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All Studies   Meta Analysis   Recent: 
0 0.5 1 1.5 2+ Mortality -70% Improvement Relative Risk c19hcq.org Sands et al. HCQ for COVID-19 LATE TREATMENT Favors HCQ Favors control
No clinical benefit in mortality associated with hydroxychloroquine treatment in patients with COVID-19
Sands et al., International Journal of Infectious Diseases, doi:/10.1016/j.ijid.2020.12.060
1 Jan 2021    Source   PDF   Share   Tweet
Retrospective database analysis of 1,669 patients in the US showing OR 1.81, p = 0.01. Confounding by indication is likely.
COVID-19 was determined via PCR+ results, therefore authors include patients asymptomatic for COVID-19, but in the hospital for other reasons. While authors adjust for severity, the method used is very poor. 93.5% of patients are classified as "mild", which is patients with no documented care in a critical care unit within 8 hours of admission. Therefore almost all patients are in the same category, and those in a different category may be due to symptoms unrelated to COVID-19. Lower bias toward male patients in the control group also agrees with the hypothesis that the control group is made up of more people that were in hospital for another reason.
Since the analysis covers the initial period of the pandemic in the USA, it is likely that HCQ was used more often earlier in the analysis period when treatment protocols were considerably worse. It's unclear why the analysis only considers patients up to April 27, when the manuscript was submitted in October.
For other issues see [ijidonline.com].
risk of death, 69.9% higher, RR 1.70, p = 0.01, treatment 101 of 973 (10.4%), control 56 of 696 (8.0%), odds ratio converted to relative risk.
Effect extraction follows pre-specified rules prioritizing more serious outcomes. Submit updates
This study is excluded in the after exclusion results of meta analysis: includes PCR+ patients that may be asymptomatic for COVID-19 but in hospital for other reasons; substantial unadjusted confounding by indication likely.
Sands et al., 1 Jan 2021, retrospective, database analysis, USA, peer-reviewed, 10 authors.
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