Admissions to a large tertiary care hospital and Omicron BA.1 and BA.2 SARS-CoV-2 PCR positivity: primary, contributing, or incidental COVID-19

SARS-CoV-2 Omicron variants BA.1 and BA.2 seem to show reduced clinical severity. We classified 172 COVID-19 Omicron patient admissions. 66.2% of patients were admitted with primary or admission-contributing COVID-19. We therefore must be careful to base healthcare and public health decisions on the total number of hospitalized COVID-19 patients alone.

COVID Outcome Prediction in the Emergency Department (COPE)

Background and aimCOVID-19 is putting extraordinary pressure on emergency departments (EDs). To support decision making in the ED, we aimed to develop a simple and valid model for predicting mortality and need for intensive care unit (ICU) admission in suspected COVID-19 patients. MethodsFor model development, we retrospectively collected data of patients who were admitted to 4 large Dutch hospitals with suspected COVID-19 between March and August 2020 (first wave of the pandemic). Based on prior literature we considered quickly and objectively obtainable patient characteristics, vital parameters and blood test values as predictors. Logistic regression analyses with post-hoc uniform shrinkage was used to obtain predicted probabilities of in-hospital death and of the need for ICU admission, both within 28 days after hospital admission. We assessed model performance (Area Under the ROC curve (AUC); calibration plots) with temporal validation in patients who presented between September and December 2020 (second wave). We used multiple imputation to account for missing values. ResultsThe development data included 5,831 patients, of whom 629 (10.8%) died and 5,070 (86.9%) were discharged within 28 days after admission. ICU admission was fully recorded for 2,633 first wave patients in 2 hospitals, with 214 (8%) ICU admissions within 28 days. A simple model - COVID Outcome Prediction in the Emergency Department (COPE) - with age, respiratory rate, C-reactive protein, lactic dehydrogenase, albumin and urea captured most of the ability to predict death. COPE was well-calibrated and showed good discrimination in 3,252 second wave patients (AUC in 4 hospitals: 0.82 [0.78; 0.86]; 0.82 [0.74; 0.90]; 0.79 [0.70; 0.88]; 0.83 [0.79; 0.86]). COPE was also able to identify patients at high risk of needing IC in 706 second wave patients with complete information on ICU admission (AUC: 0.84 [0.78; 0.90]; 0.81 [0.66; 0.95]). The models are implemented in web-based and mobile applications. ConclusionCOPE is a simple tool that is well able to predict mortality and need for ICU admission for patients who present to the ED with suspected COVID-19 and may help patients and doctors in decision making. CONTRIBUTION TO THE LITERATUREO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIPrediction models have the potential to support decision making about hospital admission of patients presenting to the emergency department with suspected COVID-19 C_LIO_LIMost currently available models that were independently assessed contain a high risk of bias C_LIO_LIPromising models were developed in different patient selections and included predictors that are not quickly and objective obtainable in emergency departments C_LI What this study addsO_LIA simple and objective tool ("COPE") is well able to predict mortality and need for ICU admission for patients who present to the ED with suspected COVID-19 C_LIO_LICOPE may support ED physicians to identify high-risk patients - i.e. those at high risk of deterioration and/or death - requiring treatment in the ICU, intermediate-risk patients requiring admission to the clinical ward, and low-risk patients who can potentially be sent home C_LI

Temporal kinetics of RNAemia and associated systemic cytokines in hospitalized COVID-19 patients

COVID-19 is associated to a wide range of extra-respiratory complications, of which the pathogenesis is currently not fully understood. In this study we report the temporal kinetics of viral RNA and inflammatory cytokines and chemokines in serum during the course of COVID-19. We show that a RNAemia occurs more frequently and lasts longer in patients that develop critical disease compared to patients that develop moderate or severe disease. Furthermore we show that concentrations of IL-10 and MCP-1--but not IL-6--are associated with viral load in serum. However, higher levels of IL-6 were associated with the development of critical disease. The direct association of inflammatory cytokines with viral load or disease severity highlights the complexity of systemic inflammatory response and the role of systemic viral spread.