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Intermittent body composition analysis as monitoring tool for muscle wasting in critically ill COVID-19 patients
Objectives SARS-CoV-2 virus infection can lead to acute respiratory distress syndrome (ARDS), which can be complicated by severe muscle wasting. Until now, data on muscle loss of critically ill COVID-19 patients are limited, while computed tomography (CT) scans for clinical follow-up are available....
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| Published in: | Annals of intensive care 2023-07, Vol.13 (1), p.61-61, Article 61 |
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| container_end_page | 61 |
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| container_title | Annals of intensive care |
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| creator | Kolck, Johannes Rako, Zvonimir A. Beetz, Nick L. Auer, Timo A. Segger, Laura K. Pille, Christian Penzkofer, Tobias Fehrenbach, Uli Geisel, Dominik |
| description | Objectives
SARS-CoV-2 virus infection can lead to acute respiratory distress syndrome (ARDS), which can be complicated by severe muscle wasting. Until now, data on muscle loss of critically ill COVID-19 patients are limited, while computed tomography (CT) scans for clinical follow-up are available. We sought to investigate the parameters of muscle wasting in these patients by being the first to test the clinical application of body composition analysis (BCA) as an intermittent monitoring tool.
Materials
BCA was conducted on 54 patients, with a minimum of three measurements taken during hospitalization, totaling 239 assessments. Changes in psoas- (PMA) and total abdominal muscle area (TAMA) were assessed by linear mixed model analysis. PMA was calculated as relative muscle loss per day for the entire monitoring period, as well as for the interval between each consecutive scan. Cox regression was applied to analyze associations with survival. Receiver operating characteristic (ROC) analysis and Youden index were used to define a decay cut-off.
Results
Intermittent BCA revealed significantly higher long-term PMA loss rates of 2.62% (vs. 1.16%,
p
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| doi_str_mv | 10.1186/s13613-023-01162-5 |
| format | article |
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SARS-CoV-2 virus infection can lead to acute respiratory distress syndrome (ARDS), which can be complicated by severe muscle wasting. Until now, data on muscle loss of critically ill COVID-19 patients are limited, while computed tomography (CT) scans for clinical follow-up are available. We sought to investigate the parameters of muscle wasting in these patients by being the first to test the clinical application of body composition analysis (BCA) as an intermittent monitoring tool.
Materials
BCA was conducted on 54 patients, with a minimum of three measurements taken during hospitalization, totaling 239 assessments. Changes in psoas- (PMA) and total abdominal muscle area (TAMA) were assessed by linear mixed model analysis. PMA was calculated as relative muscle loss per day for the entire monitoring period, as well as for the interval between each consecutive scan. Cox regression was applied to analyze associations with survival. Receiver operating characteristic (ROC) analysis and Youden index were used to define a decay cut-off.
Results
Intermittent BCA revealed significantly higher long-term PMA loss rates of 2.62% (vs. 1.16%,
p
< 0.001) and maximum muscle decay of 5.48% (vs. 3.66%,
p
= 0.039) per day in non-survivors. The first available decay rate did not significantly differ between survival groups but showed significant associations with survival in Cox regression (
p
= 0.011). In ROC analysis, PMA loss averaged over the stay had the greatest discriminatory power (AUC = 0.777) for survival. A long-term PMA decline per day of 1.84% was defined as a threshold; muscle loss beyond this cut-off proved to be a significant BCA-derived predictor of mortality.
Conclusion
Muscle wasting in critically ill COVID-19 patients is severe and correlates with survival. Intermittent BCA derived from clinically indicated CT scans proved to be a valuable monitoring tool, which allows identification of individuals at risk for adverse outcomes and has great potential to support critical care decision-making.</description><identifier>ISSN: 2110-5820</identifier><identifier>EISSN: 2110-5820</identifier><identifier>DOI: 10.1186/s13613-023-01162-5</identifier><identifier>PMID: 37421448</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Anesthesiology ; Artificial intelligence ; Body composition ; Body composition analysis ; Body measurements ; Computed tomography ; COVID-19 ; Critical care ; Critical Care Medicine ; Emergency Medicine ; Intensive ; Intensive care ; Medicine ; Medicine & Public Health ; Muscle wasting ; Sarcopenia ; Severe acute respiratory syndrome coronavirus 2 ; Tomography</subject><ispartof>Annals of intensive care, 2023-07, Vol.13 (1), p.61-61, Article 61</ispartof><rights>The Author(s) 2023</rights><rights>2023. The Author(s).</rights><rights>The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c608t-8f07d8fb101735cec5b7aedb0deb1b9183d84941dea59e0880627af2f9cf0b1f3</citedby><cites>FETCH-LOGICAL-c608t-8f07d8fb101735cec5b7aedb0deb1b9183d84941dea59e0880627af2f9cf0b1f3</cites><orcidid>0000-0001-9843-2247</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2834540014/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2834540014?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,25732,27903,27904,36991,36992,38495,43874,44569,53770,53772,74159,74873</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37421448$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kolck, Johannes</creatorcontrib><creatorcontrib>Rako, Zvonimir A.</creatorcontrib><creatorcontrib>Beetz, Nick L.</creatorcontrib><creatorcontrib>Auer, Timo A.</creatorcontrib><creatorcontrib>Segger, Laura K.</creatorcontrib><creatorcontrib>Pille, Christian</creatorcontrib><creatorcontrib>Penzkofer, Tobias</creatorcontrib><creatorcontrib>Fehrenbach, Uli</creatorcontrib><creatorcontrib>Geisel, Dominik</creatorcontrib><title>Intermittent body composition analysis as monitoring tool for muscle wasting in critically ill COVID-19 patients</title><title>Annals of intensive care</title><addtitle>Ann. Intensive Care</addtitle><addtitle>Ann Intensive Care</addtitle><description>Objectives
SARS-CoV-2 virus infection can lead to acute respiratory distress syndrome (ARDS), which can be complicated by severe muscle wasting. Until now, data on muscle loss of critically ill COVID-19 patients are limited, while computed tomography (CT) scans for clinical follow-up are available. We sought to investigate the parameters of muscle wasting in these patients by being the first to test the clinical application of body composition analysis (BCA) as an intermittent monitoring tool.
