Bioelectric impedance vector analysis (BIVA) in hospitalised children; predictors and associations with clinical outcomes
Background Clinical use of bioelectric impedance is limited by variability in hydration. Analysis of raw bioelectric impedance vectors (BIVA), resistance (R), reactance (Xc) and phase angle (PA) may be an alternative for monitoring disease progression/treatment. Clinical experience of BIVA in childr...
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creator | Roche, S. Lara-Pompa, N. E. Macdonald, S. Fawbert, K. Valente, J. Williams, J. E. Hill, S. Wells, J. C. Fewtrell, M. S. |
description | Background
Clinical use of bioelectric impedance is limited by variability in hydration. Analysis of raw bioelectric impedance vectors (BIVA), resistance (R), reactance (Xc) and phase angle (PA) may be an alternative for monitoring disease progression/treatment. Clinical experience of BIVA in children is limited. We investigated predictors of BIVA and their ability to predict clinical outcomes in children with complex diagnoses.
Methods
R, Xc and PA were measured (BODYSTAT Quadscan 4000) on admission in 108 patients (4.6–16.8 years, mean 10.0). R and Xc were indexed by height (H) and BIVA-SDS for age and sex calculated using data from healthy children. Potential predictors and clinical outcomes (greater-than-expected length-of-stay (LOS), complications) were recorded.
Results
Mean R/H-SDS was significantly higher (0.99 (SD 1.32)) and PA-SDS lower (−1.22 (1.68))) than expected, with a wide range for all parameters. In multivariate models, the Strongkids risk category predicted R/H-SDS (adjusted mean for low, medium and high risk = 0.49, 1.28, 2.17,
p
= 0.009) and PA-SDS (adjusted mean −0.52, −1.53, −2.36,
p
= 0.01). BIVA-SDS were not significantly different in patients with or without adverse outcomes.
Conclusions
These complex patients had abnormal mean BIVA-SDS suggestive of reduced hydration and poor cellular health according to conventional interpretation. R/H-SDS was higher and PA-SDS lower in those classified as higher malnutrition risk by the StrongKids tool. Further investigation in specific patient groups, including those with acute fluid shifts and using disease-specific outcomes, may better define the clinical role of BIV. |
doi_str_mv | 10.1038/s41430-019-0436-7 |
format | Article |
fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_miscellaneous_2231912466</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A601578889</galeid><sourcerecordid>A601578889</sourcerecordid><originalsourceid>FETCH-LOGICAL-c551t-884990fbc2266390d8549cc2b71611ebd404e887e06e86b96bb1f9cf6b7bfe763</originalsourceid><addsrcrecordid>eNp1kk2L1TAUhosoznX0B7iRgCDjomPSpvnA1Z3Bj4EBN-o2pOnpbYY0qUmr3H9v6h0dR65kETjnec_i4S2K5wSfE1yLN4kSWuMSE1liWrOSPyg2hHJWNozih8UGy4aWNcb8pHiS0g3Gecmrx8VJTTBnrGGbYn9hAzgwc7QG2XGCTnsD6HuehIi0126fbEJnF1dft6-R9WgIabKzdjZBh8xgXRfBv0VThM6umZRDHdIpBWP1bINP6IedB2Sc9dZoh8IymzBCelo86rVL8Oz2Py2-vH_3-fJjef3pw9Xl9ro0TUPmUggqJe5bU1WM1RJ3oqHSmKrlhBECbUcxBSE4YAaCtZK1Leml6VnL2x44q0-Ls8PdKYZvC6RZjTYZcE57CEtSVVUTSSrKVvTlP-hNWGJ2kKmskbBsubqjdtqBsr4Pc9RmPaq2DJOGCyFkpsoj1A48RO2Ch97m8T3-_AifXwejNUcDr_4KDKDdPKTgll_O74PkAJoYUorQqynaUce9IlitPVKHHqncI7X2SPGceXFrYmlH6P4kfhcnA9UBSHnldxDvVP3_6k-1R9DK</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2300160432</pqid></control><display><type>article</type><title>Bioelectric impedance vector analysis (BIVA) in hospitalised children; predictors and associations with clinical outcomes</title><source>Alma/SFX Local Collection</source><creator>Roche, S. ; Lara-Pompa, N. E. ; Macdonald, S. ; Fawbert, K. ; Valente, J. ; Williams, J. E. ; Hill, S. ; Wells, J. C. ; Fewtrell, M. S.</creator><creatorcontrib>Roche, S. ; Lara-Pompa, N. E. ; Macdonald, S. ; Fawbert, K. ; Valente, J. ; Williams, J. E. ; Hill, S. ; Wells, J. C. ; Fewtrell, M. S.</creatorcontrib><description>Background
Clinical use of bioelectric impedance is limited by variability in hydration. Analysis of raw bioelectric impedance vectors (BIVA), resistance (R), reactance (Xc) and phase angle (PA) may be an alternative for monitoring disease progression/treatment. Clinical experience of BIVA in children is limited. We investigated predictors of BIVA and their ability to predict clinical outcomes in children with complex diagnoses.
