Abstract
Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19), has spread around the world, spurring the biomedical community to find and create antiviral therapies. The agent remdesivir, which has undergone a protracted and tortuous developmental path, is one potential therapeutic strategy now being assessed in several clinical trials. A broad-spectrum antiviral drug called remdesivir has already shown antiviral effects against filoviruses. Remdesivir was suggested as an exploratory medicine early in the pandemic because in vitro tests showed it to have antiviral effectiveness against SARS-CoV-2. Methods We conducted a retrospective cohort study that examined patient data captured through an electronic medical system at the Abu Arish General Hospital between 2021 and 2022. Data analysis was performed with SPSS version 25.0 (Armonk, NY: IBM Corp.). Results A total of 88 patients were included in this study. With the usage of remdesivir, our risk model is able to forecast adverse events and the case fatality rate. In contrast to D-dimer and c-reactive proteins, we showed that alanine transaminase (ALT), aspartate aminotransferase (AST), serum creatinine, and hemoglobin are relevant variables. Conclusion Our risk model can predict the adverse reactions and case fatality rate with the use of remdesivir. We demonstrated ALT, AST, serum creatinine, and hemoglobin as important variables rather than D-dimer and c-reactive proteins.