Development and Validation of ARC, a Model for Anticipating Acute Respiratory Failure in Coronavirus Disease 2019 Patients.

Critical Care Explorations
Suchi SariaVikas N O'Reilly-Shah

Abstract

To evaluate factors predictive of clinical progression among coronavirus disease 2019 patients following admission, and whether continuous, automated assessments of patient status may contribute to optimal monitoring and management. Retrospective cohort for algorithm training, testing, and validation. Eight hospitals across two geographically distinct regions. Two-thousand fifteen hospitalized coronavirus disease 2019-positive patients. None. Anticipating Respiratory failure in Coronavirus disease (ARC), a clinically interpretable, continuously monitoring prognostic model of acute respiratory failure in hospitalized coronavirus disease 2019 patients, was developed and validated. An analysis of the most important clinical predictors aligns with key risk factors identified by other investigators but contributes new insights regarding the time at which key factors first begin to exhibit aberrency and distinguishes features predictive of acute respiratory failure in coronavirus disease 2019 versus pneumonia caused by other types of infection. Departing from prior work, ARC was designed to update continuously over time as new observations (vitals and laboratory test results) are recorded in the electronic health record. Validation a...Continue Reading

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Software Mentioned

Python shap package
xgboost package
Python

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