Materials
BCA was conducted on 54 patients, with a minimum of three measurements taken during hospitalization, totaling 239 assessments. Changes in psoas- (PMA) and total abdominal muscle area (TAMA) were assessed by linear mixed model analysis. PMA was calculated as relative muscle loss per day for the entire monitoring period, as well as for the interval between each consecutive scan. Cox regression was applied to analyze associations with survival. Receiver operating characteristic (ROC) analysis and Youden index were used to define a decay cut-off.
Results
Intermittent BCA revealed significantly higher long-term PMA loss rates of 2.62% (vs. 1.16%,
p
< 0.001) and maximum muscle decay of 5.48% (vs. 3.66%,
p
= 0.039) per day in non-survivors. The first available decay rate did not significantly differ between survival groups but showed significant associations with survival in Cox regression (
p
= 0.011). In ROC analysis, PMA loss averaged over the stay had the greatest discriminatory power (AUC = 0.777) for survival. A long-term PMA decline per day of 1.84% was defined as a threshold; muscle loss beyond this cut-off proved to be a significant BCA-derived predictor of mortality.
Conclusion
Muscle wasting in critically ill COVID-19 patients is severe and correlates with survival. Intermittent BCA derived from clinically indicated CT scans proved to be a valuable monitoring tool, which allows identification of individuals at risk for adverse outcomes and has great potential to support critical care decision-making.</description><subject>Anesthesiology</subject><subject>Artificial intelligence</subject><subject>Body composition</subject><subject>Body composition analysis</subject><subject>Body measurements</subject><subject>Computed tomography</subject><subject>COVID-19</subject><subject>Critical care</subject><subject>Critical Care Medicine</subject><subject>Emergency Medicine</subject><subject>Intensive</subject><subject>Intensive care</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Muscle wasting</subject><subject>Sarcopenia</subject><subject>Severe acute respiratory syndrome coronavirus 2</subject><subject>Tomography</subject><issn>2110-5820</issn><issn>2110-5820</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>COVID</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNp9kkFvFCEUxydGY5vaL-DBkHjxMpUHMwxzMmbVukmTXtQrAQZWNswwAqPZby-7U2vrQRICefze_70X_lX1EvAVAGdvE1AGtMakbABG6vZJdU4AcN1ygp8-uJ9VlyntcVkt7gihz6sz2jUEmoafV_N2yiaOLmczZaTCcEA6jHNILrswITlJf0guIZnQGCaXQ3TTDuUQPLIhonFJ2hv0S6Z8jLsJ6VgytfT-gJz3aHP7bfuhhh7NMrtSIr2onlnpk7m8Oy-qr58-ftl8rm9ur7eb9ze1ZpjnmlvcDdwqwNDRVhvdqk6aQeHBKFA9cDrwpm9gMLLtDeYcM9JJS2yvLVZg6UW1XXWHIPdijm6U8SCCdOIUCHEnZCydeiM0IwMzSmPJbUMV6TnhSjOtGafWaF203q1a86JGM-gyR5T-kejjl8l9F7vwUwCmpGe4LQpv7hRi-LGYlMXokjbey8mEJQnCaUtYX0Yq6Ot_0H1YYvmHE9W0DcbQFIqslI4hpWjsfTeAxdEgYjWIKAYRJ4OIYxevHs5xn_LHDgWgK5Dm4z-b-Lf2f2R_A5szyHI</recordid><startdate>20230708</startdate><enddate>20230708</enddate><creator>Kolck, Johannes</creator><creator>Rako, Zvonimir A.</creator><creator>Beetz, Nick L.</creator><creator>Auer, Timo A.</creator><creator>Segger, Laura K.</creator><creator>Pille, Christian</creator><creator>Penzkofer, Tobias</creator><creator>Fehrenbach, Uli</creator><creator>Geisel, Dominik</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><general>SpringerOpen</general><scope>C6C</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>AN0</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>NAPCQ</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-9843-2247</orcidid></search><sort><creationdate>20230708</creationdate><title>Intermittent body composition analysis as monitoring tool for muscle wasting in critically ill COVID-19 patients</title><author>Kolck, Johannes ; Rako, Zvonimir A. ; Beetz, Nick L. ; Auer, Timo A. ; Segger, Laura K. ; Pille, Christian ; Penzkofer, Tobias ; Fehrenbach, Uli ; Geisel, Dominik</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c608t-8f07d8fb101735cec5b7aedb0deb1b9183d84941dea59e0880627af2f9cf0b1f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Anesthesiology</topic><topic>Artificial intelligence</topic><topic>Body composition</topic><topic>Body composition analysis</topic><topic>Body measurements</topic><topic>Computed tomography</topic><topic>COVID-19</topic><topic>Critical care</topic><topic>Critical Care Medicine</topic><topic>Emergency Medicine</topic><topic>Intensive</topic><topic>Intensive care</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Muscle wasting</topic><topic>Sarcopenia</topic><topic>Severe acute respiratory syndrome coronavirus 2</topic><topic>Tomography</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kolck, Johannes</creatorcontrib><creatorcontrib>Rako, Zvonimir A.