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 during the early phases of the pandemic in March—October 2020. 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. 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.
【초록키워드】 Dexamethasone, Treatment, convalescent plasma, SARS-CoV-2, Efficacy, pandemic, Hydroxychloroquine, severity, hospital, Remdesivir, Favipiravir, outcome, Characteristics, Patient, statistical model, dataset, predictor, association, marker, Evidence, retrospective, Combination, Analysis, external validation, pharmacological treatment, Support, Czech Republic, prognostic model, early phase, positive, tested, performed, collected, required, treated, baseline, 【제목키워드】 progression, Czech Republic, Exploratory analysis, patients hospitalized,