Variations in end‐of‐life care practices in older critically ill patients with COVID‐19 in Europe

Background Previous studies reported regional differences in end‐of‐life care (EoLC) for critically ill patients in Europe. Objectives The purpose of this post‐hoc analysis of the prospective multicentre COVIP study was to investigate variations in EoLC practices among older patients in intensive ca...

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Veröffentlicht in:Journal of Internal Medicine 2022-09, Vol.292 (3), p.438-449
Hauptverfasser: Wernly, Bernhard, Rezar, Richard, Flaatten, Hans, Beil, Michael, Fjølner, Jesper, Bruno, Raphael R., Artigas, Antonio, Pinto, Bernardo B., Schefold, Joerg C., Kelm, Malte, Sigal, Sviri, Heerden, Peter V., Szczeklik, Wojciech, Elhadi, Muhammed, Joannidis, Michael, Oeyen, Sandra, Wolff, Georg, Marsh, Brian, Andersen, Finn H., Moreno, Rui, Leaver, Susannah, Wernly, Sarah, Boumendil, Ariane, De Lange, Dylan W., Guidet, Bertrand, Jung, Christian
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container_end_page 449
container_issue 3
container_start_page 438
container_title Journal of Internal Medicine
container_volume 292
creator Wernly, Bernhard
Rezar, Richard
Flaatten, Hans
Beil, Michael
Fjølner, Jesper
Bruno, Raphael R.
Artigas, Antonio
Pinto, Bernardo B.
Schefold, Joerg C.
Kelm, Malte
Sigal, Sviri
Heerden, Peter V.
Szczeklik, Wojciech
Elhadi, Muhammed
Joannidis, Michael
Oeyen, Sandra
Wolff, Georg
Marsh, Brian
Andersen, Finn H.
Moreno, Rui
Leaver, Susannah
Wernly, Sarah
Boumendil, Ariane
De Lange, Dylan W.
Guidet, Bertrand
Jung, Christian
description Background Previous studies reported regional differences in end‐of‐life care (EoLC) for critically ill patients in Europe. Objectives The purpose of this post‐hoc analysis of the prospective multicentre COVIP study was to investigate variations in EoLC practices among older patients in intensive care units during the coronavirus disease 2019 pandemic. Methods A total of 3105 critically ill patients aged 70 years and older were enrolled in this study (Central Europe: n = 1573; Northern Europe: n = 821; Southern Europe: n = 711). Generalised estimation equations were used to calculate adjusted odds ratios (aORs) to population averages. Data were adjusted for patient‐specific variables (demographic, disease‐specific) and health economic data (gross domestic product, health expenditure per capita). The primary outcome was any treatment limitation, and 90‐day mortality was a secondary outcome. Results The frequency of the primary endpoint (treatment limitation) was highest in Northern Europe (48%), intermediate in Central Europe (39%) and lowest in Southern Europe (24%). The likelihood for treatment limitations was lower in Southern than in Central Europe (aOR 0.39; 95% confidence interval [CI] 0.21–0.73; p = 0.004), even after multivariable adjustment, whereas no statistically significant differences were observed between Northern and Central Europe (aOR 0.57; 95%CI 0.27–1.22; p = 0.15). After multivariable adjustment, no statistically relevant mortality differences were found between Northern and Central Europe (aOR 1.29; 95%CI 0.80–2.09; p = 0.30) or between Southern and Central Europe (aOR 1.07; 95%CI 0.66–1.73; p = 0.78). Conclusion This study shows a north‐to‐south gradient in rates of treatment limitation in Europe, highlighting the heterogeneity of EoLC practices across countries. However, mortality rates were not affected by these results.    
