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Int J Clin Pharmacol Ther ; 62(7): 311-318, 2024 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-38660885

RESUMO

OBJECTIVE: To investigate the incidence of and risk factors for potential drug-drug interactions (DDIs) among elderly patients with corona virus disease 2019 (-COVID-19) in hospital and to explore management strategies to reduce the occurrence of potential DDIs and ensure patient medication safety. MATERIALS AND METHODS: This was a descriptive, retrospective cross-sectional study among patients aged 65 years and older who were hospitalized with COVID-19. Potential DDIs associated with prescriptions containing two or more medicines were analyzed with Lexicomp software, the incidence of DDIs was calculated, recommendations for medication adjustment were formulated, and the χ2-test and binary logistic regression were used to analyze related risk factors. RESULTS: A total of 772 prescriptions were analyzed, 527 (68.26) of which involved 5,732 potential DDIs. The results of this study showed that a total of 152 (28.84%) prescriptions had 270 X risk class potential DDIs (i.e., avoid combining), 313 (59.39%) prescriptions had 1,161 D risk class potential DDIs (i.e., consider therapy modification), and 476 (90.32%) prescriptions had 4,301 C risk class potential DDIs (i.e., monitor therapy). The study findings showed that the total number of drugs (p < 0.001), the length of hospital stay (p < 0.001), and the number of comorbidities (p < 0.001) were risk factors affecting the occurrence of potential DDIs. CONCLUSION: This study identified factors associated with potential DDIs, which can assist in changing medication strategies, preventing adverse drug reactions, and improving clinical efficacy.


Assuntos
Tratamento Farmacológico da COVID-19 , COVID-19 , Interações Medicamentosas , Humanos , Estudos Transversais , Idoso , Estudos Retrospectivos , Masculino , Feminino , Fatores de Risco , COVID-19/epidemiologia , COVID-19/prevenção & controle , Idoso de 80 Anos ou mais , Polimedicação , Hospitalização/estatística & dados numéricos , SARS-CoV-2 , Incidência
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