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0 0.5 1 1.5 2+ Mortality -27% Improvement Relative Risk c19hcq.com Fried et al. HCQ for COVID-19 LATE TREATMENT Favors HCQ Favors control
Fried, 11,721 patient HCQ late treatment study: 27% higher mortality [p=0.001] https://c19p.org/fried
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Patient Characteristics and Outcomes of 11,721 Patients with COVID19 Hospitalized Across the United States
Fried et al., Clinical Infectious Disease, doi:10.1093/cid/ciaa1268
28 Aug 2020    Source   PDF   Share   Tweet
Database analysis of 11,721 hospitalized patients, 4,232 on HCQ. Strong evidence for confounding by indication and compassionate use of HCQ. 24.9% of HCQ patients were on mechanical ventilation versus 12.2% control. Ventilation mortality was 70.5% versus 11.6%.
This study does not adjust for the differences in comorbid conditions and disease severity, and therefore does not make a conclusion. Unadjusted HCQ mortality was 24.8% versus control 19.6%. Adjusting for ventilation only gives us 17.7% HCQ versus 19.6% control (adjusting the HCQ group to have the same proportion of ventilation patients), RR 0.90. Hopefully authors can do a full adjustment analysis. Comorbidities may favor control, while patients remaining in the hospital (5.3%) may favor HCQ (other studies show faster resolution for HCQ patients).
Data inconsistencies have been found in this study, for example 99.4% of patients treated with HCQ were treated in urban hospitals, compared to 65% of untreated patients (Supplemental Table 3), while patients are distributed in a more balanced manner between teaching or not-teaching hospitals, as well as in the most urbanized (Northeast) and less urbanized (Midwest) regions of the United States [academic.oup.com].
risk of death, 27.0% higher, RR 1.27, p < 0.001, treatment 1,048 of 4,232 (24.8%), control 1,466 of 7,489 (19.6%).
Effect extraction follows pre-specified rules prioritizing more serious outcomes. Submit updates
This study is excluded in the after exclusion results of meta analysis: excessive unadjusted differences between groups, substantial unadjusted confounding by indication likely.
Fried et al., 8/28/2020, retrospective, database analysis, USA, North America, peer-reviewed, 11 authors.
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