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New approaches to physiological informatics in neurocritical care
A fundamental purpose of neurocritical care is the management of secondary brain injury. This is often accomplished by monitoring and managing individual patient parameters including physiological vital signs. Yet, the ability to record physiological data exceeds our ability to fully integrate it in...
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Published in: | Neurocritical care 2007-08, Vol.7 (1), p.45-52 |
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container_title | Neurocritical care |
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creator | Sorani, Marco D Hemphill, 3rd, J Claude Morabito, Diane Rosenthal, Guy Manley, Geoffrey T |
description | A fundamental purpose of neurocritical care is the management of secondary brain injury. This is often accomplished by monitoring and managing individual patient parameters including physiological vital signs. Yet, the ability to record physiological data exceeds our ability to fully integrate it into patient care. We propose that advances in monitoring must be accompanied by advances in methods of high-frequency, multivariate data analysis that integrate the multiple processes occurring in critically ill patients.
We describe initial work in the emerging field of physiological informatics in critical care medicine. We analyzed data on 23 patients with brain injury from our Neurotrauma and Critical Care Database, which contains more than 20 physiological parameters recorded automatically at one-minute intervals via bedside monitors connected to standard personal computers. We performed exploratory data analysis, studied two patient cases in detail, and implemented a data-driven classification approach using hierarchical clustering.
In this study, we present challenges and opportunities for high-frequency multimodal monitoring to quantitatively detect secondary brain insults, and develop clustering methodology to construct multivariate physiological data "profiles" to classify patients for diagnosis and treatment.
Recording of many physiological variables across multiple patients is feasible and can lead to new clinical insights. Computational and analytical methods previously used primarily for basic science may have clinical relevance and can potentially be adapted to provide physicians with improved ability to integrate complex information for decision making in neurocritical care. |
doi_str_mv | 10.1007/s12028-007-0043-7 |
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We describe initial work in the emerging field of physiological informatics in critical care medicine. We analyzed data on 23 patients with brain injury from our Neurotrauma and Critical Care Database, which contains more than 20 physiological parameters recorded automatically at one-minute intervals via bedside monitors connected to standard personal computers. We performed exploratory data analysis, studied two patient cases in detail, and implemented a data-driven classification approach using hierarchical clustering.
In this study, we present challenges and opportunities for high-frequency multimodal monitoring to quantitatively detect secondary brain insults, and develop clustering methodology to construct multivariate physiological data "profiles" to classify patients for diagnosis and treatment.
Recording of many physiological variables across multiple patients is feasible and can lead to new clinical insights. Computational and analytical methods previously used primarily for basic science may have clinical relevance and can potentially be adapted to provide physicians with improved ability to integrate complex information for decision making in neurocritical care.</description><identifier>ISSN: 1541-6933</identifier><identifier>EISSN: 1556-0961</identifier><identifier>DOI: 10.1007/s12028-007-0043-7</identifier><identifier>PMID: 17565451</identifier><language>eng</language><publisher>United States: Springer Nature B.V</publisher><subject>Adult ; Brain Injuries - complications ; Brain Injuries - physiopathology ; Brain Injuries - therapy ; Cluster Analysis ; Critical Care ; Data analysis ; Humans ; Informatics ; Medical Informatics Applications ; Medical Informatics Computing ; Middle Aged ; Monitoring, Physiologic ; Multivariate Analysis ; Patients ; Physiology ; Point-of-Care Systems ; Traumatic brain injury</subject><ispartof>Neurocritical care, 2007-08, Vol.7 (1), p.45-52</ispartof><rights>Humana Press Inc. 2007.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c401t-2925faa9fccd31ea1e782141314de531b282c0d68b41f4b074245fff2a26e58b3</citedby><cites>FETCH-LOGICAL-c401t-2925faa9fccd31ea1e782141314de531b282c0d68b41f4b074245fff2a26e58b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/17565451$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sorani, Marco D</creatorcontrib><creatorcontrib>Hemphill, 3rd, J Claude</creatorcontrib><creatorcontrib>Morabito, Diane</creatorcontrib><creatorcontrib>Rosenthal, Guy</creatorcontrib><creatorcontrib>Manley, Geoffrey T</creatorcontrib><title>New approaches to physiological informatics in neurocritical care</title><title>Neurocritical care</title><addtitle>Neurocrit Care</addtitle><description>A fundamental purpose of neurocritical care is the management of secondary brain injury. This is often accomplished by monitoring and managing individual patient parameters including physiological vital signs. Yet, the ability to record physiological data exceeds our ability to fully integrate it into patient care. We propose that advances in monitoring must be accompanied by advances in methods of high-frequency, multivariate data analysis that integrate the multiple processes occurring in critically ill patients.
We describe initial work in the emerging field of physiological informatics in critical care medicine. We analyzed data on 23 patients with brain injury from our Neurotrauma and Critical Care Database, which contains more than 20 physiological parameters recorded automatically at one-minute intervals via bedside monitors connected to standard personal computers. We performed exploratory data analysis, studied two patient cases in detail, and implemented a data-driven classification approach using hierarchical clustering.
In this study, we present challenges and opportunities for high-frequency multimodal monitoring to quantitatively detect secondary brain insults, and develop clustering methodology to construct multivariate physiological data "profiles" to classify patients for diagnosis and treatment.