</creatorcontrib><creatorcontrib>Beetz, Nick L.</creatorcontrib><creatorcontrib>Auer, Timo A.</creatorcontrib><creatorcontrib>Segger, Laura K.</creatorcontrib><creatorcontrib>Pille, Christian</creatorcontrib><creatorcontrib>Penzkofer, Tobias</creatorcontrib><creatorcontrib>Fehrenbach, Uli</creatorcontrib><creatorcontrib>Geisel, Dominik</creatorcontrib><collection>SpringerOpen</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>British Nursing Database</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central</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>Publicly Available Content Database</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 China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Annals of intensive care</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kolck, Johannes</au><au>Rako, Zvonimir A.</au><au>Beetz, Nick L.</au><au>Auer, Timo A.</au><au>Segger, Laura K.</au><au>Pille, Christian</au><au>Penzkofer, Tobias</au><au>Fehrenbach, Uli</au><au>Geisel, Dominik</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Intermittent body composition analysis as monitoring tool for muscle wasting in critically ill COVID-19 patients</atitle><jtitle>Annals of intensive care</jtitle><stitle>Ann. Intensive Care</stitle><addtitle>Ann Intensive Care</addtitle><date>2023-07-08</date><risdate>2023</risdate><volume>13</volume><issue>1</issue><spage>61</spage><epage>61</epage><pages>61-61</pages><artnum>61</artnum><issn>2110-5820</issn><eissn>2110-5820</eissn><abstract>Objectives
SARS-CoV-2 virus infection can lead to acute respiratory distress syndrome (ARDS), which can be complicated by severe muscle wasting. Until now, data on muscle loss of critically ill COVID-19 patients are limited, while computed tomography (CT) scans for clinical follow-up are available. We sought to investigate the parameters of muscle wasting in these patients by being the first to test the clinical application of body composition analysis (BCA) as an intermittent monitoring tool.
Materials
BCA was conducted on 54 patients, with a minimum of three measurements taken during hospitalization, totaling 239 assessments. Changes in psoas- (PMA) and total abdominal muscle area (TAMA) were assessed by linear mixed model analysis. PMA was calculated as relative muscle loss per day for the entire monitoring period, as well as for the interval between each consecutive scan. Cox regression was applied to analyze associations with survival. Receiver operating characteristic (ROC) analysis and Youden index were used to define a decay cut-off.
Results
Intermittent BCA revealed significantly higher long-term PMA loss rates of 2.62% (vs. 1.16%,
p
< 0.001) and maximum muscle decay of 5.48% (vs. 3.66%,
p
= 0.039) per day in non-survivors. The first available decay rate did not significantly differ between survival groups but showed significant associations with survival in Cox regression (
p
= 0.011). In ROC analysis, PMA loss averaged over the stay had the greatest discriminatory power (AUC = 0.777) for survival. A long-term PMA decline per day of 1.84% was defined as a threshold; muscle loss beyond this cut-off proved to be a significant BCA-derived predictor of mortality.
Conclusion
Muscle wasting in critically ill COVID-19 patients is severe and correlates with survival. Intermittent BCA derived from clinically indicated CT scans proved to be a valuable monitoring tool, which allows identification of individuals at risk for adverse outcomes and has great potential to support critical care decision-making.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>37421448</pmid><doi>10.1186/s13613-023-01162-5</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0001-9843-2247</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Annals of intensive care, 2023-07, Vol.13 (1), p.61-61, Article 61 |
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| language | eng |
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| source | Publicly Available Content Database; Springer Nature - SpringerLink Journals - Fully Open Access; PubMed Central; Coronavirus Research Database |
| subjects | Anesthesiology Artificial intelligence Body composition Body composition analysis Body measurements Computed tomography COVID-19 Critical care Critical Care Medicine Emergency Medicine Intensive Intensive care Medicine Medicine & Public Health Muscle wasting Sarcopenia Severe acute respiratory syndrome coronavirus 2 Tomography |
| title | Intermittent body composition analysis as monitoring tool for muscle wasting in critically ill COVID-19 patients |
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