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0 0.5 1 1.5 2+ Mortality 59% Improvement Relative Risk HCQ for COVID-19  Modrák et al.  LATE TREATMENT Is late treatment with HCQ beneficial for COVID-19? Retrospective 213 patients in Czech Republic Lower mortality with HCQ (p=0.038) c19hcq.org Modrák et al., medRxiv, December 2020 Favors HCQ Favors control

Detailed disease progression of 213 patients hospitalized with Covid-19 in the Czech Republic: An exploratory analysis

Modrák et al., medRxiv, doi:10.1101/2020.12.03.20239863
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 421 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.
3,800+ studies for 60+ treatments. c19hcq.org
Retrospective 213 hospitalized patients in Czech Republic showing lower mortality with HCQ. Subject to confounding by indication.
risk of death, 59.0% lower, RR 0.41, p = 0.04, treatment 108, control 105, Cox (single).
Effect extraction follows pre-specified rules prioritizing more serious outcomes. Submit updates
Modrák et al., 4 Dec 2020, retrospective, Czech Republic, preprint, 26 authors.
This PaperHCQAll
Detailed disease progression of 213 patients hospitalized with Covid-19 in the Czech Republic: An exploratory analysis
Martin Modrák, Paul-Christian Bürkner, Tomáš Sieger, Tomáš Slisz, Martina Vašáková, Grigorij Mesežnikov, Luis Fernando Casas-Mendez, Jaromír Vajter, Jan Táborský, Viktor Kubricht, Daniel Suk, Jan Horejsek, Martin Jedlička, Adriana Mifková, Adam Jaroš, Miroslav Kubiska, Jana Váchalová, Robin Šín, Markéta Veverková, Zbyšek Pospíšil, Julie Vohryzková, Rebeka Pokrievková, Kristián Hrušák, Kristína Christozova, Vianey Leos-Barajas, Karel Fišer, Tomáš Hyánek
doi:10.1101/2020.12.03.20239863
We collected a multi-centric retrospective dataset of patients (N = 213) who were admitted to ten hospitals in Czech Republic and tested positive for SARS-CoV-2. The dataset contains baseline patient characteristics, breathing support required, pharmacological treatment received and multiple markers on daily resolution. Patients in the dataset were treated with hydroxychloroquine (N = 108), azithromycin (N = 72), favipiravir (N = 9), convalescent plasma (N = 7), dexamethasone (N = 4) and remdesivir (N = 3), often in combination. Most patients were admitted during the first wave of the epidemic. To explore association between treatments and patient outcomes we performed multiverse analysis, observing how the conclusions change between defensible choices of statistical model, predictors included in the model and other analytical degrees of freedom. Weak evidence to constrain the potential efficacy of azithromycin and favipiravir can be extracted from the data. Additionally, we performed external validation of several proposed prognostic models for Covid-19 severity showing that they mostly perform unsatisfactorily on our dataset.
Conflict of Interest The authors declare that there is no conflict of interest.
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Late treatment
is less effective
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