Statistical analysis
LME, EVLWi, SD
Statistical analyses were performed in the intention-to-treat (ITT) population of 66 randomized patients. An overview of predefined statistical tests is provided in the Statistical Analysis Plan (Additional file The primary endpoint was presented as mean ± SD and analyzed using a two-tailed t-test. In addition, an analysis of covariance (ANCOVA) was performed. For the primary endpoint, data imputation was performed in case of missing EVLWi values. In case of missing values on day 1, the data from day 2 was carried backwards. In case of missing values at day 4, the value was imputed by carrying the day 3 value forward, or, in case of no day 3 measurement, carrying the day 5 value backwards. For sensitivity analysis, the primary endpoint was analyzed in the ITT population without data imputation. In addition, a per-protocol analysis of the primary endpoint was performed in all patients missing ≤ 1 study drug dose in the first four study days and who had no missing EVLWi measurements on days 1 and 4.28-day mortality was analyzed using a Cox proportional hazards model and visualized using a Kaplan–Meier curve. EVLWi, PVPi, ventilation parameters, plasma biomarkers and clinical laboratory outcomes over the first seven days were analyzed using linear mixed effect (LME) models, with time point, randomization group and their interaction term as fixed effects, study ID as random intercept and, in case of baseline imbalances, relevant covariates. For LME analyses, logarithmic transformation was applied to non-normally distributed data.We performed a posthoc analysis applying the three biomarker-derived subphenotypes identified in the CounterCOVID trial [