Recording of many physiological variables across multiple patients is feasible and can lead to new clinical insights. Computational and analytical methods previously used primarily for basic science may have clinical relevance and can potentially be adapted to provide physicians with improved ability to integrate complex information for decision making in neurocritical care.</description><subject>Adult</subject><subject>Brain Injuries - complications</subject><subject>Brain Injuries - physiopathology</subject><subject>Brain Injuries - therapy</subject><subject>Cluster Analysis</subject><subject>Critical Care</subject><subject>Data analysis</subject><subject>Humans</subject><subject>Informatics</subject><subject>Medical Informatics Applications</subject><subject>Medical Informatics Computing</subject><subject>Middle Aged</subject><subject>Monitoring, Physiologic</subject><subject>Multivariate Analysis</subject><subject>Patients</subject><subject>Physiology</subject><subject>Point-of-Care Systems</subject><subject>Traumatic brain injury</subject><issn>1541-6933</issn><issn>1556-0961</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><recordid>eNqFkU1LxDAQhoMo7rr6A7xIQfBWzeSzPS6LX7DoRc8hTRO3S9vUpEX239u6C4IXD8O8MM8MM_MidAn4FjCWdxEIJlk6yjEYTeURmgPnIsW5gONJM0hFTukMncW4xZjIXPJTNAPJBWcc5mj5Yr8S3XXBa7OxMel90m12sfK1_6iMrpOqdT40uq9MHHXS2iF4E6r-p2h0sOfoxOk62otDXqD3h_u31VO6fn18Xi3XqWEY-pTkhDutc2dMScFqsDIjwIACKy2nUJCMGFyKrGDgWIElI4w754gmwvKsoAt0s5877vo52NirporG1rVurR-iklgKQnP2L0gAKMHZBF7_Abd-CO14hBq3xVxIKWCkYE-Z4GMM1qkuVI0OOwVYTTaovQ1qkpMNSo49V4fJQ9HY8rfj8Hf6DV7Kgak</recordid><startdate>200708</startdate><enddate>200708</enddate><creator>Sorani, Marco D</creator><creator>Hemphill, 3rd, J Claude</creator><creator>Morabito, Diane</creator><creator>Rosenthal, Guy</creator><creator>Manley, Geoffrey T</creator><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7TK</scope><scope>7X8</scope></search><sort><creationdate>200708</creationdate><title>New approaches to physiological informatics in neurocritical care</title><author>Sorani, Marco D ; Hemphill, 3rd, J Claude ; Morabito, Diane ; Rosenthal, Guy ; Manley, Geoffrey T</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c401t-2925faa9fccd31ea1e782141314de531b282c0d68b41f4b074245fff2a26e58b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Adult</topic><topic>Brain Injuries - complications</topic><topic>Brain Injuries - physiopathology</topic><topic>Brain Injuries - therapy</topic><topic>Cluster Analysis</topic><topic>Critical Care</topic><topic>Data analysis</topic><topic>Humans</topic><topic>Informatics</topic><topic>Medical Informatics Applications</topic><topic>Medical Informatics Computing</topic><topic>Middle Aged</topic><topic>Monitoring, Physiologic</topic><topic>Multivariate Analysis</topic><topic>Patients</topic><topic>Physiology</topic><topic>Point-of-Care Systems</topic><topic>Traumatic brain injury</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sorani, Marco D</creatorcontrib><creatorcontrib>Hemphill, 3rd, J Claude</creatorcontrib><creatorcontrib>Morabito, Diane</creatorcontrib><creatorcontrib>Rosenthal, Guy</creatorcontrib><creatorcontrib>Manley, Geoffrey T</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Nursing & Allied Health Database</collection><collection>ProQuest_Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Neurosciences Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Neurocritical care</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sorani, Marco D</au><au>Hemphill, 3rd, J Claude</au><au>Morabito, Diane</au><au>Rosenthal, Guy</au><au>Manley, Geoffrey T</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>New approaches to physiological informatics in neurocritical care</atitle><jtitle>Neurocritical care</jtitle><addtitle>Neurocrit Care</addtitle><date>2007-08</date><risdate>2007</risdate><volume>7</volume><issue>1</issue><spage>45</spage><epage>52</epage><pages>45-52</pages><issn>1541-6933</issn><eissn>1556-0961</eissn><abstract>A fundamental purpose of neurocritical care is the management of secondary brain injury. This is often accomplished by monitoring and managing individual patient parameters including physiological vital signs. Yet, the ability to record physiological data exceeds our ability to fully integrate it into patient care. We propose that advances in monitoring must be accompanied by advances in methods of high-frequency, multivariate data analysis that integrate the multiple processes occurring in critically ill patients.
We describe initial work in the emerging field of physiological informatics in critical care medicine. We analyzed data on 23 patients with brain injury from our Neurotrauma and Critical Care Database, which contains more than 20 physiological parameters recorded automatically at one-minute intervals via bedside monitors connected to standard personal computers. We performed exploratory data analysis, studied two patient cases in detail, and implemented a data-driven classification approach using hierarchical clustering.
In this study, we present challenges and opportunities for high-frequency multimodal monitoring to quantitatively detect secondary brain insults, and develop clustering methodology to construct multivariate physiological data "profiles" to classify patients for diagnosis and treatment.
Recording of many physiological variables across multiple patients is feasible and can lead to new clinical insights. Computational and analytical methods previously used primarily for basic science may have clinical relevance and can potentially be adapted to provide physicians with improved ability to integrate complex information for decision making in neurocritical care.</abstract><cop>United States</cop><pub>Springer Nature B.V</pub><pmid>17565451</pmid><doi>10.1007/s12028-007-0043-7</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adult Brain Injuries - complications Brain Injuries - physiopathology Brain Injuries - therapy Cluster Analysis Critical Care Data analysis Humans Informatics Medical Informatics Applications Medical Informatics Computing Middle Aged Monitoring, Physiologic Multivariate Analysis Patients Physiology Point-of-Care Systems Traumatic brain injury |
title | New approaches to physiological informatics in neurocritical care |
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