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HCQ study #101 of 320   Meta Analysis
7/23 Late treatment study
Cavalcanti et al., NEJM, July 23, 2020, doi:10.1056/NEJMoa2019014 (Peer Reviewed)
Hydroxychloroquine with or without Azithromycin in Mild-to-Moderate Covid-19
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Late stage RCT of 667 hospitalized patients with up to 14 days of symptoms at enrollment and receiving up to 4 liters per minute supplemental oxygen, not finding a significant effect after 15 days.
Authors note: "the trial cannot definitively rule out either a substantial benefit of the trial drugs or a substantial harm", sample sizes are too small.
The paper uses the terms mild and moderate, however all patients had serious enough disease to be hospitalized, and 14% were actually randomized in the ICU.
The trial had significant protocol deviations and unusually low medication adherence. Randomization resulted in 64.3% male patients (HCQ) vs. 54.2% (control) which may significantly affect results due to the much higher risk for male patients.
Authors note: "our aim was to exclude patients already receiving longer and potentially therapeutic doses of the study treatments" in explanation for why the study protocol was changed to exclude patients with previous use of the medications >24hrs. Analyzing these patients rather than excluding them may have revealed effectiveness with early use as shown in other studies.
The trial initially required enrollment within 48 hours of admission and was changed to remove this requirement, this change is likely to reduce effectiveness because enrollment was moved later, compared to the time the disease became serious enough for hospitalization. Total HCQ dosage 5.6g.
A correction for 17 errors has been published: [1]

Cavalcanti et al., 7/23/2020, Randomized Controlled Trial, Brazil, South America, peer-reviewed, baseline oxygen requirements 41.8%, 14 authors.
risk of death, 16.0% lower, RR 0.84, p = 0.77, treatment 8 of 331 (2.4%), control 5 of 173 (2.9%), HCQ+HCQ/AZ.
risk of hospitalization, 28.0% higher, RR 1.28, p = 0.30, treatment 331, control 173, HCQ+HCQ/AZ.

Effect extraction follows pre-specified rules prioritizing more serious outcomes. For an individual study the most serious outcome may have a smaller number of events and lower statistical signficance, however this provides the strongest evidence for the most serious outcomes when combining the results of many trials.
All 320 studies   Meta Analysis
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