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Dynamic Transitions of Pediatric Sepsis: A Markov Chain Analysis
Pediatric sepsis is a heterogeneous disease with varying physiological dynamics associated with recovery, disability, and mortality. Using risk scores generated from a sepsis prediction model to define illness states, we used Markov chain modeling to describe disease dynamics over time by describing...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8517521/ https://www.ncbi.nlm.nih.gov/pubmed/34660494 http://dx.doi.org/10.3389/fped.2021.743544 |
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author | Kausch, Sherry L. Lobo, Jennifer M. Spaeder, Michael C. Sullivan, Brynne Keim-Malpass, Jessica |
author_facet | Kausch, Sherry L. Lobo, Jennifer M. Spaeder, Michael C. Sullivan, Brynne Keim-Malpass, Jessica |
author_sort | Kausch, Sherry L. |
collection | PubMed |
description | Pediatric sepsis is a heterogeneous disease with varying physiological dynamics associated with recovery, disability, and mortality. Using risk scores generated from a sepsis prediction model to define illness states, we used Markov chain modeling to describe disease dynamics over time by describing how children transition among illness states. We analyzed 18,666 illness state transitions over 157 pediatric intensive care unit admissions in the 3 days following blood cultures for suspected sepsis. We used Shannon entropy to quantify the differences in transition matrices stratified by clinical characteristics. The population-based transition matrix based on the sepsis illness severity scores in the days following a sepsis diagnosis can describe a sepsis illness trajectory. Using the entropy based on Markov chain transition matrices, we found a different structure of dynamic transitions based on ventilator use but not age group. Stochastic modeling of transitions in sepsis illness severity scores can be useful in describing the variation in transitions made by patient and clinical characteristics. |
format | Online Article Text |
id | pubmed-8517521 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85175212021-10-16 Dynamic Transitions of Pediatric Sepsis: A Markov Chain Analysis Kausch, Sherry L. Lobo, Jennifer M. Spaeder, Michael C. Sullivan, Brynne Keim-Malpass, Jessica Front Pediatr Pediatrics Pediatric sepsis is a heterogeneous disease with varying physiological dynamics associated with recovery, disability, and mortality. Using risk scores generated from a sepsis prediction model to define illness states, we used Markov chain modeling to describe disease dynamics over time by describing how children transition among illness states. We analyzed 18,666 illness state transitions over 157 pediatric intensive care unit admissions in the 3 days following blood cultures for suspected sepsis. We used Shannon entropy to quantify the differences in transition matrices stratified by clinical characteristics. The population-based transition matrix based on the sepsis illness severity scores in the days following a sepsis diagnosis can describe a sepsis illness trajectory. Using the entropy based on Markov chain transition matrices, we found a different structure of dynamic transitions based on ventilator use but not age group. Stochastic modeling of transitions in sepsis illness severity scores can be useful in describing the variation in transitions made by patient and clinical characteristics. Frontiers Media S.A. 2021-10-01 /pmc/articles/PMC8517521/ /pubmed/34660494 http://dx.doi.org/10.3389/fped.2021.743544 Text en Copyright © 2021 Kausch, Lobo, Spaeder, Sullivan and Keim-Malpass. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pediatrics Kausch, Sherry L. Lobo, Jennifer M. Spaeder, Michael C. Sullivan, Brynne Keim-Malpass, Jessica Dynamic Transitions of Pediatric Sepsis: A Markov Chain Analysis |
title | Dynamic Transitions of Pediatric Sepsis: A Markov Chain Analysis |
title_full | Dynamic Transitions of Pediatric Sepsis: A Markov Chain Analysis |
title_fullStr | Dynamic Transitions of Pediatric Sepsis: A Markov Chain Analysis |
title_full_unstemmed | Dynamic Transitions of Pediatric Sepsis: A Markov Chain Analysis |
title_short | Dynamic Transitions of Pediatric Sepsis: A Markov Chain Analysis |
title_sort | dynamic transitions of pediatric sepsis: a markov chain analysis |
topic | Pediatrics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8517521/ https://www.ncbi.nlm.nih.gov/pubmed/34660494 http://dx.doi.org/10.3389/fped.2021.743544 |
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