Thiamine for COVID-19

Abstract Background Thiamine is a precursor of the essential coenzyme thiamine pyrophosphate required for glucose metabolism; it improves the immune system function and has shown to reduce the risk of several diseases. The role of thiamine in critically ill septic patient has been addressed in multiple studies; however, it’s role in COVID-19 patients is still unclear. The aim of this study was to evaluate the use of thiamine as an adjunctive therapy on mortality in COVID-19 critically ill patients. Methods This is a two-center, non-interventional, retrospective cohort study for critically ill patients admitted to intensive care units (ICUs) with a confirmed diagnosis of COVID19. All patients aged 18 years or older admitted to ICUs between March 1, 2020, and December 31, 2020, with positive PCR COVID-19 were eligible for inclusion. We investigated thiamine use as an adjunctive therapy on the clinical outcomes in critically ill COVID-19 patients after propensity score matching. Results A total of 738 critically ill patients with COVID-19 who had been admitted to ICUs were included in the study. Among 166 patients matched using the propensity score method, 83 had received thiamine as adjunctive therapy. There was significant association between thiamine use with in-hospital mortality (OR = 0.39; 95% CI 0.19–0.78; P value = 0.008) as well as the 30-day mortality (OR = 0.37; 95% CI 0.18–0.78; P value = 0.009). Moreover, patients who received thiamine as an adjunctive therapy were less likely to have thrombosis during ICU stay [OR (95% CI) 0.19 (0.04–0.88), P value = 0.03]. Conclusion Thiamine use as adjunctive therapy may have potential survival benefits in critically ill patients with COVID-19. Additionally, it was associated with a lower incidence of thrombosis. Further interventional studies are required to confirm these findings.

Abstract Background Thiamine is a precursor of the essential coenzyme thiamine pyrophosphate required for glucose metabolism; it improves the immune system function and has shown to reduce the risk of several diseases. The role of thiamine in critically ill septic patient has been addressed in multiple studies; however, it’s role in COVID-19 patients is still unclear. The aim of this study was to evaluate the use of thiamine as an adjunctive therapy on mortality in COVID-19 critically ill patients. Methods This is a two-center, non-interventional, retrospective cohort study for critically ill patients admitted to intensive care units (ICUs) with a confirmed diagnosis of COVID19. All patients aged 18 years or older admitted to ICUs between March 1, 2020, and December 31, 2020, with positive PCR COVID-19 were eligible for inclusion. We investigated thiamine use as an adjunctive therapy on the clinical outcomes in critically ill COVID-19 patients after propensity score matching. Results A total of 738 critically ill patients with COVID-19 who had been admitted to ICUs were included in the study. Among 166 patients matched using the propensity score method, 83 had received thiamine as adjunctive therapy. There was significant association between thiamine use with in-hospital mortality (OR = 0.39; 95% CI 0.19–0.78; P value = 0.008) as well as the 30-day mortality (OR = 0.37; 95% CI 0.18–0.78; P value = 0.009). Moreover, patients who received thiamine as an adjunctive therapy were less likely to have thrombosis during ICU stay [OR (95% CI) 0.19 (0.04–0.88), P value = 0.03]. Conclusion Thiamine use as adjunctive therapy may have potential survival benefits in critically ill patients with COVID-19. Additionally, it was associated with a lower incidence of thrombosis. Further interventional studies are required to confirm these findings.

The active global SARS-CoV-2 pandemic caused more than 426 million cases and 5.8 million deaths worldwide. The development of completely new drugs for such a novel disease is a challenging, time intensive process. Despite researchers around the world working on this task, no effective treatments have been developed yet. This emphasizes the importance of drug repurposing, where treatments are found among existing drugs that are meant for different diseases. A common approach to this is based on \emph{knowledge graphs}, that condense relationships between entities like drugs, diseases and genes. Graph neural networks (GNNs) can then be used for the task at hand by predicting links in such knowledge graphs. Expanding on state-of-the-art GNN research, Doshi {\sl et al.} recently developed the \drcov \ model. We further extend their work using additional output interpretation strategies. The best aggregation strategy derives a top-100 ranking of 8,070 candidate drugs, 32 of which are currently being tested in COVID-19-related clinical trials. Moreover, we present an alternative application for the model, the generation of additional candidates based on a given pre-selection of drug candidates using collaborative filtering. In addition, we improved the implementation of the \drcov \ model by significantly shortening the inference and pre-processing time by exploiting data-parallelism. As drug repurposing is a task that requires high computation and memory resources, we further accelerate the post-processing phase using a new emerging hardware --- we propose a new approach to leverage the use of high-capacity Non-Volatile Memory for aggregate drug ranking.