Permutation Entropy Analysis to Intracranial Hypertension from a Porcine Model

Autores
Pose, Fernando Ezequiel; Ciarrocchi, Nicolas Marcelo; Videla, Carlos; Redelico, Francisco Oscar
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Intracranial pressure (ICP) monitoring is commonly used in the follow-up of patients in intensive care units, but only a small part of the information available in the ICP time series is exploited. One of the most important features to guide patient follow-up and treatment is intracranial compliance. We propose using permutation entropy (PE) as a method to extract non-obvious information from the ICP curve. We analyzed the results of a pig experiment with sliding windows of 3600 samples and 1000 displacement samples, and estimated their respective PEs, their associated probability distributions, and the number of missing patterns (NMP). We observed that the behavior of PE is inverse to that of ICP, in addition to the fact that NMP appears as a surrogate for intracranial compliance. In lesion-free periods, PE is usually greater than 0.3, and normalized NMP is less than (Formula presented.) and (Formula presented.). Any deviation from these values could be a possible warning of altered neurophysiology. In the terminal phases of the lesion, the normalized NMP is higher than (Formula presented.), and PE is not sensitive to changes in ICP and (Formula presented.). The results show that it could be used for real-time patient monitoring or as input for a machine learning tool.
Fil: Pose, Fernando Ezequiel. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; Argentina
Fil: Ciarrocchi, Nicolas Marcelo. Hospital Italiano; Argentina
Fil: Videla, Carlos. Hospital Italiano; Argentina
Fil: Redelico, Francisco Oscar. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina
Materia
INTRACRANIAL COMPLIANCE
INTRACRANIAL PRESSURE
PERMUTATION ENTROPY
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/227945
Acceder
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network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling Permutation Entropy Analysis to Intracranial Hypertension from a Porcine ModelPose, Fernando EzequielCiarrocchi, Nicolas MarceloVidela, CarlosRedelico, Francisco OscarINTRACRANIAL COMPLIANCEINTRACRANIAL PRESSUREPERMUTATION ENTROPYhttps://purl.org/becyt/ford/3.1https://purl.org/becyt/ford/3Intracranial pressure (ICP) monitoring is commonly used in the follow-up of patients in intensive care units, but only a small part of the information available in the ICP time series is exploited. One of the most important features to guide patient follow-up and treatment is intracranial compliance. We propose using permutation entropy (PE) as a method to extract non-obvious information from the ICP curve. We analyzed the results of a pig experiment with sliding windows of 3600 samples and 1000 displacement samples, and estimated their respective PEs, their associated probability distributions, and the number of missing patterns (NMP). We observed that the behavior of PE is inverse to that of ICP, in addition to the fact that NMP appears as a surrogate for intracranial compliance. In lesion-free periods, PE is usually greater than 0.3, and normalized NMP is less than (Formula presented.) and (Formula presented.). Any deviation from these values could be a possible warning of altered neurophysiology. In the terminal phases of the lesion, the normalized NMP is higher than (Formula presented.), and PE is not sensitive to changes in ICP and (Formula presented.). The results show that it could be used for real-time patient monitoring or as input for a machine learning tool.Fil: Pose, Fernando Ezequiel. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; ArgentinaFil: Ciarrocchi, Nicolas Marcelo. Hospital Italiano; ArgentinaFil: Videla, Carlos. Hospital Italiano; ArgentinaFil: Redelico, Francisco Oscar. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaMolecular Diversity Preservation International2023-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/227945Pose, Fernando Ezequiel; Ciarrocchi, Nicolas Marcelo; Videla, Carlos; Redelico, Francisco Oscar; Permutation Entropy Analysis to Intracranial Hypertension from a Porcine Model; Molecular Diversity Preservation International; Entropy; 25; 2; 1-2023; 1-151099-4300CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/1099-4300/25/2/267info:eu-repo/semantics/altIdentifier/doi/10.3390/e25020267info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:53:22Zoai:ri.conicet.gov.ar:11336/227945instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:53:23.223CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Permutation Entropy Analysis to Intracranial Hypertension from a Porcine Model
title Permutation Entropy Analysis to Intracranial Hypertension from a Porcine Model
spellingShingle Permutation Entropy Analysis to Intracranial Hypertension from a Porcine Model
Pose, Fernando Ezequiel
INTRACRANIAL COMPLIANCE
INTRACRANIAL PRESSURE
PERMUTATION ENTROPY
title_short Permutation Entropy Analysis to Intracranial Hypertension from a Porcine Model
