Despite guidelines promoting the prevention and aggressive treatment of ventilator-associated pneumonia , the importance of VAP as a driver of outcomes in mechanically ventilated patients, including patients with severe COVID-19, remains unclear. We aimed to determine the contribution of unsuccessful treatment of VAP to mortality in patients with severe pneumonia.
Given the relatively long ICU length of stay among patients with COVID-19, we developed a machine learning approach called, which groups similar ICU patient-days into clinical states based on electronic health record data.revealed that the long ICU length of stay among patients with COVID-19 is attributable to long stays in clinical states characterized primarily by respiratory failure.