Lessons learned during COVID-19 pandemic: From a pulmonary perspective toward derivation and validation of predictive models for relevant clinical outcomes

During COVID-19 pandemic, several new skills and techniques about data management were learned. Some examples are related to prediction of increase in lung weight according to biomarkers present in blood samples obtained at hospital admission. Further examples are related to derivation and external validation of predictive models for clinical outcomes. Much of these clinical and laboratory data can be gathered at hospital admission, statistically treated and properly analyzed. The main objective is to obtain valuable information to detect whether the patients should or not be evolved to advanced respiratory treatment. Furthermore, one fundamental approach is to externally validate those predictive models, so that they can be used elsewhere, without borders. This will be explained at the symposium.