Machine learning links unresolving secondary pneumonia to mortality in patients with severe pneumonia, including COVID-19

The NU SCRIPT Study Investigators

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1 Scopus citations

Abstract

BACKGROUND. Despite guidelines promoting the prevention and aggressive treatment of ventilator-associated pneumonia (VAP), 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 for patients with severe pneumonia. METHODS. We performed a single-center, prospective cohort study of 585 mechanically ventilated patients with severe pneumonia and respiratory failure, 190 of whom had COVID-19, who underwent at least 1 bronchoalveolar lavage. A panel of intensive care unit (ICU) physicians adjudicated the pneumonia episodes and endpoints on the basis of clinical and microbiological data. Given the relatively long ICU length of stay (LOS) among patients with COVID-19, we developed a machine-learning approach called CarpeDiem, which grouped similar ICU patient-days into clinical states based on electronic health record data. RESULTS. CarpeDiem revealed that the long ICU LOS among patients with COVID-19 was attributable to long stays in clinical states characterized primarily by respiratory failure. While VAP was not associated with mortality overall, the mortality rate was higher for patients with 1 episode of unsuccessfully treated VAP compared with those with successfully treated VAP (76.4% versus 17.6%, P < 0.001). For all patients, including those with COVID-19, CarpeDiem demonstrated that unresolving VAP was associated with a transitions to clinical states associated with higher mortality. CONCLUSIONS. Unsuccessful treatment of VAP is associated with higher mortality. The relatively long LOS for patients with COVID-19 was primarily due to prolonged respiratory failure, placing them at higher risk of VAP.

Original languageEnglish (US)
Article numbere170682
JournalJournal of Clinical Investigation
Volume133
Issue number12
DOIs
StatePublished - Jun 15 2023

ASJC Scopus subject areas

  • Medicine(all)

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