Background The clinical presentation of COVID-19 in patients admitted to hospital is heterogeneous. We aimed to determine whether clinical phenotypes of patients with COVID-19 can be derived from clinical data, to assess the reproducibility of these phenotypes and correlation with prognosis, and to derive and validate a simplified probabilistic model for phenotype assignment. Phenotype identification was not primarily intended as a predictive tool for mortality. MethodsIn this study, we used data from two cohorts: the COVID-19@Spain cohort, a retrospective cohort including 4035 consecutive adult patients admitted to 127 hospitals in Spain with COVID-19 between Feb 2 and March 17, 2020, and the COVID-19@HULP cohort, including 2226 consecutive adult patients admitted to a teaching hospital in Madrid between Feb 25 and April 19, 2020. The COVID-19@Spain cohort was divided into a derivation cohort, comprising 2667 randomly selected patients, and an internal validation cohort, comprising the remaining 1368 patients. The COVID-19@HULP cohort was used as an external validation cohort. A probabilistic model for phenotype assignment was derived in the derivation cohort using multinomial logistic regression and validated in the internal validation cohort. The model was also applied to the external validation cohort. 30-day mortality and other prognostic variables were assessed in the derived phenotypes and in the phenotypes assigned by the probabilistic model. Findings Three distinct phenotypes were derived in the derivation cohort (n=2667)-phenotype A (516 [19%] patients), phenotype B (1955 [73%]) and phenotype C (196 [7%])-and reproduced in the internal validation cohort (n=1368)phenotype A (233 [17%] patients), phenotype B (1019 [74%]), and phenotype C (116 [8%]). Patients with phenotype A were younger, were less frequently male, had mild viral symptoms, and had normal inflammatory parameters. Patients with phenotype B included more patients with obesity, lymphocytopenia, and moderately elevated inflammatory parameters. Patients with phenotype C included older patients with more comorbidities and even higher inflammatory parameters than phenotype B. We developed a simplified probabilistic model (validated in the internal validation cohort) for phenotype assignment, including 16 variables. In the derivation cohort, 30-day mortality rates were 2•5% (95% CI 1•4-4•3) for patients with phenotype A, 30•5% (28•5-32•6) for patients with phenotype B, and 60•7% (53•7-67•2) for patients with phenotype C (log-rank test p<0•0001). The predicted phenotypes in the internal validation cohort and external validation cohort showed similar mortality rates to the assigned phenotypes (internal validation cohort: 5•3% [95% CI 3•4-8•1] for phenotype A, 31•3% [28•5-34•2] for phenotype B, and 59•5% [48•8-69•3] for phenotype C; external validation cohort: 3•7% [2•0-6•4] for phenotype A, 23•7% [21•8-25•7] for phenotype B, and 51•4% [41•9-60•7] for phenotype C).Interpretation Patients admitted to hospital with COVID-19 can be classified into three...

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We aimed to identify the key players in the prothrombotic profile of patients with systemic lupus erythematosus (SLE) not mediated by antiphospholipid antibodies, as well as the potential utility of global coagulation tests to characterize hemostasis in these patients. Patients with SLE without antiphospholipid antibodies and without signs of thrombosis were included. The kinetics of clot formation were determined by ROTEM®. Platelet activation markers were determined by flow cytometry. Thrombin generation associated with Neutrophil Extracellular Traps (NETs) and microparticles (MPs) was measured by calibrated automated thrombogram (CAT). The plasma levels of PAI-1 were also determined. ROTEM® showed a procoagulant profile in SLE patients. SLE patients had activated platelets and more leukocyte/platelet aggregates at basal conditions. The plasma PAI-1 and platelet aggregates correlated with several ROTEM® parameters. The thrombin generation associated withthe tissue factor (TF) content of MPs and with NETs was increased. Our results suggest the utility of global tests for studying hemostasis in SLE patients because they detect their procoagulant profile, despite having had neither antiphospholipid antibodies nor any previous thrombotic event. A global appraisal of hemostasis should, if possible, be incorporated into clinical practice to detect the risk of a thrombotic event in patients with SLE and to consequently act to prevent its occurrence.

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