CLIA-certified laboratories were enrolled through the IMPACT biorepository study 15. In the IMPACT study, biospecimens including blood, nasopharyngeal swabs, saliva, urine and stool samples were collected at study enrolment (baseline denotes the first time point) and longitudinally on average every 3 to 7 days (serial time points). The detailed demographics and clinical characteristics of these 98 participants are shown in Extended Data Table 1. Plasma and peripheral blood mononuclear cells (PBMCs) were isolated from whole blood, and plasma was used for titre measurements of SARS-CoV-2 spike S1 protein-specific IgG and IgM antibodies (anti-S1-IgG and-IgM) and cytokine or chemokine measurements. Freshly isolated PBMCs were stained and analysed by flow cytometry 15. We obtained longitudinal serial time-point samples from a subset of these 98 study participants (n = 48; information in Extended Data Table 1). To compare the immune phenotypes between sexes, two sets of data analyses were performed in parallel-baseline and longitudinal, as described below. As a control group, healthcare workers (HCWs) from Yale-New Haven Hospital were enrolled who were uninfected with COVID-19. Demographics and background information for the HCW group and the demographics of HCWs for cytokine assays and flow cytometry assays for the primary analyses are in Extended Data Table 1. Demographic data, time-point information of the samples defined by the days from the symptom onset (DFSO) in each patient, treatment information, and raw data used to generate figures and tables is in Supplementary Table 1. Baseline analysis The baseline analysis was performed on samples from the first time point of patients who met the following criteria: not in intensive care unit (ICU), had not received tocilizumab, and had not received high doses of corticosteroids (prednisone equivalent of more than 40 mg) before the first sample collection date. This patient group, cohort A, consisted of 39 patients (17 male and 22 female) (Extended Data Tables 1, 2). Intersex and transgender individuals were not represented in this study. Figures 1-4 represent analyses of baseline raw values obtained from patients in cohort A. In cohort A patients, male and female patients were matched in terms of age, body mass index (BMI), and DFSO at the first time point sample collection (Extended Data Fig. 1a). However, there were significant differences in age and BMI between HCW controls and patients (patients had higher age and BMI values) (Extended Data Table 1), and therefore an age-and BMI-adjusted difference-indifferences analysis was also performed in parallel (Extended Data Table 3). Longitudinal analysis As parallel secondary analyses, we performed longitudinal analysis on a total patient cohort (cohort B) to evaluate the difference in immune response over the course of the disease between male and female patients. Cohort B included all patient samples from cohort A (including several time-point samples from the cohort A patients) as well as an additional 59 patients who d...

This is a PDF file of a peer-reviewed paper that has been accepted for publication. Although unedited, the content has been subjected to preliminary formatting. Nature is providing this early version of the typeset paper as a service to our authors and readers. The text and figures will undergo copyediting and a proof review before the paper is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers apply.

Objective The goal of this study was to develop a prognostic tool of early hospital respiratory failure among emergency department (ED) patients admitted with COVID-19. Methods This was an observational, retrospective cohort study from a nine ED health system in the United States of admitted adult patients with SARS-CoV-2 (COVID-19) and a ≤ 6 L/min oxygen requirement. We sought to predict respiratory failure within 24 hours of admission as defined by oxygen requirement of ≥ 10 L/min, any high-flow device, non-invasive or invasive ventilation, or death. Predictive models were compared to the Elixhauser comorbidity index, quick serial organ failure assessment (qSOFA), and the CURB-65 pneumonia severity score. Results During the study period from March 1 to April 27, 2020, 1,792 patients were admitted with COVID-19, 620 (35%) of whom had respiratory failure in the ED. Of the remaining 1,172 admitted patients, 144 (12.3%) met the composite endpoint within the first 24 hours of hospitalization. Using area under receiver-operating characteristic curves, we compared the performance of a novel bedside scoring system, the quick COVID-19 severity index (qCSI) composed of respiratory rate, oxygen saturation, and oxygen flow rate (mean [95% CI]) (0.81 [0.73-0.89]), a machine- learning model, the COVID-19 severity index (0.76 [0.65-0.86]), to the Elixhauser mortality index (0.61 [0.51-0.70])), CURB-65 (0.50 [0.40-0.60]), and qSOFA (0.59 [0.50-0.68]). A low qCSI score (≤ 3) had a sensitivity of 0.79 [0.65- 0.93] and specificity of 0.78 [0.72-0.83] in predicting respiratory decompensation with a less than 5% risk of outcome in the validation cohort. Conclusions A significant proportion of admitted COVID-19 patients progress to respiratory failure within 24 hours of admission. These events are accurately predicted using bedside respiratory exam findings within a simple scoring system.