Methods
R, Xc and PA were measured (BODYSTAT Quadscan 4000) on admission in 108 patients (4.6–16.8 years, mean 10.0). R and Xc were indexed by height (H) and BIVA-SDS for age and sex calculated using data from healthy children. Potential predictors and clinical outcomes (greater-than-expected length-of-stay (LOS), complications) were recorded.
Results
Mean R/H-SDS was significantly higher (0.99 (SD 1.32)) and PA-SDS lower (−1.22 (1.68))) than expected, with a wide range for all parameters. In multivariate models, the Strongkids risk category predicted R/H-SDS (adjusted mean for low, medium and high risk = 0.49, 1.28, 2.17,
p
= 0.009) and PA-SDS (adjusted mean −0.52, −1.53, −2.36,
p
= 0.01). BIVA-SDS were not significantly different in patients with or without adverse outcomes.
Conclusions
These complex patients had abnormal mean BIVA-SDS suggestive of reduced hydration and poor cellular health according to conventional interpretation. R/H-SDS was higher and PA-SDS lower in those classified as higher malnutrition risk by the StrongKids tool. Further investigation in specific patient groups, including those with acute fluid shifts and using disease-specific outcomes, may better define the clinical role of BIV.</description><identifier>ISSN: 0954-3007</identifier><identifier>EISSN: 1476-5640</identifier><identifier>DOI: 10.1038/s41430-019-0436-7</identifier><identifier>PMID: 31076656</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>631/1647/245 ; 692/308/575 ; 692/53 ; Bioelectricity ; Children ; Clinical Nutrition ; Clinical outcomes ; Disease control ; Epidemiology ; Hydration ; Impedance ; Internal Medicine ; Malnutrition ; Medicine ; Medicine & Public Health ; Metabolic Diseases ; Patients ; Public Health ; Reactance ; Risk ; Vector analysis</subject><ispartof>European journal of clinical nutrition, 2019-10, Vol.73 (10), p.1431-1440</ispartof><rights>Springer Nature Limited 2019</rights><rights>COPYRIGHT 2019 Nature Publishing Group</rights><rights>Springer Nature Limited 2019.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c551t-884990fbc2266390d8549cc2b71611ebd404e887e06e86b96bb1f9cf6b7bfe763</citedby><cites>FETCH-LOGICAL-c551t-884990fbc2266390d8549cc2b71611ebd404e887e06e86b96bb1f9cf6b7bfe763</cites><orcidid>0000-0001-9783-3444 ; 0000-0001-6751-0636</orcidid></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/31076656$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Roche, S.</creatorcontrib><creatorcontrib>Lara-Pompa, N. E.</creatorcontrib><creatorcontrib>Macdonald, S.</creatorcontrib><creatorcontrib>Fawbert, K.</creatorcontrib><creatorcontrib>Valente, J.</creatorcontrib><creatorcontrib>Williams, J. E.</creatorcontrib><creatorcontrib>Hill, S.</creatorcontrib><creatorcontrib>Wells, J. C.</creatorcontrib><creatorcontrib>Fewtrell, M. S.</creatorcontrib><title>Bioelectric impedance vector analysis (BIVA) in hospitalised children; predictors and associations with clinical outcomes</title><title>European journal of clinical nutrition</title><addtitle>Eur J Clin Nutr</addtitle><addtitle>Eur J Clin Nutr</addtitle><description>Background
Clinical use of bioelectric impedance is limited by variability in hydration. Analysis of raw bioelectric impedance vectors (BIVA), resistance (R), reactance (Xc) and phase angle (PA) may be an alternative for monitoring disease progression/treatment. Clinical experience of BIVA in children is limited. We investigated predictors of BIVA and their ability to predict clinical outcomes in children with complex diagnoses.
