Development of a risk-prediction model for Middle East respiratory syndrome coronavirus infection in dialysis patients.
Identifieur interne : 000951 ( PubMed/Checkpoint ); précédent : 000950; suivant : 000952Development of a risk-prediction model for Middle East respiratory syndrome coronavirus infection in dialysis patients.
Auteurs : Anwar E. Ahmed [Arabie saoudite] ; Abeer N. Alshukairi [Arabie saoudite] ; Hamdan Al-Jahdali [Arabie saoudite] ; Mody Alaqeel [Arabie saoudite] ; Salma S. Siddiq [Arabie saoudite] ; Hanan A. Alsaab [Arabie saoudite] ; Ezzeldin A. Sakr [Arabie saoudite] ; Hamed A. Alyahya [Arabie saoudite] ; Munzir M. Alandonisi [Arabie saoudite] ; Alaa T. Subedar [Arabie saoudite] ; Nouf M. Aloudah [Arabie saoudite] ; Salim Baharoon [Arabie saoudite] ; Majid A. Alsalamah [Arabie saoudite] ; Sameera Al Johani [Arabie saoudite] ; Mohammed G. Alghamdi [Arabie saoudite]Source :
- Hemodialysis international. International Symposium on Home Hemodialysis [ 1542-4758 ] ; 2018.
Descripteurs français
- KwdFr :
- Adolescent, Adulte, Adulte d'âge moyen, Arabie saoudite, Coronavirus du syndrome respiratoire du Moyen-Orient (pathogénicité), Dialyse rénale (), Dialyse rénale (effets indésirables), Femelle, Humains, Infections à coronavirus (anatomopathologie), Infections à coronavirus (étiologie), Jeune adulte, Mâle, Sujet âgé, Sujet âgé de 80 ans ou plus, Études rétrospectives.
- MESH :
- anatomopathologie : Infections à coronavirus.
- effets indésirables : Dialyse rénale.
- pathogénicité : Coronavirus du syndrome respiratoire du Moyen-Orient.
- étiologie : Infections à coronavirus.
- Adolescent, Adulte, Adulte d'âge moyen, Arabie saoudite, Dialyse rénale, Femelle, Humains, Jeune adulte, Mâle, Sujet âgé, Sujet âgé de 80 ans ou plus, Études rétrospectives.
- Wicri :
- geographic : Arabie saoudite.
English descriptors
- KwdEn :
- Adolescent, Adult, Aged, Aged, 80 and over, Coronavirus Infections (etiology), Coronavirus Infections (pathology), Female, Humans, Male, Middle Aged, Middle East Respiratory Syndrome Coronavirus (pathogenicity), Renal Dialysis (adverse effects), Renal Dialysis (methods), Retrospective Studies, Saudi Arabia, Young Adult.
- MESH :
- geographic : Saudi Arabia.
- adverse effects : Renal Dialysis.
- etiology : Coronavirus Infections.
- methods : Renal Dialysis.
- pathogenicity : Middle East Respiratory Syndrome Coronavirus.
- pathology : Coronavirus Infections.
- Adolescent, Adult, Aged, Aged, 80 and over, Female, Humans, Male, Middle Aged, Retrospective Studies, Young Adult.
Abstract
Introduction The Middle East respiratory syndrome coronavirus (MERS-CoV) infection can cause transmission clusters and high mortality in hemodialysis facilities. We attempted to develop a risk-prediction model to assess the early risk of MERS-CoV infection in dialysis patients. Methods This two-center retrospective cohort study included 104 dialysis patients who were suspected of MERS-CoV infection and diagnosed with rRT-PCR between September 2012 and June 2016 at King Fahd General Hospital in Jeddah and King Abdulaziz Medical City in Riyadh. We retrieved data on demographic, clinical, and radiological findings, and laboratory indices of each patient. Findings A risk-prediction model to assess early risk for MERS-CoV in dialysis patients has been developed. Independent predictors of MERS-CoV infection were identified, including chest pain (OR = 24.194; P = 0.011), leukopenia (OR = 6.080; P = 0.049), and elevated aspartate aminotransferase (AST) (OR = 11.179; P = 0.013). The adequacy of this prediction model was good (P = 0.728), with a high predictive utility (area under curve [AUC] = 76.99%; 95% CI: 67.05% to 86.38%). The prediction of the model had optimism-corrected bootstrap resampling AUC of 71.79%. The Youden index yielded a value of 0.439 or greater as the best cut-off for high risk of MERS infection. Discussion This risk-prediction model in dialysis patients appears to depend markedly on chest pain, leukopenia, and elevated AST. The model accurately predicts the high risk of MERS-CoV infection in dialysis patients. This could be clinically useful in applying timely intervention and control measures to prevent clusters of infections in dialysis facilities or other health care settings. The predictive utility of the model warrants further validation in external samples and prospective studies.
