Fig. 3: Stratified survival analysis.

Stratification of patients in a. the held-out Optum test cohort (left, 14,215 patients) and b. the external TriNetX test cohort (right, 5005 patients) according to their assigned CovEWS score over time (in hours since COVID-19 diagnosis) into those patients that were assigned a CovEWS score below 60 (orange, bottommost), from 60 to 69 (deep blue), 70 to 79 (green), 80 to 89 (turquoise), and 90 to 100 (red, topmost). Shaded areas indicate 95% CIs calculated on the logarithmic scale from the standard errors of the Kaplan–Meier estimator with the centre values corresponding to the the Kaplan–Meier estimates⁴⁴. Note that the five strata and their respective limits were chosen for clarity of visualisation—other strata are possible, and may, depending on context, have better clinical utility. Rows show time-varying survival probabilities (top row), the number of patients (centre row), and the cumulative number of mortality events observed (bottom row) for patients in each stratum of assigned CovEWS scores. Steeper curves indicate that more patients died while assigned a CovEWS score in the respective stratum. In contrast to traditional survival curves, cohorts as defined by strata of CovEWS scores are not static over time, and patients move between the stratified groups as they are assigned lower or higher CovEWS scores in response to their status improving or deteriorating, respectively. The results showed that CovEWS enables effective stratification of patients into risk groups over the course of their disease, as patients that were assigned a higher CovEWS score were more likely to die over time on both test cohorts while maintaining separation between the stratified cohorts.