Signatures of illness in children requiring unplanned intubation in the pediatric intensive care unit: A retrospective cohort machine-learning study.

Autor:	Spaeder MC; Department of Pediatrics, Division of Pediatric Critical Care, School of Medicine, University of Virginia, Charlottesville, VA, United States.; Center for Advanced Medical Analytics, School of Medicine, University of Virginia, Charlottesville, VA, United States., Moorman JR; Center for Advanced Medical Analytics, School of Medicine, University of Virginia, Charlottesville, VA, United States.; Department of Medicine, Division of Cardiovascular Medicine, School of Medicine, University of Virginia, Charlottesville, VA, United States., Moorman LP; Center for Advanced Medical Analytics, School of Medicine, University of Virginia, Charlottesville, VA, United States.; Nihon Kohden Digital Health Solutions, Irvine, CA, United States., Adu-Darko MA; Department of Pediatrics, Division of Pediatric Critical Care, School of Medicine, University of Virginia, Charlottesville, VA, United States., Keim-Malpass J; Center for Advanced Medical Analytics, School of Medicine, University of Virginia, Charlottesville, VA, United States.; Department of Acute and Specialty Care, School of Nursing, University of Virginia, Charlottesville, VA, United States., Lake DE; Center for Advanced Medical Analytics, School of Medicine, University of Virginia, Charlottesville, VA, United States.; Department of Medicine, Division of Cardiovascular Medicine, School of Medicine, University of Virginia, Charlottesville, VA, United States., Clark MT; Center for Advanced Medical Analytics, School of Medicine, University of Virginia, Charlottesville, VA, United States.; Nihon Kohden Digital Health Solutions, Irvine, CA, United States.
Jazyk:	angličtina
Zdroj:	Frontiers in pediatrics [Front Pediatr] 2022 Oct 19; Vol. 10, pp. 1016269. Date of Electronic Publication: 2022 Oct 19 (Print Publication: 2022).
DOI:	10.3389/fped.2022.1016269
Abstrakt:	Acute respiratory failure requiring the initiation of invasive mechanical ventilation remains commonplace in the pediatric intensive care unit (PICU). Early recognition of patients at risk for respiratory failure may provide clinicians with the opportunity to intervene and potentially improve outcomes. Through the development of a random forest model to identify patients at risk for requiring unplanned intubation, we tested the hypothesis that subtle signatures of illness are present in physiological and biochemical time series of PICU patients in the early stages of respiratory decompensation. We included 116 unplanned intubation events as recorded in the National Emergency Airway Registry for Children in 92 PICU admissions over a 29-month period at our institution. We observed that children have a physiologic signature of illness preceding unplanned intubation in the PICU. Generally, it comprises younger age, and abnormalities in electrolyte, hematologic and vital sign parameters. Additionally, given the heterogeneity of the PICU patient population, we found differences in the presentation among the major patient groups - medical, cardiac surgical, and non-cardiac surgical. At four hours prior to the event, our random forest model demonstrated an area under the receiver operating characteristic curve of 0.766 (0.738 for medical, 0.755 for cardiac surgical, and 0.797 for non-cardiac surgical patients). The multivariable statistical models that captured the physiological and biochemical dynamics leading up to the event of urgent unplanned intubation in a PICU can be repurposed for bedside risk prediction. Competing Interests: Authors LPM and MTC were employed by company Nihon Kohden Digital Health Solutions. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (© 2022 Spaeder, Moorman, Moorman, Adu-Darko, Keim-Malpass, Lake and Clark.)
Databáze:	MEDLINE
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