Potential drug-drug interactions and their associated factors in hospitalized COVID-19 patients with comorbidities

BACKGROUND: Hospitalized COVID-19 patients with comorbidities receive more complex drug therapy. This increases the probability of potential drug-drug interactions (pDDIs). Studies on pDDIs in hospitalized patients with COVID-19 in countries with limited resources like Indonesia during the later period of the disease are still limited. This study aims to identify the pattern of pDDIs in hospitalized COVID-19 patients with comorbidities and their associated factors, especially in the second wave of the disease in Indonesia. METHODS: This study was a longitudinal-retrospective study observing hospitalized COVID-19 patients with comorbidities using medical record data in June–August 2021 at a public hospital in a region in Indonesia. pDDIs were identified using the Lexicomp(®) database. Data were descriptively analyzed. Factors associated with important pDDIs were analyzed in multivariate logistic regression model. RESULTS: A total of 258 patients with a mean age of 56.99 ± 11.94 years met the inclusion criteria. Diabetes mellitus was the most common comorbidity experienced by 58.14% of the patients. More than 70% of the patients had one comorbidity and the average number of administered drugs was 9.55 ± 2.71 items per patient. Type D pDDIs, which required modification of therapeutic regimens, amounted to 21.55% of the total interactions. Only the number of drugs was significantly and independently associated with type D pDDIs (adjusted odds ratio 1.47 [1.23–1.75], p < 0.01). CONCLUSION: The drugs involved in the pDDIs of hospitalized COVID-19 patients with comorbidities may differ depending on the disease periods, hospital settings, or countries. This study was small, single center, and of short duration. However, it may give a glimpse of important pDDIs during the delta variant of COVID-19 in a similar limited-resource setting. Further studies are needed to confirm the clinical significance of these pDDIs.