Methods
R, Xc and PA were measured (BODYSTAT Quadscan 4000) on admission in 108 patients (4.6–16.8 years, mean 10.0). R and Xc were indexed by height (H) and BIVA-SDS for age and sex calculated using data from healthy children. Potential predictors and clinical outcomes (greater-than-expected length-of-stay (LOS), complications) were recorded.
Results
Mean R/H-SDS was significantly higher (0.99 (SD 1.32)) and PA-SDS lower (−1.22 (1.68))) than expected, with a wide range for all parameters. In multivariate models, the Strongkids risk category predicted R/H-SDS (adjusted mean for low, medium and high risk = 0.49, 1.28, 2.17,
p
= 0.009) and PA-SDS (adjusted mean −0.52, −1.53, −2.36,
p
= 0.01). BIVA-SDS were not significantly different in patients with or without adverse outcomes.
Conclusions
These complex patients had abnormal mean BIVA-SDS suggestive of reduced hydration and poor cellular health according to conventional interpretation. R/H-SDS was higher and PA-SDS lower in those classified as higher malnutrition risk by the StrongKids tool. Further investigation in specific patient groups, including those with acute fluid shifts and using disease-specific outcomes, may better define the clinical role of BIV.</description><subject>631/1647/245</subject><subject>692/308/575</subject><subject>692/53</subject><subject>Bioelectricity</subject><subject>Children</subject><subject>Clinical Nutrition</subject><subject>Clinical outcomes</subject><subject>Disease control</subject><subject>Epidemiology</subject><subject>Hydration</subject><subject>Impedance</subject><subject>Internal Medicine</subject><subject>Malnutrition</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Metabolic Diseases</subject><subject>Patients</subject><subject>Public Health</subject><subject>Reactance</subject><subject>Risk</subject><subject>Vector analysis</subject><issn>0954-3007</issn><issn>1476-5640</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp1kk2L1TAUhosoznX0B7iRgCDjomPSpvnA1Z3Bj4EBN-o2pOnpbYY0qUmr3H9v6h0dR65kETjnec_i4S2K5wSfE1yLN4kSWuMSE1liWrOSPyg2hHJWNozih8UGy4aWNcb8pHiS0g3Gecmrx8VJTTBnrGGbYn9hAzgwc7QG2XGCTnsD6HuehIi0126fbEJnF1dft6-R9WgIabKzdjZBh8xgXRfBv0VThM6umZRDHdIpBWP1bINP6IedB2Sc9dZoh8IymzBCelo86rVL8Oz2Py2-vH_3-fJjef3pw9Xl9ro0TUPmUggqJe5bU1WM1RJ3oqHSmKrlhBECbUcxBSE4YAaCtZK1Leml6VnL2x44q0-Ls8PdKYZvC6RZjTYZcE57CEtSVVUTSSrKVvTlP-hNWGJ2kKmskbBsubqjdtqBsr4Pc9RmPaq2DJOGCyFkpsoj1A48RO2Ch97m8T3-_AifXwejNUcDr_4KDKDdPKTgll_O74PkAJoYUorQqynaUce9IlitPVKHHqncI7X2SPGceXFrYmlH6P4kfhcnA9UBSHnldxDvVP3_6k-1R9DK</recordid><startdate>20191001</startdate><enddate>20191001</enddate><creator>Roche, S.</creator><creator>Lara-Pompa, N. E.</creator><creator>Macdonald, S.</creator><creator>Fawbert, K.</creator><creator>Valente, J.</creator><creator>Williams, J. E.</creator><creator>Hill, S.</creator><creator>Wells, J. C.</creator><creator>Fewtrell, M. S.</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QP</scope><scope>7RV</scope><scope>7TK</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AN0</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>M7P</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-9783-3444</orcidid><orcidid>https://orcid.org/0000-0001-6751-0636</orcidid></search><sort><creationdate>20191001</creationdate><title>Bioelectric impedance vector analysis (BIVA) in hospitalised children; predictors and associations with clinical outcomes</title><author>Roche, S. ; Lara-Pompa, N. E. ; Macdonald, S. ; Fawbert, K. ; Valente, J. ; Williams, J. E. ; Hill, S. ; Wells, J. C. ; Fewtrell, M. S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c551t-884990fbc2266390d8549cc2b71611ebd404e887e06e86b96bb1f9cf6b7bfe763</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>631/1647/245</topic><topic>692/308/575</topic><topic>692/53</topic><topic>Bioelectricity</topic><topic>Children</topic><topic>Clinical Nutrition</topic><topic>Clinical outcomes</topic><topic>Disease control</topic><topic>Epidemiology</topic><topic>Hydration</topic><topic>Impedance</topic><topic>Internal Medicine</topic><topic>Malnutrition</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Metabolic Diseases</topic><topic>Patients</topic><topic>Public Health</topic><topic>Reactance</topic><topic>Risk</topic><topic>Vector analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Roche, S.