Plos one17(2), e0263266
Published: February 22, 2022

Characteristics of patients at risk of developing severe forms of COVID-19 disease have been widely described, but very few studies describe their evolution through the following waves.

Data was collected retrospectively from a prospectively maintained database from a University Hospital in Paris area, over a year corresponding to the first three waves of COVID-19 in France. Evolution of patient characteristics between non-severe and severe cases through the waves was analyzed with a classical multivariate logistic regression along with a complementary Machine-Learning-based analysis using explainability methods.

Typology of hospitalized patients with severe forms evolved rapidly through the waves. This evolution may be due to the changes of hospital practices and the early vaccination campaign targeting the people at high risk such as elderly and patients with comorbidities.

Other resources you may be interested in

Impact of COVID-19 on surgical emergencies: nationwide analysis

Impact of COVID-19 on surgical emergencies: nationwide analysis

To cope with the burden of disease, hospital staff were reassigned and elective surgery was significantly delayed. Various countries implemented national containment […].

Covid-19 : Predicting admissions and extracting valuable insights from data analytics

Covid-19 : Predicting admissions and extracting valuable insights from data analytics

Faced with this health crisis, it was natural for Kaduceo to make our expertise available to hospitals. Adapting some of our predictive and indicator models to…