National Early Warning Score 2 (NEWS2) better predicts critical Coronavirus Disease 2019 (COVID-19) illness than COVID-GRAM, a multi-centre study
Purpose Clinical scores to rapidly assess the severity illness of Coronavirus Disease 2019 (COVID-19) could be considered of help for clinicians. Recently, a specific score (named COVID-GRAM) for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection, based on a nationwide Chinese co...
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| Veröffentlicht in: | Infection 2021-10, Vol.49 (5), p.1033-1038 |
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| creator | De Socio, Giuseppe Vittorio Gidari, Anna Sicari, Francesco Palumbo, Michele Francisci, Daniela |
| description | Purpose
Clinical scores to rapidly assess the severity illness of Coronavirus Disease 2019 (COVID-19) could be considered of help for clinicians. Recently, a specific score (named COVID-GRAM) for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection, based on a nationwide Chinese cohort, has been proposed. We routinely applied the National Early Warning Score 2 (NEWS2) to predict critical COVID-19. Aim of this study is to compare NEWS2 and COVID-GRAM score.
Methods
We retrospectively analysed data of 121 COVID-19 patients admitted in two Clinics of Infectious Diseases in the Umbria region, Italy. The primary outcome was critical COVID-19 illness defined as admission to the intensive care unit, invasive ventilation, or death. Accuracy of the scores was evaluated with the area under the receiver-operating characteristic curve (AUROC). Differences between scores were confirmed used Hanley–McNeil test.
Results
The NEWS2 AUROC curve measured 0.87 (standard error, SE 0.03; 95% CI 0.80–0.93;
p
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| doi_str_mv | 10.1007/s15010-021-01620-x |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8108728</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2576738598</sourcerecordid><originalsourceid>FETCH-LOGICAL-c474t-a8b61aa61c501d0ef10587bd2761543c335ea82f1df05b06a6937869023aa9093</originalsourceid><addsrcrecordid>eNp9kc1u1DAUhS0EokPhBVggS2ymEoZrO4ntDVI1HUql0koU6NJyHGfqKpMMtlN1HoM3xtOU8rNgZcn3O-f-HIReUnhLAcS7SEugQIBRArRiQG4foRktuCKgBH-MZsABiKSs2kPPYrwGgFIV4ina41wJKDidoR9nJvmhNx1emtBt8aUJve9X-MIOwWGG52fLywt2gGuXkgt4E1zjbYrYBp-8zbLFELL8xocx4iMfnYlZBlTh-eL828kRoeoA-67rXYw4XZkeT9_Hnw8_vcEGr8cueWJdn3K7mMZm-xw9aU0X3Yv7dx99_bD8svhITs-PTxaHp8QWokjEyLqixlTU5iM04FoKpRR1w0RFy4JbzktnJGtp00JZQ2UqxYWsFDBujALF99H7yXcz1mvX3I1gOr0Jfm3CVg_G678rvb_Sq-FGSwpSMJkN5vcGYfg-upj02kfrus70bhijZiUr5O76kNHX_6DXwxjy1XeUqASXpdoZsomyYYgxuPZhGAp6l7ieEtc5cX2XuL7Nold_rvEg-RVxBvgExFzqVy787v0f258kcLR1</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2576738598</pqid></control><display><type>article</type><title>National Early Warning Score 2 (NEWS2) better predicts critical Coronavirus Disease 2019 (COVID-19) illness than COVID-GRAM, a multi-centre study</title><source>MEDLINE</source><source>SpringerLink Journals - AutoHoldings</source><creator>De Socio, Giuseppe Vittorio ; Gidari, Anna ; Sicari, Francesco ; Palumbo, Michele ; Francisci, Daniela</creator><creatorcontrib>De Socio, Giuseppe Vittorio ; Gidari, Anna ; Sicari, Francesco ; Palumbo, Michele ; Francisci, Daniela</creatorcontrib><description>Purpose
Clinical scores to rapidly assess the severity illness of Coronavirus Disease 2019 (COVID-19) could be considered of help for clinicians. Recently, a specific score (named COVID-GRAM) for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection, based on a nationwide Chinese cohort, has been proposed. We routinely applied the National Early Warning Score 2 (NEWS2) to predict critical COVID-19. Aim of this study is to compare NEWS2 and COVID-GRAM score.
