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IMPORTANCEThe National COVID Cohort Collaborative (N3C) is a centralized, harmonized, highgranularity electronic health record repository that is the largest, most representative COVID-19 cohort to date. This multicenter data set can support robust evidence-based development of predictive and diagnostic tools and inform clinical care and policy.OBJECTIVES To evaluate COVID-19 severity and risk factors over time and assess the use of machine learning to predict clinical severity. DESIGN, SETTING, AND PARTICIPANTSIn a retrospective cohort study of 1 926 526 US adults with SARS-CoV-2 infection (polymerase chain reaction >99% or antigen <1%) and adult patients without SARS-CoV-2 infection who served as controls from 34 medical centers nationwide between January 1, 2020, and December 7, 2020, patients were stratified using a World Health Organization COVID-19 severity scale and demographic characteristics. Differences between groups over time were evaluated using multivariable logistic regression. Random forest and XGBoost models were used to predict severe clinical course (death, discharge to hospice, invasive ventilatory support, or extracorporeal membrane oxygenation). MAIN OUTCOMES AND MEASURESPatient demographic characteristics and COVID-19 severity using the World Health Organization COVID-19 severity scale and differences between groups over time using multivariable logistic regression. RESULTSThe cohort included 174 568 adults who tested positive for SARS-CoV-2 (mean [SD] age, 44.4 [18.6] years; 53.2% female) and 1 133 848 adult controls who tested negative for SARS-CoV-2 (mean [SD] age, 49.5 [19.2] years; 57.1% female). Of the 174 568 adults with SARS-CoV-2, 32 472(18.6%) were hospitalized, and 6565 (20.2%) of those had a severe clinical course (invasive ventilatory support, extracorporeal membrane oxygenation, death, or discharge to hospice). Of the hospitalized patients, mortality was 11.6% overall and decreased from 16.4% in March to April 2020 to 8.6% in September to October 2020 (P = .002 for monthly trend). Using 64 inputs available on the first hospital day, this study predicted a severe clinical course using random forest and XGBoost models (area under the receiver operating curve = 0.87 for both) that were stable over time. The factor most strongly associated with clinical severity was pH; this result was consistent across machine learning methods. In a separate multivariable logistic regression model built for inference, (continued) Key Points Question In a US data resource large enough to adjust for multiple confounders, what risk factors are associated with COVID-19 severity and severity trajectory over time, and can machine learning models predict clinical severity? Findings In this cohort study of 174 568 adults with SARS-CoV-2, 32 472 (18.6%) were hospitalized and 6565 (20.2%) were severely ill, and first-day machine learning models accurately predicted clinical severity. Mortality was 11.6%

BackgroundEchocardiographic myocardial dysfunction is reported commonly in sepsis and septic shock, but there are limited data on sepsis-related right ventricular dysfunction. This study sought to evaluate the association of right ventricular dysfunction with clinical outcomes in patients with severe sepsis and septic shock.MethodsHistorical cohort study of adult patients admitted to all intensive care units at the Mayo Clinic from January 1, 2007 through December 31, 2014 for severe sepsis and septic shock, who had an echocardiogram performed within 72 h of admission. Patients with prior heart failure, cor-pulmonale, pulmonary hypertension and valvular disease were excluded. Right ventricular dysfunction was defined by the American Society of Echocardiography criteria. Outcomes included 1-year survival, in-hospital mortality and length of stay.ResultsRight ventricular dysfunction was present in 214 (55%) of 388 patients who met the inclusion criteria—isolated right ventricular dysfunction was seen in 100 (47%) and combined right and left ventricular dysfunction in 114 (53%). The baseline characteristics were similar between cohorts except for the higher mechanical ventilation use in patients with isolated right ventricular dysfunction. Echocardiographic findings demonstrated lower right ventricular and tricuspid valve velocities in patients with right ventricular dysfunction and lower left ventricular ejection fraction and increased mitral E/e′ ratios in patients with combined right and left ventricular dysfunction. After adjustment for age, comorbidity, illness severity, septic shock and use of mechanical ventilation, isolated right ventricular dysfunction was independently associated with worse 1-year survival—hazard ratio 1.6 [95% confidence interval 1.2–2.1; p = 0.002) in patients with sepsis and septic shock.ConclusionsIsolated right ventricular dysfunction is seen commonly in sepsis and septic shock and is associated with worse long-term survival.

BackgroundTroponin‐T elevation is seen commonly in sepsis and septic shock patients admitted to the intensive care unit. We sought to evaluate the role of admission and serial troponin‐T testing in the prognostication of these patients.Methods and ResultsThis was a retrospective cohort study from 2007 to 2014 on patients admitted to the intensive care units at the Mayo Clinic with severe sepsis and septic shock. Elevated admission troponin‐T and significant delta troponin‐T were defined as ≥0.01 ng/mL and ≥0.03 ng/mL in 3 hours, respectively. The primary outcome was in‐hospital mortality. Secondary outcomes included 1‐year mortality and lengths of stay. During this 8‐year period, 944 patients met the inclusion criteria with 845 (90%) having an admission troponin‐T ≥0.01 ng/mL. Serial troponin‐T values were available in 732 (78%) patients. Elevated admission troponin‐T was associated with older age, higher baseline comorbidity, and severity of illness, whereas significant delta troponin‐T was associated with higher severity of illness. Admission log10 troponin‐T was associated with unadjusted in‐hospital (odds ratio 1.6; P=0.003) and 1‐year mortality (odds ratio 1.3; P=0.04), but did not correlate with length of stay. Elevated delta troponin‐T and log10 delta troponin‐T were not significantly associated with any of the primary or secondary outcomes. Admission log10 troponin‐T remained an independent predictor of in‐hospital mortality (odds ratio 1.4; P=0.04) and 1‐year survival (hazard ratio 1.3; P=0.008).ConclusionsIn patients with sepsis and septic shock, elevated admission troponin‐T was associated with higher short‐ and long‐term mortality. Routine serial troponin‐T testing did not add incremental prognostic value in these patients.

In patients with severe sepsis and septic shock, the presence of new-onset LV dysfunction did not increase the risk of long-term adverse heart failure outcomes.

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The incidence of IE in children has remained unchanged in the United States during the 11-year study period. Among culture-positive patients there was a significant decrease in Staphylococcal IE and a significant increase of Streptococcal IE. Staphylococcal IE was associated with increased LOS and highest mortality.