The Catalan Agency for Health Quality and Evaluation (AQuAS), through the Data Analysis Program for Research and Innovation in Health (PADRIS), has activated a new urgent prioritization procedure for projects related to 'current epidemic of COVID-19 that need expert support for the preparation, analysis and exploration of data and construction of predictive models through the information of the Health System of Catalonia.
This urgent procedure of prioritization of the PADRIS program aims to optimize the management of available resources and ensure the highest quality of the results obtained to contribute to the knowledge about COVID-19 and the coronavirus that causes it.
In the context of this competitive call, the four projects set out below, led by the Fundació Parc Taulí, have been selected to receive this support from the AQuAS:
"Classification and personalized prognostic evolution through machine learning techniques in COVID-19 patients with admission requirements to the Intensive Care Unit"
IP: Lluís Blanch Torra
The aim is to obtain a tool for classifying and predicting the evolution of critical COVID-19 patients admitted to the Intensive Care Unit, based on the use of machine learning applied to the physiognomies obtained from the continuous monitoring of these patients.
"Are low vitamin D levels a severe risk factor for COVID-19?"
IP: Joaquim Oristrell
Vitamin D modulates defense against viral infections, decreasing the inflammatory response. On the other hand, epidemiological studies have observed that deficiency of this vitamin is associated with increased risk of respiratory infections. The aim of this study is to demonstrate the protective role of vitamin D in the pathogenesis of COVID-19.
“Stratification of the risk of serious and poor evolution of COVID-19 infection, based on Patterns of Chronic Multimorbidity and other clinical and demographic factors”
IP: Maria Lluïsa Baré Mañas
There were certain chronic diseases that, alone or interrelated (constituting patterns or clusters), increase the risk of severe COVID infection19 and, at the same time, these diseases and patterns of association, along with other factors such as sex, age, or pharmacological treatments may determine an increased risk of complications (sepsis, septic shock, SARS, death)
The aim of this study is to identify these patterns of multimorbidity, and also to design a tool for predicting disease.
“Population study of COVID-19 disease in chronic kidney patients in Catalonia. Establishment of predictive models ”
IP: Juan Carlos Martínez Ocaña
Chronic kidney disease is characterized by high comorbidity and higher overall morbidity and mortality compared to the general population. The aim of this study is to assess whether there are different risk factors for infection, disease and mortality from SARS-CoV-2 in this population compared to the general population and to establish predictive models to identify those patients who are they could benefit from early intervention and those with poor vital prognosis in order to help adjust the health resources to be used in each group of chronic kidney patients affected by COVID-19.
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