbidities, hospitalization at the neurodegenerative ward, and use of antipsychotics were identified as the relevant predictors of pDDIs. Lexi-interact software detected significantly more pDDIs than Micromedex (p<0.001). Conclusion: Neurologists should pay special attention when deciding whether to administer new drug to a PD patient with multiple comorbidities, hospitalized in a neurodegenerative ward and/or taking antidepressant or antipsychotic drugs.

Funder

Ministry of Education, Science and Technological Development of the Republic of Serbia

Publisher

Centre for Evaluation in Education and Science (CEON/CEES)

Subject

General Medicine

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