Development and validation of an early warning tool for sepsis and decompensation in children during emergency department triage

Abstract This study was designed to develop and validate an early warning system for sepsis based on a predictive model of critical decompensation. Data from the electronic medical records for 537,837 visits to a pediatric Emergency Department (ED) from March 2013 to December 2019 were collected. A...

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Autores principales:	Louis Ehwerhemuepha, Theodore Heyming, Rachel Marano, Mary Jane Piroutek, Antonio C. Arrieta, Kent Lee, Jennifer Hayes, James Cappon, Kamila Hoenk, William Feaster
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/fee043617e814d7e86063696a4a99a9b
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spelling	oai:doaj.org-article:fee043617e814d7e86063696a4a99a9b2021-12-02T18:27:47ZDevelopment and validation of an early warning tool for sepsis and decompensation in children during emergency department triage10.1038/s41598-021-87595-z2045-2322https://doaj.org/article/fee043617e814d7e86063696a4a99a9b2021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-87595-zhttps://doaj.org/toc/2045-2322Abstract This study was designed to develop and validate an early warning system for sepsis based on a predictive model of critical decompensation. Data from the electronic medical records for 537,837 visits to a pediatric Emergency Department (ED) from March 2013 to December 2019 were collected. A multiclass stochastic gradient boosting model was built to identify early warning signs associated with death, severe sepsis, non-severe sepsis, and bacteremia. Model features included triage vital signs, previous diagnoses, medications, and healthcare utilizations within 6 months of the index ED visit. There were 483 patients who had severe sepsis and/or died, 1102 had non-severe sepsis, 1103 had positive bacteremia tests, and the remaining had none of the events. The most important predictors were age, heart rate, length of stay of previous hospitalizations, temperature, systolic blood pressure, and prior sepsis. The one-versus-all area under the receiver operator characteristic curve (AUROC) were 0.979 (0.967, 0.991), 0.990 (0.985, 0.995), 0.976 (0.972, 0.981), and 0.968 (0.962, 0.974) for death, severe sepsis, non-severe sepsis, and bacteremia without sepsis respectively. The multi-class macro average AUROC and area under the precision recall curve were 0.977 and 0.316 respectively. The study findings were used to develop an automated early warning decision tool for sepsis. Implementation of this model in pediatric EDs will allow sepsis-related critical decompensation to be predicted accurately after a few seconds of triage.Louis EhwerhemuephaTheodore HeymingRachel MaranoMary Jane PiroutekAntonio C. ArrietaKent LeeJennifer HayesJames CapponKamila HoenkWilliam FeasterNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Louis Ehwerhemuepha Theodore Heyming Rachel Marano Mary Jane Piroutek Antonio C. Arrieta Kent Lee Jennifer Hayes James Cappon Kamila Hoenk William Feaster Development and validation of an early warning tool for sepsis and decompensation in children during emergency department triage
description	Abstract This study was designed to develop and validate an early warning system for sepsis based on a predictive model of critical decompensation. Data from the electronic medical records for 537,837 visits to a pediatric Emergency Department (ED) from March 2013 to December 2019 were collected. A multiclass stochastic gradient boosting model was built to identify early warning signs associated with death, severe sepsis, non-severe sepsis, and bacteremia. Model features included triage vital signs, previous diagnoses, medications, and healthcare utilizations within 6 months of the index ED visit. There were 483 patients who had severe sepsis and/or died, 1102 had non-severe sepsis, 1103 had positive bacteremia tests, and the remaining had none of the events. The most important predictors were age, heart rate, length of stay of previous hospitalizations, temperature, systolic blood pressure, and prior sepsis. The one-versus-all area under the receiver operator characteristic curve (AUROC) were 0.979 (0.967, 0.991), 0.990 (0.985, 0.995), 0.976 (0.972, 0.981), and 0.968 (0.962, 0.974) for death, severe sepsis, non-severe sepsis, and bacteremia without sepsis respectively. The multi-class macro average AUROC and area under the precision recall curve were 0.977 and 0.316 respectively. The study findings were used to develop an automated early warning decision tool for sepsis. Implementation of this model in pediatric EDs will allow sepsis-related critical decompensation to be predicted accurately after a few seconds of triage.
format	article
author	Louis Ehwerhemuepha Theodore Heyming Rachel Marano Mary Jane Piroutek Antonio C. Arrieta Kent Lee Jennifer Hayes James Cappon Kamila Hoenk William Feaster
author_facet	Louis Ehwerhemuepha Theodore Heyming Rachel Marano Mary Jane Piroutek Antonio C. Arrieta Kent Lee Jennifer Hayes James Cappon Kamila Hoenk William Feaster
author_sort	Louis Ehwerhemuepha
title	Development and validation of an early warning tool for sepsis and decompensation in children during emergency department triage
title_short	Development and validation of an early warning tool for sepsis and decompensation in children during emergency department triage
title_full	Development and validation of an early warning tool for sepsis and decompensation in children during emergency department triage
title_fullStr	Development and validation of an early warning tool for sepsis and decompensation in children during emergency department triage
title_full_unstemmed	Development and validation of an early warning tool for sepsis and decompensation in children during emergency department triage
title_sort	development and validation of an early warning tool for sepsis and decompensation in children during emergency department triage
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/fee043617e814d7e86063696a4a99a9b
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Development and validation of an early warning tool for sepsis and decompensation in children during emergency department triage

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