DOI: 10.1111/hdi.12661
PubMed: 29656480
Affiliations:
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<author><name sortKey="Sakr, Ezzeldin A" sort="Sakr, Ezzeldin A" uniqKey="Sakr E" first="Ezzeldin A" last="Sakr">Ezzeldin A. Sakr</name>
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<author><name sortKey="Alyahya, Hamed A" sort="Alyahya, Hamed A" uniqKey="Alyahya H" first="Hamed A" last="Alyahya">Hamed A. Alyahya</name>
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<term>Adult</term>
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<term>Coronavirus Infections (etiology)</term>
<term>Coronavirus Infections (pathology)</term>
<term>Female</term>
<term>Humans</term>
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<term>Adulte</term>
<term>Adulte d'âge moyen</term>
<term>Arabie saoudite</term>
<term>Coronavirus du syndrome respiratoire du Moyen-Orient (pathogénicité)</term>
<term>Dialyse rénale ()</term>
<term>Dialyse rénale (effets indésirables)</term>
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<keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Renal Dialysis</term>
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<keywords scheme="MESH" qualifier="pathogenicity" xml:lang="en"><term>Middle East Respiratory Syndrome Coronavirus</term>
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<term>Humans</term>
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<term>Retrospective Studies</term>
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<term>Adulte</term>
<term>Adulte d'âge moyen</term>
<term>Arabie saoudite</term>
<term>Dialyse rénale</term>
<term>Femelle</term>
<term>Humains</term>
<term>Jeune adulte</term>
<term>Mâle</term>
<term>Sujet âgé</term>
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<front><div type="abstract" xml:lang="en">Introduction The Middle East respiratory syndrome coronavirus (MERS-CoV) infection can cause transmission clusters and high mortality in hemodialysis facilities. We attempted to develop a risk-prediction model to assess the early risk of MERS-CoV infection in dialysis patients. Methods This two-center retrospective cohort study included 104 dialysis patients who were suspected of MERS-CoV infection and diagnosed with rRT-PCR between September 2012 and June 2016 at King Fahd General Hospital in Jeddah and King Abdulaziz Medical City in Riyadh. We retrieved data on demographic, clinical, and radiological findings, and laboratory indices of each patient. Findings A risk-prediction model to assess early risk for MERS-CoV in dialysis patients has been developed. Independent predictors of MERS-CoV infection were identified, including chest pain (OR = 24.194; P = 0.011), leukopenia (OR = 6.080; P = 0.049), and elevated aspartate aminotransferase (AST) (OR = 11.179; P = 0.013). The adequacy of this prediction model was good (P = 0.728), with a high predictive utility (area under curve [AUC] = 76.99%; 95% CI: 67.05% to 86.38%). The prediction of the model had optimism-corrected bootstrap resampling AUC of 71.79%. The Youden index yielded a value of 0.439 or greater as the best cut-off for high risk of MERS infection. Discussion This risk-prediction model in dialysis patients appears to depend markedly on chest pain, leukopenia, and elevated AST. The model accurately predicts the high risk of MERS-CoV infection in dialysis patients. This could be clinically useful in applying timely intervention and control measures to prevent clusters of infections in dialysis facilities or other health care settings. The predictive utility of the model warrants further validation in external samples and prospective studies.</div>
</front>
</TEI>
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<DateCompleted><Year>2019</Year>
<Month>04</Month>
<Day>18</Day>
</DateCompleted>
<DateRevised><Year>2019</Year>
<Month>04</Month>
<Day>18</Day>
</DateRevised>
<Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1542-4758</ISSN>
<JournalIssue CitedMedium="Internet"><Volume>22</Volume>
<Issue>4</Issue>
<PubDate><Year>2018</Year>
<Month>10</Month>
</PubDate>
</JournalIssue>
<Title>Hemodialysis international. International Symposium on Home Hemodialysis</Title>
<ISOAbbreviation>Hemodial Int</ISOAbbreviation>
</Journal>
<ArticleTitle>Development of a risk-prediction model for Middle East respiratory syndrome coronavirus infection in dialysis patients.</ArticleTitle>
