Acute respiratory distress syndrome after SARS-CoV-2 infection on young adult population: International observational federated study based on electronic health records through the 4CE consortium.

PURPOSE: In young adults (18 to 49 years old), investigation of the acute respiratory distress syndrome (ARDS) after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been limited. We evaluated the risk factors and outcomes of ARDS following infection with SARS-CoV-2 in a young adult population. METHODS: A retrospective cohort study was conducted between January 1st, 2020 and February 28th, 2021 using patient-level electronic health records (EHR), across 241 United States hospitals and 43 European hospitals participating in the Consortium for Clinical Characterization of COVID-19 by EHR (4CE). To identify the risk factors associated with ARDS, we compared young patients with and without ARDS through a federated analysis. We further compared the outcomes between young and old patients with ARDS. RESULTS: Among the 75,377 hospitalized patients with positive SARS-CoV-2 PCR, 1001 young adults presented with ARDS (7.8% of young hospitalized adults). Their mortality rate at 90 days was 16.2% and they presented with a similar complication rate for infection than older adults with ARDS. Peptic ulcer disease, paralysis, obesity, congestive heart failure, valvular disease, diabetes, chronic pulmonary disease and liver disease were associated with a higher risk of ARDS. We described a high prevalence of obesity (53%), hypertension (38%- although not significantly associated with ARDS), and diabetes (32%). CONCLUSION: Trough an innovative method, a large international cohort study of young adults developing ARDS after SARS-CoV-2 infection has been gather. It demonstrated the poor outcomes of this population and associated risk factor.

The benefit of augmenting open data with clinical data-warehouse EHR for forecasting SARS-CoV-2 hospitalizations in Bordeaux area, France.

Objective: The aim of this study was to develop an accurate regional forecast algorithm to predict the number of hospitalized patients and to assess the benefit of the Electronic Health Records (EHR) information to perform those predictions. Materials and Methods: Aggregated data from SARS-CoV-2 and weather public database and data warehouse of the Bordeaux hospital were extracted from May 16, 2020 to January 17, 2022. The outcomes were the number of hospitalized patients in the Bordeaux Hospital at 7 and 14 days. We compared the performance of different data sources, feature engineering, and machine learning models. Results: During the period of 88 weeks, 2561 hospitalizations due to COVID-19 were recorded at the Bordeaux Hospital. The model achieving the best performance was an elastic-net penalized linear regression using all available data with a median relative error at 7 and 14 days of 0.136 [0.063; 0.223] and 0.198 [0.105; 0.302] hospitalizations, respectively. Electronic health records (EHRs) from the hospital data warehouse improved median relative error at 7 and 14 days by 10.9% and 19.8%, respectively. Graphical evaluation showed remaining forecast error was mainly due to delay in slope shift detection. Discussion: Forecast model showed overall good performance both at 7 and 14 days which were improved by the addition of the data from Bordeaux Hospital data warehouse. Conclusions: The development of hospital data warehouse might help to get more specific and faster information than traditional surveillance system, which in turn will help to improve epidemic forecasting at a larger and finer scale.

Accuracy of COVID-19 rapid antigenic tests compared to RT-PCR in a student population: The StudyCov study.

OBJECTIVE: There is a lack of data evaluating performance of antigenic test (AT) for SARS-CoV-2 diagnosis (Ag-RDT) in clinical practice, especially in asymptomatic subjects. The main objective of this study was to evaluate the diagnostic performance of AT compared to Reverse Transcription Polymerase Chain Reaction (RT-PCR) for SARS-CoV-2 diagnosis. METHODS: StudyCov is a monocentric cross-sectional study. A SARS-CoV-2 screening facility was set up in the Bordeaux University health campus from October 28th to November 20th 2020. Students willing to have a RT-PCR test (ARGENE SARS-CoV-2 R-GENE, BioMérieux, France) for SARS-CoV-2 diagnosis were also offered the Abbott Panbio™ SARS-CoV-2 antigenic rapid test. All participants attending the screening facility with an AT in addition to RT-PCR and having signed an informed consent were included in the study. The main objective was to assess performance of AT as compared with RT-PCR in the recruited population. Secondary objectives dealt with the analysis of the main objective stratified by current symptoms and risk exposure. A sensitivity analysis with different RT-PCR cycle thresholds was included. RESULTS: RT-PCR and AT results were available for 692 subjects. Overall sensitivity and specificity of AT tests were respectively 63.5% (95% confidence interval (CI): 49.0 - 76.4) and 100% (95% CI: 99.4 - 100). In the asymptomatic sub-group, they were respectively 35.0% (95% CI: 15.4% - 59.2%) and 100% (95% CI: 99.3 - 100). CONCLUSIONS: This study shows the poor sensitivity of AT in asymptomatic subjects, specificity being however excellent. The performance results fall below the World Health Organization recommendation of 80% sensitivity and question using AT in general population, especially when asymptomatic.