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Development of Traumatic Brain Injury Associated Intracranial Hypertension Prediction Algorithms: A Narrative Review

Traumatic intracranial hypertension (tIH) is a common and potentially lethal complication of moderate to severe traumatic brain injury (m-sTBI). It often develops with little warning and is managed reactively with the tiered application of intracranial pressure (ICP)-lowering interventions administe...

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Autores principales: McNamara, Robert, Meka, Shiv, Anstey, James, Fatovich, Daniel, Haseler, Luke, Jeffcote, Toby, Udy, Andrew, Bellomo, Rinaldo, Fitzgerald, Melinda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Mary Ann Liebert, Inc., publishers 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9986028/
https://www.ncbi.nlm.nih.gov/pubmed/36205570
http://dx.doi.org/10.1089/neu.2022.0201
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author McNamara, Robert
Meka, Shiv
Anstey, James
Fatovich, Daniel
Haseler, Luke
Jeffcote, Toby
Udy, Andrew
Bellomo, Rinaldo
Fitzgerald, Melinda
author_facet McNamara, Robert
Meka, Shiv
Anstey, James
Fatovich, Daniel
Haseler, Luke
Jeffcote, Toby
Udy, Andrew
Bellomo, Rinaldo
Fitzgerald, Melinda
author_sort McNamara, Robert
collection PubMed
description Traumatic intracranial hypertension (tIH) is a common and potentially lethal complication of moderate to severe traumatic brain injury (m-sTBI). It often develops with little warning and is managed reactively with the tiered application of intracranial pressure (ICP)-lowering interventions administered in response to an ICP rising above a set threshold. For over 45 years, a variety of research groups have worked toward the development of technology to allow for the preemptive management of tIH in the hope of improving patient outcomes. In 2022, the first operationalizable tIH prediction system became a reality. With such a system, ICP lowering interventions could be administered prior to the rise in ICP, thus protecting the patient from potentially damaging tIH episodes and limiting the overall ICP burden experienced. In this review, we discuss related approaches to ICP forecasting and IH prediction algorithms, which collectively provide the foundation for the successful development of an operational tIH prediction system. We also discuss operationalization and the statistical assessment of tIH algorithms. This review will be of relevance to clinicians and researchers interested in development of this technology as well as those with a general interest in the bedside application of machine learning (ML) technology.
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spelling pubmed-99860282023-03-07 Development of Traumatic Brain Injury Associated Intracranial Hypertension Prediction Algorithms: A Narrative Review McNamara, Robert Meka, Shiv Anstey, James Fatovich, Daniel Haseler, Luke Jeffcote, Toby Udy, Andrew Bellomo, Rinaldo Fitzgerald, Melinda J Neurotrauma Reviews Traumatic intracranial hypertension (tIH) is a common and potentially lethal complication of moderate to severe traumatic brain injury (m-sTBI). It often develops with little warning and is managed reactively with the tiered application of intracranial pressure (ICP)-lowering interventions administered in response to an ICP rising above a set threshold. For over 45 years, a variety of research groups have worked toward the development of technology to allow for the preemptive management of tIH in the hope of improving patient outcomes. In 2022, the first operationalizable tIH prediction system became a reality. With such a system, ICP lowering interventions could be administered prior to the rise in ICP, thus protecting the patient from potentially damaging tIH episodes and limiting the overall ICP burden experienced. In this review, we discuss related approaches to ICP forecasting and IH prediction algorithms, which collectively provide the foundation for the successful development of an operational tIH prediction system. We also discuss operationalization and the statistical assessment of tIH algorithms. This review will be of relevance to clinicians and researchers interested in development of this technology as well as those with a general interest in the bedside application of machine learning (ML) technology. Mary Ann Liebert, Inc., publishers 2023-03-01 2023-03-01 /pmc/articles/PMC9986028/ /pubmed/36205570 http://dx.doi.org/10.1089/neu.2022.0201 Text en © Robert McNamara et al., 2023; Published by Mary Ann Liebert, Inc. https://creativecommons.org/licenses/by/4.0/This Open Access article is distributed under the terms of the Creative Commons License (CC-BY) (http://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.
spellingShingle Reviews
McNamara, Robert
Meka, Shiv
Anstey, James
Fatovich, Daniel
Haseler, Luke
Jeffcote, Toby
Udy, Andrew
Bellomo, Rinaldo
Fitzgerald, Melinda
Development of Traumatic Brain Injury Associated Intracranial Hypertension Prediction Algorithms: A Narrative Review
title Development of Traumatic Brain Injury Associated Intracranial Hypertension Prediction Algorithms: A Narrative Review
title_full Development of Traumatic Brain Injury Associated Intracranial Hypertension Prediction Algorithms: A Narrative Review
title_fullStr Development of Traumatic Brain Injury Associated Intracranial Hypertension Prediction Algorithms: A Narrative Review
title_full_unstemmed Development of Traumatic Brain Injury Associated Intracranial Hypertension Prediction Algorithms: A Narrative Review
title_short Development of Traumatic Brain Injury Associated Intracranial Hypertension Prediction Algorithms: A Narrative Review
title_sort development of traumatic brain injury associated intracranial hypertension prediction algorithms: a narrative review
topic Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9986028/
https://www.ncbi.nlm.nih.gov/pubmed/36205570
http://dx.doi.org/10.1089/neu.2022.0201
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