Methods
We retrospectively analysed data of 121 COVID-19 patients admitted in two Clinics of Infectious Diseases in the Umbria region, Italy. The primary outcome was critical COVID-19 illness defined as admission to the intensive care unit, invasive ventilation, or death. Accuracy of the scores was evaluated with the area under the receiver-operating characteristic curve (AUROC). Differences between scores were confirmed used Hanley–McNeil test.
Results
The NEWS2 AUROC curve measured 0.87 (standard error, SE 0.03; 95% CI 0.80–0.93;
p
< 0.0001). The COVID-GRAM score AUROC curve measured 0.77 (SE 0.04; 95% CI 0.68–0.85;
p
< 0.0001). Hanley–McNeil test showed that NEWS2 better predicted severe COVID-19 (Z = 2.03).
Conclusions
The NEWS2 showed superior accuracy to COVID-GRAM score for prediction of critical COVID-19 illness.</description><identifier>ISSN: 0300-8126</identifier><identifier>EISSN: 1439-0973</identifier><identifier>DOI: 10.1007/s15010-021-01620-x</identifier><identifier>PMID: 33970431</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Brief Report ; Clinical deterioration ; Coronaviruses ; COVID-19 ; Critical Illness ; Early Warning Score ; Error analysis ; Family Medicine ; General Practice ; Humans ; Illnesses ; Infectious Diseases ; Internal Medicine ; Mechanical ventilation ; Medicine ; Medicine & Public Health ; Respiratory diseases ; Retrospective Studies ; SARS-CoV-2 ; Severe acute respiratory syndrome coronavirus 2 ; Standard error ; Viral diseases ; Vital signs</subject><ispartof>Infection, 2021-10, Vol.49 (5), p.1033-1038</ispartof><rights>The Author(s) 2021</rights><rights>2021. The Author(s).</rights><rights>The Author(s) 2021. 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-c474t-a8b61aa61c501d0ef10587bd2761543c335ea82f1df05b06a6937869023aa9093</citedby><cites>FETCH-LOGICAL-c474t-a8b61aa61c501d0ef10587bd2761543c335ea82f1df05b06a6937869023aa9093</cites><orcidid>0000-0002-6556-6553 ; 0000-0001-8752-8278 ; 0000-0001-8774-4843</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s15010-021-01620-x$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s15010-021-01620-x$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,27924,27925,41488,42557,51319</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33970431$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>De Socio, Giuseppe Vittorio</creatorcontrib><creatorcontrib>Gidari, Anna</creatorcontrib><creatorcontrib>Sicari, Francesco</creatorcontrib><creatorcontrib>Palumbo, Michele</creatorcontrib><creatorcontrib>Francisci, Daniela</creatorcontrib><title>National Early Warning Score 2 (NEWS2) better predicts critical Coronavirus Disease 2019 (COVID-19) illness than COVID-GRAM, a multi-centre study</title><title>Infection</title><addtitle>Infection</addtitle><addtitle>Infection</addtitle><description>Purpose
Clinical scores to rapidly assess the severity illness of Coronavirus Disease 2019 (COVID-19) could be considered of help for clinicians. Recently, a specific score (named COVID-GRAM) for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection, based on a nationwide Chinese cohort, has been proposed. We routinely applied the National Early Warning Score 2 (NEWS2) to predict critical COVID-19. Aim of this study is to compare NEWS2 and COVID-GRAM score.
Methods
We retrospectively analysed data of 121 COVID-19 patients admitted in two Clinics of Infectious Diseases in the Umbria region, Italy. The primary outcome was critical COVID-19 illness defined as admission to the intensive care unit, invasive ventilation, or death. Accuracy of the scores was evaluated with the area under the receiver-operating characteristic curve (AUROC). Differences between scores were confirmed used Hanley–McNeil test.