title_full Permutation Entropy Analysis to Intracranial Hypertension from a Porcine Model
title_fullStr Permutation Entropy Analysis to Intracranial Hypertension from a Porcine Model
title_full_unstemmed Permutation Entropy Analysis to Intracranial Hypertension from a Porcine Model
title_sort Permutation Entropy Analysis to Intracranial Hypertension from a Porcine Model
dc.creator.none.fl_str_mv Pose, Fernando Ezequiel
Ciarrocchi, Nicolas Marcelo
Videla, Carlos
Redelico, Francisco Oscar
author Pose, Fernando Ezequiel
author_facet Pose, Fernando Ezequiel
Ciarrocchi, Nicolas Marcelo
Videla, Carlos
Redelico, Francisco Oscar
author_role author
author2 Ciarrocchi, Nicolas Marcelo
Videla, Carlos
Redelico, Francisco Oscar
author2_role author
author
author
dc.subject.none.fl_str_mv INTRACRANIAL COMPLIANCE
INTRACRANIAL PRESSURE
PERMUTATION ENTROPY
topic INTRACRANIAL COMPLIANCE
INTRACRANIAL PRESSURE
PERMUTATION ENTROPY
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.1
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv Intracranial pressure (ICP) monitoring is commonly used in the follow-up of patients in intensive care units, but only a small part of the information available in the ICP time series is exploited. One of the most important features to guide patient follow-up and treatment is intracranial compliance. We propose using permutation entropy (PE) as a method to extract non-obvious information from the ICP curve. We analyzed the results of a pig experiment with sliding windows of 3600 samples and 1000 displacement samples, and estimated their respective PEs, their associated probability distributions, and the number of missing patterns (NMP). We observed that the behavior of PE is inverse to that of ICP, in addition to the fact that NMP appears as a surrogate for intracranial compliance. In lesion-free periods, PE is usually greater than 0.3, and normalized NMP is less than (Formula presented.) and (Formula presented.). Any deviation from these values could be a possible warning of altered neurophysiology. In the terminal phases of the lesion, the normalized NMP is higher than (Formula presented.), and PE is not sensitive to changes in ICP and (Formula presented.). The results show that it could be used for real-time patient monitoring or as input for a machine learning tool.
Fil: Pose, Fernando Ezequiel. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; Argentina
Fil: Ciarrocchi, Nicolas Marcelo. Hospital Italiano; Argentina
Fil: Videla, Carlos. Hospital Italiano; Argentina
Fil: Redelico, Francisco Oscar. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina
description Intracranial pressure (ICP) monitoring is commonly used in the follow-up of patients in intensive care units, but only a small part of the information available in the ICP time series is exploited. One of the most important features to guide patient follow-up and treatment is intracranial compliance. We propose using permutation entropy (PE) as a method to extract non-obvious information from the ICP curve. We analyzed the results of a pig experiment with sliding windows of 3600 samples and 1000 displacement samples, and estimated their respective PEs, their associated probability distributions, and the number of missing patterns (NMP). We observed that the behavior of PE is inverse to that of ICP, in addition to the fact that NMP appears as a surrogate for intracranial compliance. In lesion-free periods, PE is usually greater than 0.3, and normalized NMP is less than (Formula presented.) and (Formula presented.). Any deviation from these values could be a possible warning of altered neurophysiology. In the terminal phases of the lesion, the normalized NMP is higher than (Formula presented.), and PE is not sensitive to changes in ICP and (Formula presented.). The results show that it could be used for real-time patient monitoring or as input for a machine learning tool.
publishDate 2023
dc.date.none.fl_str_mv 2023-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/227945
Pose, Fernando Ezequiel; Ciarrocchi, Nicolas Marcelo; Videla, Carlos; Redelico, Francisco Oscar; Permutation Entropy Analysis to Intracranial Hypertension from a Porcine Model; Molecular Diversity Preservation International; Entropy; 25; 2; 1-2023; 1-15
1099-4300
CONICET Digital
CONICET
url http://hdl.handle.net/11336/227945
identifier_str_mv Pose, Fernando Ezequiel; Ciarrocchi, Nicolas Marcelo; Videla, Carlos; Redelico, Francisco Oscar; Permutation Entropy Analysis to Intracranial Hypertension from a Porcine Model; Molecular Diversity Preservation International; Entropy; 25; 2; 1-2023; 1-15
1099-4300
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/1099-4300/25/2/267
info:eu-repo/semantics/altIdentifier/doi/10.3390/e25020267
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Molecular Diversity Preservation International
publisher.none.fl_str_mv Molecular Diversity Preservation International
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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