Prediction of Duration of Mechanical Ventilation in Acute Hypoxemic Respiratoty Failure

Acute hypoxemic respiratory failure (AHRF) is a common cause of admission in intensive care units (ICUs) worldwide. We will assess machine learning (ML) techniques for prediction of prolonged duration (\> or = to 7 days) of mechanical ventilation (MV) in 1,241 patients enrolled in the PANDORA study in Spain. The study was registered with ClinalTrials.gov (NCT03145974). Our aim is to identify a model with the minimum number of variables that predict duration of prolonged ventilation in AHRF patients using data as early as from the first 48 hours with machine learning algorithms.

Inclusion Criteria: * enotracheal intubation puls mechanical ventilation * PaO2/FiO2 ratio \or =5 and FiO2 \>or = 0.3 Exclusion Criteria: * Brain death patients