Results
The NEWS2 AUROC curve measured 0.87 (standard error, SE 0.03; 95% CI 0.80–0.93;
p
< 0.0001). The COVID-GRAM score AUROC curve measured 0.77 (SE 0.04; 95% CI 0.68–0.85;
p
< 0.0001). Hanley–McNeil test showed that NEWS2 better predicted severe COVID-19 (Z = 2.03).
Conclusions
The NEWS2 showed superior accuracy to COVID-GRAM score for prediction of critical COVID-19 illness.</description><subject>Brief Report</subject><subject>Clinical deterioration</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>Critical Illness</subject><subject>Early Warning Score</subject><subject>Error analysis</subject><subject>Family Medicine</subject><subject>General Practice</subject><subject>Humans</subject><subject>Illnesses</subject><subject>Infectious Diseases</subject><subject>Internal Medicine</subject><subject>Mechanical ventilation</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Respiratory diseases</subject><subject>Retrospective Studies</subject><subject>SARS-CoV-2</subject><subject>Severe acute respiratory syndrome coronavirus 2</subject><subject>Standard error</subject><subject>Viral diseases</subject><subject>Vital signs</subject><issn>0300-8126</issn><issn>1439-0973</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNp9kc1u1DAUhS0EokPhBVggS2ymEoZrO4ntDVI1HUql0koU6NJyHGfqKpMMtlN1HoM3xtOU8rNgZcn3O-f-HIReUnhLAcS7SEugQIBRArRiQG4foRktuCKgBH-MZsABiKSs2kPPYrwGgFIV4ina41wJKDidoR9nJvmhNx1emtBt8aUJve9X-MIOwWGG52fLywt2gGuXkgt4E1zjbYrYBp-8zbLFELL8xocx4iMfnYlZBlTh-eL828kRoeoA-67rXYw4XZkeT9_Hnw8_vcEGr8cueWJdn3K7mMZm-xw9aU0X3Yv7dx99_bD8svhITs-PTxaHp8QWokjEyLqixlTU5iM04FoKpRR1w0RFy4JbzktnJGtp00JZQ2UqxYWsFDBujALF99H7yXcz1mvX3I1gOr0Jfm3CVg_G678rvb_Sq-FGSwpSMJkN5vcGYfg-upj02kfrus70bhijZiUr5O76kNHX_6DXwxjy1XeUqASXpdoZsomyYYgxuPZhGAp6l7ieEtc5cX2XuL7Nold_rvEg-RVxBvgExFzqVy787v0f258kcLR1</recordid><startdate>20211001</startdate><enddate>20211001</enddate><creator>De Socio, Giuseppe Vittorio</creator><creator>Gidari, Anna</creator><creator>Sicari, Francesco</creator><creator>Palumbo, Michele</creator><creator>Francisci, Daniela</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>C6C</scope><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>7QL</scope><scope>7RV</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>NAPCQ</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-6556-6553</orcidid><orcidid>https://orcid.org/0000-0001-8752-8278</orcidid><orcidid>https://orcid.org/0000-0001-8774-4843</orcidid></search><sort><creationdate>20211001</creationdate><title>National Early Warning Score 2 (NEWS2) better predicts critical Coronavirus Disease 2019 (COVID-19) illness than COVID-GRAM, a multi-centre study</title><author>De Socio, Giuseppe Vittorio ; Gidari, Anna ; Sicari, Francesco ; Palumbo, Michele ; Francisci, Daniela</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c474t-a8b61aa61c501d0ef10587bd2761543c335ea82f1df05b06a6937869023aa9093</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Brief Report</topic><topic>Clinical deterioration</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>Critical Illness</topic><topic>Early Warning Score</topic><topic>Error analysis</topic><topic>Family Medicine</topic><topic>General Practice</topic><topic>Humans</topic><topic>Illnesses</topic><topic>Infectious Diseases</topic><topic>Internal Medicine</topic><topic>Mechanical ventilation</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Respiratory diseases</topic><topic>Retrospective Studies</topic><topic>SARS-CoV-2</topic><topic>Severe acute respiratory syndrome coronavirus 2</topic><topic>Standard error</topic><topic>Viral diseases</topic><topic>Vital signs</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>De Socio, Giuseppe Vittorio</creatorcontrib><creatorcontrib>Gidari, Anna</creatorcontrib><creatorcontrib>Sicari, Francesco</creatorcontrib><creatorcontrib>Palumbo, Michele</creatorcontrib><creatorcontrib>Francisci, Daniela</creatorcontrib><collection>Springer