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Pharmaceutical and Biomedical Sciences Journal (PBSJ)Pharmaceutical and Biomedical Sciences Journal (PBSJ)

Diabetes mellitus is one of the common comorbidities found in COVID-19 patients. The use of large amounts of medication (polypharmacy) in COVID-19 patients with comorbid diabetes mellitus can increase the possibility of drug interactions. The study aimed to determine the potential drug-drug interactions and it is the relationship with clinical outcomes in COVID-19 patients with comorbid type 2 diabetes mellitus at the General Hospital in South Tangerang City. The study was a retrospective study conducted in the hospital by using patients medical records from January-December 2021. Potential drug-drug interactions were analyzed by using the software, Medscape, and Drugs.com. The 97 patients met the inclusion and exclusion criteria. The results of the study were found in 40 patients who experience drug interactions with COVID-19 drugs and antidiabetics (58.2%), the majority of them are in moderate severity degree (78.5%), major severity degree (21.5%), with pharmacodynamic mechanism (100%). There is no significant relationship between drug interactions and clinical outcomes of patients (P>0.05). The interactions found were all pharmacodynamic, although there was no significant relationship to clinical outcomes, therapeutic monitoring was still required.

The study concluded that a significant proportion of COVID-19 patients with type 2 diabetes mellitus experienced drug interactions, predominantly of moderate severity and pharmacodynamic in nature.However, no significant association was found between these drug interactions and clinical outcomes.Despite the lack of a statistically significant relationship, the study emphasizes the importance of continued therapeutic monitoring to mitigate potential risks associated with these interactions.

Penelitian lebih lanjut perlu dilakukan untuk mengeksplorasi dampak spesifik dari interaksi obat farmakodinamik pada hasil klinis pasien COVID-19 dengan diabetes mellitus tipe 2, dengan mempertimbangkan variasi genetik yang dapat memengaruhi respons obat. Selain itu, studi prospektif yang melibatkan pemantauan kadar obat secara berkala dan penilaian fungsi organ dapat memberikan wawasan yang lebih mendalam tentang mekanisme interaksi obat dan dampaknya terhadap efikasi dan keamanan terapi. Terakhir, pengembangan dan validasi algoritma berbasis kecerdasan buatan untuk memprediksi potensi interaksi obat pada pasien COVID-19 dengan komorbiditas, serta memberikan rekomendasi dosis yang dipersonalisasi, dapat meningkatkan kualitas perawatan dan mengurangi risiko efek samping obat. Penelitian-penelitian ini diharapkan dapat memberikan kontribusi signifikan dalam optimalisasi terapi obat pada pasien COVID-19 dengan diabetes mellitus, sehingga meningkatkan hasil klinis dan kualitas hidup mereka.

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