doi_str_mv 10.1111/joim.13492
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Objectives The purpose of this post‐hoc analysis of the prospective multicentre COVIP study was to investigate variations in EoLC practices among older patients in intensive care units during the coronavirus disease 2019 pandemic. Methods A total of 3105 critically ill patients aged 70 years and older were enrolled in this study (Central Europe: n = 1573; Northern Europe: n = 821; Southern Europe: n = 711). Generalised estimation equations were used to calculate adjusted odds ratios (aORs) to population averages. Data were adjusted for patient‐specific variables (demographic, disease‐specific) and health economic data (gross domestic product, health expenditure per capita). The primary outcome was any treatment limitation, and 90‐day mortality was a secondary outcome. Results The frequency of the primary endpoint (treatment limitation) was highest in Northern Europe (48%), intermediate in Central Europe (39%) and lowest in Southern Europe (24%). The likelihood for treatment limitations was lower in Southern than in Central Europe (aOR 0.39; 95% confidence interval [CI] 0.21–0.73; p = 0.004), even after multivariable adjustment, whereas no statistically significant differences were observed between Northern and Central Europe (aOR 0.57; 95%CI 0.27–1.22; p = 0.15). After multivariable adjustment, no statistically relevant mortality differences were found between Northern and Central Europe (aOR 1.29; 95%CI 0.80–2.09; p = 0.30) or between Southern and Central Europe (aOR 1.07; 95%CI 0.66–1.73; p = 0.78). Conclusion This study shows a north‐to‐south gradient in rates of treatment limitation in Europe, highlighting the heterogeneity of EoLC practices across countries. However, mortality rates were not affected by these results.    </description><identifier>ISSN: 0954-6820</identifier><identifier>EISSN: 1365-2796</identifier><identifier>DOI: 10.1111/joim.13492</identifier><identifier>PMID: 35398948</identifier><language>eng</language><publisher>England: Blackwell Publishing Ltd</publisher><subject>Confidence intervals ; Coronaviruses ; COVID-19 ; critical care ; Demographic variables ; frail elderly ; Heterogeneity ; Hospitals ; Intensive care units ; Life Sciences ; Mathematical analysis ; Mortality ; Original ; Pandemics ; Patients ; public health systems research ; resuscitation orders ; Statistical analysis ; Viral diseases</subject><ispartof>Journal of Internal Medicine, 2022-09, Vol.292 (3), p.438-449</ispartof><rights>2022 The Authors. published by John Wiley &amp; Sons Ltd on behalf of Association for Publication of The Journal of Internal Medicine.</rights><rights>2022 The Authors. Journal of Internal Medicine published by John Wiley &amp; Sons Ltd on behalf of Association for Publication of The Journal of Internal Medicine.</rights><rights>2022. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). 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Objectives The purpose of this post‐hoc analysis of the prospective multicentre COVIP study was to investigate variations in EoLC practices among older patients in intensive care units during the coronavirus disease 2019 pandemic. Methods A total of 3105 critically ill patients aged 70 years and older were enrolled in this study (Central Europe: n = 1573; Northern Europe: n = 821; Southern Europe: n = 711). Generalised estimation equations were used to calculate adjusted odds ratios (aORs) to population averages. Data were adjusted for patient‐specific variables (demographic, disease‐specific) and health economic data (gross domestic product, health expenditure per capita). The primary outcome was any treatment limitation, and 90‐day mortality was a secondary outcome. Results The frequency of the primary endpoint (treatment limitation) was highest in Northern Europe (48%), intermediate in Central Europe (39%) and lowest in Southern Europe (24%). The likelihood for treatment limitations was lower in Southern than in Central Europe (aOR 0.39; 95% confidence interval [CI] 0.21–0.73; p = 0.004), even after multivariable adjustment, whereas no statistically significant differences were observed between Northern and Central Europe (aOR 0.57; 95%CI 0.27–1.22; p = 0.15). After multivariable adjustment, no statistically relevant mortality differences were found between Northern and Central Europe (aOR 1.29; 95%CI 0.80–2.09; p = 0.30) or between Southern and Central Europe (aOR 1.07; 95%CI 0.66–1.73; p = 0.78). Conclusion This study shows a north‐to‐south gradient in rates of treatment limitation in Europe, highlighting the heterogeneity of EoLC practices across countries. However, mortality rates were not affected by these results.    </description><subject>Confidence intervals</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>critical care</subject><subject>Demographic variables</subject><subject>frail elderly</subject><subject>Heterogeneity</subject><subject>Hospitals</subject><subject>Intensive care units</subject><subject>Life Sciences</subject><subject>Mathematical analysis</subject><subject>Mortality</subject><subject>Original</subject><subject>Pandemics</subject><subject>Patients</subject><subject>public health systems research</subject><subject>resuscitation orders</subject><subject>Statistical analysis</subject><subject>Viral diseases</subject><issn>0954-6820</issn><issn>1365-2796</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><recordid>eNp9kc1uEzEUhS0EomlgwwOgkdgA0hT_jJ3xBqkKhQYFZQPdWo5zp3HkjFN7plV2fQSekSfhplMq6AIvbOn6u8f3-BDyitEThuvDJvrtCROV5k_IiAklSz7R6ikZUS2rUtWcHpHjnDeUMkEVfU6OhBS61lU9IpcXNnnb-djmwrcFtKtftz9jg1vwDRTOJih2ybrOO7gjYlhBKlzyWLEh7AsfQrFDBWi7XNz4bl1MFxezT6jA9KHhrE9xBy_Is8aGDC_vzzH58fns-_S8nC--zKan89JVNedlRRVQyqXmjXSg0IBVS-6ksgzkRCzVRKjKNSCclkhy5kADY8ou0apeKTEmHwfdXb_cwsrhVMkGs0t-a9PeROvNvzetX5vLeG00Y5JzjgLvBoH1o7bz07k51KiotWQ1v2bIvr1_LMWrHnJntj47CMG2EPtsuMJMpKQ49Zi8eYRuYp9a_Aqk9ERU6LVC6v1AuRRzTtA8TMCoOWRtDlmbu6wRfv231Qf0T7gIsAG48QH2_5EyXxezb4Pob6lOtfA</recordid><startdate>202209</startdate><enddate>202209</enddate><creator>Wernly, Bernhard</creator><creator>Rezar, Richard</creator><creator>Flaatten, Hans</creator><creator>Beil, Michael</creator><creator>Fjølner, Jesper</creator><creator>Bruno, Raphael R.</creator><creator>Artigas, Antonio</creator><creator>Pinto, Bernardo B.</creator><creator>Schefold, Joerg C.</creator><creator>Kelm, Malte</creator><creator>Sigal, Sviri</creator><creator>Heerden, Peter V.</creator><creator>Szczeklik, Wojciech</creator><creator>Elhadi, Muhammed</creator><creator>Joannidis, Michael</creator><creator>Oeyen, Sandra</creator><creator>Wolff, Georg</creator><creator>Marsh, Brian</creator><creator>Andersen, Finn H.</creator><creator>Moreno, Rui</creator><creator>Leaver, Susannah</creator><creator>Wernly, Sarah</creator><creator>Boumendil, Ariane</creator><creator>De Lange, Dylan W.</creator><creator>Guidet, Bertrand</creator><creator>Jung, Christian</creator><general>Blackwell Publishing Ltd</general><general>John Wiley and Sons Inc</general><scope>24P</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QL</scope><scope>C1K</scope><scope>K9.</scope><scope>7X8</scope><scope>1XC</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-4024-0220</orcidid><orcidid>https://orcid.org/0000-0001-9264-3115</orcidid><orcidid>https://orcid.org/0000-0002-7118-501X</orcidid><orcidid>https://orcid.org/0000-0003-3776-3530</orcidid><orcidid>https://orcid.org/0000-0002-7643-6770</orcidid></search><sort><creationdate>202209</creationdate><title>Variations in end‐of‐life care practices in older critically ill patients with COVID‐19 in Europe</title><author>Wernly, Bernhard ; Rezar, Richard ; Flaatten, Hans ; Beil, Michael ; Fjølner, Jesper ; Bruno, Raphael R. ; Artigas, Antonio ; Pinto, Bernardo B. ; Schefold, Joerg C. ; Kelm, Malte ; Sigal, Sviri ; Heerden, Peter V. ; Szczeklik, Wojciech ; Elhadi, Muhammed ; Joannidis, Michael ; Oeyen, Sandra ; Wolff, Georg ; Marsh, Brian ; Andersen, Finn H. ; Moreno, Rui ; Leaver, Susannah ; Wernly, Sarah ; Boumendil, Ariane ; De Lange, Dylan W. ; Guidet, Bertrand ; Jung, Christian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4822-406e002592f5ce6095a6b2c56a1e573b67364cfe3c956e021ce9e116ab9549d63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Confidence intervals</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>critical care</topic><topic>Demographic variables</topic><topic>frail elderly</topic><topic>Heterogeneity</topic><topic>Hospitals</topic><topic>Intensive care units</topic><topic>Life Sciences</topic><topic>Mathematical analysis</topic><topic>Mortality</topic><topic>Original</topic><topic>Pandemics</topic><topic>Patients</topic><topic>public health systems research</topic><topic>resuscitation orders</topic><topic>Statistical analysis</topic><topic>Viral diseases</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wernly, Bernhard</creatorcontrib><creatorcontrib>Rezar, Richard</creatorcontrib><creatorcontrib>Flaatten, Hans</creatorcontrib><creatorcontrib>Beil, Michael</creatorcontrib><creatorcontrib>Fjølner, Jesper</creatorcontrib><creatorcontrib>Bruno, Raphael R.</creatorcontrib><creatorcontrib>Artigas, Antonio</creatorcontrib><creatorcontrib>Pinto, Bernardo B.</creatorcontrib><creatorcontrib>Schefold, Joerg C.</creatorcontrib><creatorcontrib>Kelm, Malte</creatorcontrib><creatorcontrib>Sigal, Sviri</creatorcontrib><creatorcontrib>Heerden, Peter V.