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0 0.5 1 1.5 2+ Progression -251% Improvement Relative Risk Case 6% HCQ for COVID-19  Huh et al.  Prophylaxis Is pre-exposure prophylaxis with HCQ beneficial for COVID-19? Retrospective 44,046 patients in South Korea Higher progression with HCQ (not stat. sig., p=0.11) Huh et al., Int. J. Infectious Diseases, Dec 2020 Favors HCQ Favors control

Association of prescribed medications with the risk of COVID-19 infection and severity among adults in South Korea

Huh et al., International Journal of Infectious Diseases, doi:10.1016/j.ijid.2020.12.041
Dec 2020  
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HCQ for COVID-19
1st treatment shown to reduce risk in March 2020
*, now known with p < 0.00000000001 from 422 studies, recognized in 42 countries.
No treatment is 100% effective. Protocols combine complementary and synergistic treatments. * >10% efficacy in meta analysis with ≥3 clinical studies.
4,000+ studies for 60+ treatments.
Retrospective database analysis with 17 cases for existing HCQ users and 5 severe cases, showing no significant difference for cases and higher risk for severe cases. However, HCQ users are likely systemic autoimmune disease patients and authors do not adjust for the very different baseline risk for these patients. Other research shows that the risk of COVID-19 for systemic autoimmune disease patients is much higher overall, Ferri et al. show OR 4.42, p<0.001 Ferri.
This study is excluded in the after exclusion results of meta analysis: not fully adjusting for the different baseline risk of systemic autoimmune patients.
Study covers metformin and HCQ.
risk of progression, 251.0% higher, RR 3.51, p = 0.11, treatment 5 of 8 (62.5%), control 873 of 2,797 (31.2%), adjusted per study, multivariate.
risk of case, 6.0% lower, RR 0.94, p = 0.82, treatment 17 of 122 (13.9%), control 7,324 of 43,924 (16.7%), adjusted per study, multivariate.
Effect extraction follows pre-specified rules prioritizing more serious outcomes. Submit updates
Huh et al., 19 Dec 2020, retrospective, database analysis, South Korea, peer-reviewed, 8 authors.
This PaperHCQAll
Association of prescribed medications with the risk of COVID-19 infection and severity among adults in South Korea
Kyungmin Huh, Wonjun Ji, Minsun Kang, Jinwook Hong, Gi Hwan Bae, Rugyeom Lee, Yewon Na, Jaehun Jung
International Journal of Infectious Diseases, doi:10.1016/j.ijid.2020.12.041
Objectives: Concerns have been expressed that some drugs may increase susceptibility to SARS-CoV-2 infection. In contrast, other drugs have generated interest as potential therapeutic agents. Methods: All adults aged 18 years who were tested for COVID-19 were included. Exposure was defined as a prescription of study drugs which would have been continued until 7 days prior to test for COVID-19 or later. The outcome measures were the diagnosis of COVID-19 and severe COVID-19. Disease risk score matching and multiple logistic regression was used. Results: Matched claims and testing results were available for 219,961 subjects, of whom 7,341 (3.34%) were diagnosed with COVID-19. Patients were matched to 36,705 controls, and the subset of 878 patients of severe COVID-19 also matched with 1,927 mild-to-moderate patients. Angiotensin receptor blockers were not associated with either the diagnosis of COVID-19 (adjusted OR [aOR], 1.02; 95% confidence interval [CI], 0.90-1.15) or severe disease (aOR, 1.11; 95% CI, 0.87-1.42). The use of hydroxychloroquine was not associated with a lower risk for 0.94; 95% CI, or severe disease (aOR, 3.51; 95% CI,. Conclusions: In this national claims data-based case-control study, no commonly prescribed medications were associated with risk of COVID-19 infection or COVID-19 severity.
Conflict of interest The authors have no conflict of interest to declare. Author contributions Drs. Huh and Jung had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: Huh, Ji, Jung. Acquisition, analysis or interpretation of data: Huh, Ji, Kang, Hong, Bae, Lee, Na, Jung. Drafting of the manuscript: Huh, Ji, Jung. Statistical analysis: Huh, Kang, Na, Jung. Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version, at doi:
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