</creatorcontrib><creatorcontrib>Lara-Pompa, N. E.</creatorcontrib><creatorcontrib>Macdonald, S.</creatorcontrib><creatorcontrib>Fawbert, K.</creatorcontrib><creatorcontrib>Valente, J.</creatorcontrib><creatorcontrib>Williams, J. E.</creatorcontrib><creatorcontrib>Hill, S.</creatorcontrib><creatorcontrib>Wells, J. C.</creatorcontrib><creatorcontrib>Fewtrell, M. S.</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Neurosciences Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>British Nursing Database</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</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>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>European journal of clinical nutrition</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Roche, S.</au><au>Lara-Pompa, N. E.</au><au>Macdonald, S.</au><au>Fawbert, K.</au><au>Valente, J.</au><au>Williams, J. E.</au><au>Hill, S.</au><au>Wells, J. C.</au><au>Fewtrell, M. S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bioelectric impedance vector analysis (BIVA) in hospitalised children; predictors and associations with clinical outcomes</atitle><jtitle>European journal of clinical nutrition</jtitle><stitle>Eur J Clin Nutr</stitle><addtitle>Eur J Clin Nutr</addtitle><date>2019-10-01</date><risdate>2019</risdate><volume>73</volume><issue>10</issue><spage>1431</spage><epage>1440</epage><pages>1431-1440</pages><issn>0954-3007</issn><eissn>1476-5640</eissn><abstract>Background
Clinical use of bioelectric impedance is limited by variability in hydration. Analysis of raw bioelectric impedance vectors (BIVA), resistance (R), reactance (Xc) and phase angle (PA) may be an alternative for monitoring disease progression/treatment. Clinical experience of BIVA in children is limited. We investigated predictors of BIVA and their ability to predict clinical outcomes in children with complex diagnoses.
Methods
R, Xc and PA were measured (BODYSTAT Quadscan 4000) on admission in 108 patients (4.6–16.8 years, mean 10.0). R and Xc were indexed by height (H) and BIVA-SDS for age and sex calculated using data from healthy children. Potential predictors and clinical outcomes (greater-than-expected length-of-stay (LOS), complications) were recorded.
Results
Mean R/H-SDS was significantly higher (0.99 (SD 1.32)) and PA-SDS lower (−1.22 (1.68))) than expected, with a wide range for all parameters. In multivariate models, the Strongkids risk category predicted R/H-SDS (adjusted mean for low, medium and high risk = 0.49, 1.28, 2.17,
p
= 0.009) and PA-SDS (adjusted mean −0.52, −1.53, −2.36,
p
= 0.01). BIVA-SDS were not significantly different in patients with or without adverse outcomes.
Conclusions
These complex patients had abnormal mean BIVA-SDS suggestive of reduced hydration and poor cellular health according to conventional interpretation. R/H-SDS was higher and PA-SDS lower in those classified as higher malnutrition risk by the StrongKids tool. Further investigation in specific patient groups, including those with acute fluid shifts and using disease-specific outcomes, may better define the clinical role of BIV.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>31076656</pmid><doi>10.1038/s41430-019-0436-7</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-9783-3444</orcidid><orcidid>https://orcid.org/0000-0001-6751-0636</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | 631/1647/245 692/308/575 692/53 Bioelectricity Children Clinical Nutrition Clinical outcomes Disease control Epidemiology Hydration Impedance Internal Medicine Malnutrition Medicine Medicine & Public Health Metabolic Diseases Patients Public Health Reactance Risk Vector analysis |
title | Bioelectric impedance vector analysis (BIVA) in hospitalised children; predictors and associations with clinical outcomes |
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