</creatorcontrib><creatorcontrib>Szczeklik, Wojciech</creatorcontrib><creatorcontrib>Elhadi, Muhammed</creatorcontrib><creatorcontrib>Joannidis, Michael</creatorcontrib><creatorcontrib>Oeyen, Sandra</creatorcontrib><creatorcontrib>Wolff, Georg</creatorcontrib><creatorcontrib>Marsh, Brian</creatorcontrib><creatorcontrib>Andersen, Finn H.</creatorcontrib><creatorcontrib>Moreno, Rui</creatorcontrib><creatorcontrib>Leaver, Susannah</creatorcontrib><creatorcontrib>Wernly, Sarah</creatorcontrib><creatorcontrib>Boumendil, Ariane</creatorcontrib><creatorcontrib>De Lange, Dylan W.</creatorcontrib><creatorcontrib>Guidet, Bertrand</creatorcontrib><creatorcontrib>Jung, Christian</creatorcontrib><creatorcontrib>COVIP study group</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of Internal Medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wernly, Bernhard</au><au>Rezar, Richard</au><au>Flaatten, Hans</au><au>Beil, Michael</au><au>Fjølner, Jesper</au><au>Bruno, Raphael R.</au><au>Artigas, Antonio</au><au>Pinto, Bernardo B.</au><au>Schefold, Joerg C.</au><au>Kelm, Malte</au><au>Sigal, Sviri</au><au>Heerden, Peter V.</au><au>Szczeklik, Wojciech</au><au>Elhadi, Muhammed</au><au>Joannidis, Michael</au><au>Oeyen, Sandra</au><au>Wolff, Georg</au><au>Marsh, Brian</au><au>Andersen, Finn H.</au><au>Moreno, Rui</au><au>Leaver, Susannah</au><au>Wernly, Sarah</au><au>Boumendil, Ariane</au><au>De Lange, Dylan W.</au><au>Guidet, Bertrand</au><au>Jung, Christian</au><aucorp>COVIP study group</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Variations in end‐of‐life care practices in older critically ill patients with COVID‐19 in Europe</atitle><jtitle>Journal of Internal Medicine</jtitle><addtitle>J Intern Med</addtitle><date>2022-09</date><risdate>2022</risdate><volume>292</volume><issue>3</issue><spage>438</spage><epage>449</epage><pages>438-449</pages><issn>0954-6820</issn><eissn>1365-2796</eissn><abstract>Background Previous studies reported regional differences in end‐of‐life care (EoLC) for critically ill patients in Europe. Objectives The purpose of this post‐hoc analysis of the prospective multicentre COVIP study was to investigate variations in EoLC practices among older patients in intensive care units during the coronavirus disease 2019 pandemic. Methods A total of 3105 critically ill patients aged 70 years and older were enrolled in this study (Central Europe: n = 1573; Northern Europe: n = 821; Southern Europe: n = 711). Generalised estimation equations were used to calculate adjusted odds ratios (aORs) to population averages. Data were adjusted for patient‐specific variables (demographic, disease‐specific) and health economic data (gross domestic product, health expenditure per capita). The primary outcome was any treatment limitation, and 90‐day mortality was a secondary outcome. Results The frequency of the primary endpoint (treatment limitation) was highest in Northern Europe (48%), intermediate in Central Europe (39%) and lowest in Southern Europe (24%). The likelihood for treatment limitations was lower in Southern than in Central Europe (aOR 0.39; 95% confidence interval [CI] 0.21–0.73; p = 0.004), even after multivariable adjustment, whereas no statistically significant differences were observed between Northern and Central Europe (aOR 0.57; 95%CI 0.27–1.22; p = 0.15). After multivariable adjustment, no statistically relevant mortality differences were found between Northern and Central Europe (aOR 1.29; 95%CI 0.80–2.09; p = 0.30) or between Southern and Central Europe (aOR 1.07; 95%CI 0.66–1.73; p = 0.78). Conclusion This study shows a north‐to‐south gradient in rates of treatment limitation in Europe, highlighting the heterogeneity of EoLC practices across countries. However, mortality rates were not affected by these results.    </abstract><cop>England</cop><pub>Blackwell Publishing Ltd</pub><pmid>35398948</pmid><doi>10.1111/joim.13492</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0003-4024-0220</orcidid><orcidid>https://orcid.org/0000-0001-9264-3115</orcidid><orcidid>https://orcid.org/0000-0002-7118-501X</orcidid><orcidid>https://orcid.org/0000-0003-3776-3530</orcidid><orcidid>https://orcid.org/0000-0002-7643-6770</orcidid><oa>free_for_read</oa></addata></record>
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subjects Confidence intervals
Coronaviruses
COVID-19
critical care
Demographic variables
frail elderly
Heterogeneity
Hospitals
Intensive care units
Life Sciences
Mathematical analysis
Mortality
Original
Pandemics
Patients
public health systems research
resuscitation orders
Statistical analysis
Viral diseases
title Variations in end‐of‐life care practices in older critically ill patients with COVID‐19 in Europe
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