Cureus · 2021
Potential Psychotropic and COVID-19 Drug Interactions: A Comparison of Integrated Evidence From Six Database Programs.
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Shareef Javedh, Belagodu Sridhar Sathvik, Thomas Sabin, Shariff Atiqulla, Chalasani Sriharsha
Аннотация
Background Drug interactions are a significant issue in mental illnesses and coronavirus disease 2019 (COVID-19) infections. Inconsistency in drug interaction resources makes prescribing challenging for healthcare professionals. To assess the scope, completeness, and consistency of drug-drug interactions (DDIs) between psychotropic and COVID-19 medications in six specific drug information (DI) databases. Methodology For the comparison, six DI resources were used: Portable Electronic Physician Information Database, Micromedex®, Medscape.com, UpToDate®, Drugs.com drug interaction checker, and WebMD.com drug interaction checker. Using the Statistical Package for the Social Sciences (SPSS) software version 27 (IBM Corp., Armonk, NY), the gathered data were examined for scope, completeness, and consistency. Results Scope scores were higher for PEPID© than all the other resources (p < 0.001) for each comparison. PEPID© had better overall completeness scores (median 5, Interquartile range [IQR] 5 to 5; p<0.05 for each comparison), except for Drugs.com (p < 0.05 for each comparison), and were more remarkable for Micromedex® (median 5, IQR 5 to 5). The Fleiss kappa scores among the six different DI sources were poor (k < 0.20, p < 0.05) for the category of information related to clinical effects and level of documentation, moderate agreement (k = 0.4 - 0.6, p < 0.05) for the severity and course of action of DDIs, and fair agreement (k = 0.4 - 0.6, p < 0.05) for mechanism. Conclusion A comprehensive, accurate information among DI resources is essential for healthcare professionals that will significantly impact patient care in the clinical practice. Banking on high-quality resources will help healthcare professionals to make an informed decision while prescribing to avoid inappropriate combinations that can adversely affect patient outcomes.