<Pagination><MedlinePgn>474-479</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1111/hdi.12661</ELocationID>
<Abstract><AbstractText>Introduction The Middle East respiratory syndrome coronavirus (MERS-CoV) infection can cause transmission clusters and high mortality in hemodialysis facilities. We attempted to develop a risk-prediction model to assess the early risk of MERS-CoV infection in dialysis patients. Methods This two-center retrospective cohort study included 104 dialysis patients who were suspected of MERS-CoV infection and diagnosed with rRT-PCR between September 2012 and June 2016 at King Fahd General Hospital in Jeddah and King Abdulaziz Medical City in Riyadh. We retrieved data on demographic, clinical, and radiological findings, and laboratory indices of each patient. Findings A risk-prediction model to assess early risk for MERS-CoV in dialysis patients has been developed. Independent predictors of MERS-CoV infection were identified, including chest pain (OR = 24.194; P = 0.011), leukopenia (OR = 6.080; P = 0.049), and elevated aspartate aminotransferase (AST) (OR = 11.179; P = 0.013). The adequacy of this prediction model was good (P = 0.728), with a high predictive utility (area under curve [AUC] = 76.99%; 95% CI: 67.05% to 86.38%). The prediction of the model had optimism-corrected bootstrap resampling AUC of 71.79%. The Youden index yielded a value of 0.439 or greater as the best cut-off for high risk of MERS infection. Discussion This risk-prediction model in dialysis patients appears to depend markedly on chest pain, leukopenia, and elevated AST. The model accurately predicts the high risk of MERS-CoV infection in dialysis patients. This could be clinically useful in applying timely intervention and control measures to prevent clusters of infections in dialysis facilities or other health care settings. The predictive utility of the model warrants further validation in external samples and prospective studies.</AbstractText>
<CopyrightInformation>© 2018 International Society for Hemodialysis.</CopyrightInformation>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Ahmed</LastName>
<ForeName>Anwar E</ForeName>
<Initials>AE</Initials>
<Identifier Source="ORCID">0000-0001-8743-6007</Identifier>
<AffiliationInfo><Affiliation>King Saud bin Abdulaziz University for Health Sciences (KSAU-HS)/King Abdullah International Medical Research Center (KAIMRC)/King Abdulaziz Medical City (KAMC), Ministry of National Guard - Health Affairs, Riyadh, Saudi Arabia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Alshukairi</LastName>
<ForeName>Abeer N</ForeName>
<Initials>AN</Initials>
<AffiliationInfo><Affiliation>King Faisal Specialist Hospital and Research Centre, Jeddah, Saudi Arabia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Al-Jahdali</LastName>
<ForeName>Hamdan</ForeName>
<Initials>H</Initials>
<AffiliationInfo><Affiliation>King Saud bin Abdulaziz University for Health Sciences (KSAU-HS)/King Abdullah International Medical Research Center (KAIMRC)/King Abdulaziz Medical City (KAMC), Ministry of National Guard - Health Affairs, Riyadh, Saudi Arabia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Alaqeel</LastName>
<ForeName>Mody</ForeName>
<Initials>M</Initials>
<AffiliationInfo><Affiliation>King Saud bin Abdulaziz University for Health Sciences (KSAU-HS)/King Abdullah International Medical Research Center (KAIMRC)/King Abdulaziz Medical City (KAMC), Ministry of National Guard - Health Affairs, Riyadh, Saudi Arabia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Siddiq</LastName>
<ForeName>Salma S</ForeName>
<Initials>SS</Initials>
<AffiliationInfo><Affiliation>King Fahad General Hospital, Jeddah, Saudi Arabia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Alsaab</LastName>
<ForeName>Hanan A</ForeName>
<Initials>HA</Initials>
<AffiliationInfo><Affiliation>Medical Records Department, Ministry of Health, Jeddah, Saudi Arabia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Sakr</LastName>
<ForeName>Ezzeldin A</ForeName>
<Initials>EA</Initials>
<AffiliationInfo><Affiliation>King Fahad General Hospital, Jeddah, Saudi Arabia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Alyahya</LastName>
<ForeName>Hamed A</ForeName>
<Initials>HA</Initials>
<AffiliationInfo><Affiliation>King Fahad General Hospital, Jeddah, Saudi Arabia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Alandonisi</LastName>
