Finding studies
Finding studies
Take this into the appointment.
Saves the questions and what to expect into your notes, next to the visit they belong to.
Lead
Assistance Publique - Hôpitaux de Paris
With
To answer the questions raised in the primary and secondary endpoints, a biological collection (serum, plasma, DNA, RNA, mono-nucleated cells and urine) and a collection of detailed data by the mean of a questionnaire (demographic, clinical, lifestyle, professional exposure to the virus, COVID-19 infection with detailed symptoms and complications) during the serological screening for SARS-CoV-2 of hospital agents (medical and non-medical staff) of the Assistance Publique Hôpitaux de Paris (Paris, France) will be carried out. 4000 professionals in 5 hospitals of the Assistance Publique Hôpitaux de Paris. As part of the research, the anti SRAS-CoV-2 serology will be monitored 6 months (M6) and 12 months (M12) after the initial serology and a brief questionnaire (update regarding treatments, co-morbidities, and COVID-19 infection) will be fulfilled at these two time points. Of note, if the inclusion could not be performed during the initial serological screening, the professional will be recalled to be included at M6. Statistical analysis: The analysis of the determinants independently associated with symptomatic COVID + status will be carried out by uni- and multivariate logistic regression. The internal validation will be carried out by methods of draw with discount (bootstrap). The performance of the model will include calibration (graphical method) and discrimination (AUC). The biomarker study will include the study of the association with COVID + symptomatic versus asymptomatic status by univariate then multivariate analyzes (logistic regression) including clinical variables. The additional value of biomarkers will be studied by comparing the discriminating power of clinical models with and without the new biomarker. Finally, the study of the heterogeneity of COVID + symptomatic and asymptomatic patients will be carried out by an unsupervised analysis of Machine Learning known as archetypes.
Age
18–any
Sex
ALL
Healthy volunteers
Accepted