Nature OA Free Journals</collection><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>Bacteriology Abstracts (Microbiology B)</collection><collection>Nursing & Allied Health Database</collection><collection>Virology and AIDS Abstracts</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>Technology Research Database</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 Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</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>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Infection</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>De Socio, Giuseppe Vittorio</au><au>Gidari, Anna</au><au>Sicari, Francesco</au><au>Palumbo, Michele</au><au>Francisci, Daniela</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>National Early Warning Score 2 (NEWS2) better predicts critical Coronavirus Disease 2019 (COVID-19) illness than COVID-GRAM, a multi-centre study</atitle><jtitle>Infection</jtitle><stitle>Infection</stitle><addtitle>Infection</addtitle><date>2021-10-01</date><risdate>2021</risdate><volume>49</volume><issue>5</issue><spage>1033</spage><epage>1038</epage><pages>1033-1038</pages><issn>0300-8126</issn><eissn>1439-0973</eissn><abstract>Purpose
Clinical scores to rapidly assess the severity illness of Coronavirus Disease 2019 (COVID-19) could be considered of help for clinicians. Recently, a specific score (named COVID-GRAM) for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection, based on a nationwide Chinese cohort, has been proposed. We routinely applied the National Early Warning Score 2 (NEWS2) to predict critical COVID-19. Aim of this study is to compare NEWS2 and COVID-GRAM score.
Methods
We retrospectively analysed data of 121 COVID-19 patients admitted in two Clinics of Infectious Diseases in the Umbria region, Italy. The primary outcome was critical COVID-19 illness defined as admission to the intensive care unit, invasive ventilation, or death. Accuracy of the scores was evaluated with the area under the receiver-operating characteristic curve (AUROC). Differences between scores were confirmed used Hanley–McNeil test.
Results
The NEWS2 AUROC curve measured 0.87 (standard error, SE 0.03; 95% CI 0.80–0.93;
p
< 0.0001). The COVID-GRAM score AUROC curve measured 0.77 (SE 0.04; 95% CI 0.68–0.85;
p
< 0.0001). Hanley–McNeil test showed that NEWS2 better predicted severe COVID-19 (Z = 2.03).
Conclusions
The NEWS2 showed superior accuracy to COVID-GRAM score for prediction of critical COVID-19 illness.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>33970431</pmid><doi>10.1007/s15010-021-01620-x</doi><tpages>6</tpages><orcidid>https://orcid.org/0000-0002-6556-6553</orcidid><orcidid>https://orcid.org/0000-0001-8752-8278</orcidid><orcidid>https://orcid.org/0000-0001-8774-4843</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0300-8126 |
| ispartof | Infection, 2021-10, Vol.49 (5), p.1033-1038 |
| issn | 0300-8126 1439-0973 |
| language | eng |
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| source | MEDLINE; SpringerLink Journals - AutoHoldings |
| subjects | Brief Report Clinical deterioration Coronaviruses COVID-19 Critical Illness Early Warning Score Error analysis Family Medicine General Practice Humans Illnesses Infectious Diseases Internal Medicine Mechanical ventilation Medicine Medicine & Public Health Respiratory diseases Retrospective Studies SARS-CoV-2 Severe acute respiratory syndrome coronavirus 2 Standard error Viral diseases Vital signs |
| title | National Early Warning Score 2 (NEWS2) better predicts critical Coronavirus Disease 2019 (COVID-19) illness than COVID-GRAM, a multi-centre study |
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