A machine learning approach identifies unresolving secondary pneumonia as a contributor to mortality in patients with severe pneumonia, including COVID-19

Abstract

Background: Patients with severe SARS-CoV-2 pneumonia experience longer durations of critical illness yet similar mortality rates compared to patients with severe pneumonia secondary to other etiologies. As secondary bacterial infection is common in SARS-CoV-2 pneumonia, we hypothesized that unresolving ventilator-associated pneumonia (VAP) drives the apparent disconnect between length-of-stay and mortality rate among these patients. Methods: We analyzed VAP in a prospective single-center observational study of 585 mechanically ventilated patients with suspected pneumonia, including 190 patients with severe SARS-CoV-2 pneumonia. We developed CarpeDiem, a novel machine learning approach based on the practice of daily ICU team rounds to identify clinical states for each of the 12,495 ICU patient-days in the cohort. We used the CarpeDiem approach to evaluate the effect of VAP and its resolution on clinical trajectories. Findings: Patients underwent a median [IQR] of 4 [2,7] transitions between 14 clinical states during their ICU stays. Clinical states were associated with differential hospital mortality. The long length-of-stay among patients with severe SARS-CoV-2 pneumonia was associated with prolonged stays in clinical states defined by severe respiratory failure and with a lower frequency of transitions between clinical states. In all patients, including those with COVID-19, unresolving VAP episodes were associated with transitions to unfavorable states and hospital mortality. Interpretation: CarpeDiem offers a machine learning approach to examine the effect of VAP on clinical outcomes. Our findings suggest an underappreciated contribution of unresolving secondary bacterial pneumonia to outcomes in mechanically ventilated patients with pneumonia, including due to SARS-CoV-2.

Competing Interest Statement

BDS holds US patent 10,905,706, Compositions and methods to accelerate resolution of acute lung inflammation, and serves on the Scientific Advisory Board of Zoe Biosciences, for which he holds stock options. Other authors declare no conflicting interests.

Funding Statement

SCRIPT is supported by NIH/NIAID U19AI135964.

Author Declarations

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

This study was approved by the Northwestern University Institutional Review Board with study ID STU00204868.

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Data Availability

Data will be available online on PhysioNet. Code is available at https://github.com/NUSCRIPT/carpediem. Data browser is available at https://nupulmonary.org/carpediem/.

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