<ForeName>Munzir M</ForeName>
<Initials>MM</Initials>
<AffiliationInfo><Affiliation>King Fahad General Hospital, Jeddah, Saudi Arabia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Subedar</LastName>
<ForeName>Alaa T</ForeName>
<Initials>AT</Initials>
<AffiliationInfo><Affiliation>King Fahad General Hospital, Jeddah, Saudi Arabia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Aloudah</LastName>
<ForeName>Nouf M</ForeName>
<Initials>NM</Initials>
<AffiliationInfo><Affiliation>King Saud University, Riyadh, Saudi Arabia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Baharoon</LastName>
<ForeName>Salim</ForeName>
<Initials>S</Initials>
<AffiliationInfo><Affiliation>King Saud bin Abdulaziz University for Health Sciences (KSAU-HS)/King Abdullah International Medical Research Center (KAIMRC)/King Abdulaziz Medical City (KAMC), Ministry of National Guard - Health Affairs, Riyadh, Saudi Arabia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Alsalamah</LastName>
<ForeName>Majid A</ForeName>
<Initials>MA</Initials>
<AffiliationInfo><Affiliation>King Saud bin Abdulaziz University for Health Sciences (KSAU-HS)/King Abdullah International Medical Research Center (KAIMRC)/King Abdulaziz Medical City (KAMC), Ministry of National Guard - Health Affairs, Riyadh, Saudi Arabia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Al Johani</LastName>
<ForeName>Sameera</ForeName>
<Initials>S</Initials>
<AffiliationInfo><Affiliation>King Saud bin Abdulaziz University for Health Sciences (KSAU-HS)/King Abdullah International Medical Research Center (KAIMRC)/King Abdulaziz Medical City (KAMC), Ministry of National Guard - Health Affairs, Riyadh, Saudi Arabia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Alghamdi</LastName>
<ForeName>Mohammed G</ForeName>
<Initials>MG</Initials>
<AffiliationInfo><Affiliation>King Fahad General Hospital, Jeddah, Saudi Arabia.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
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<ArticleDate DateType="Electronic"><Year>2018</Year>
<Month>04</Month>
<Day>14</Day>
</ArticleDate>
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<MedlineJournalInfo><Country>Canada</Country>
<MedlineTA>Hemodial Int</MedlineTA>
<NlmUniqueID>101093910</NlmUniqueID>
<ISSNLinking>1492-7535</ISSNLinking>
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<MeshHeadingList><MeshHeading><DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName>
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<MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName>
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<MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName>
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<MeshHeading><DescriptorName UI="D000369" MajorTopicYN="N">Aged, 80 and over</DescriptorName>
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<MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName>
<QualifierName UI="Q000209" MajorTopicYN="Y">etiology</QualifierName>
<QualifierName UI="Q000473" MajorTopicYN="N">pathology</QualifierName>
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<MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName>
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<MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
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<MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName>
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<MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName>
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<MeshHeading><DescriptorName UI="D065207" MajorTopicYN="N">Middle East Respiratory Syndrome Coronavirus</DescriptorName>
<QualifierName UI="Q000472" MajorTopicYN="Y">pathogenicity</QualifierName>
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<MeshHeading><DescriptorName UI="D006435" MajorTopicYN="N">Renal Dialysis</DescriptorName>
<QualifierName UI="Q000009" MajorTopicYN="Y">adverse effects</QualifierName>
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<MeshHeading><DescriptorName UI="D012189" MajorTopicYN="N">Retrospective Studies</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D012529" MajorTopicYN="N" Type="Geographic">Saudi Arabia</DescriptorName>
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<MeshHeading><DescriptorName UI="D055815" MajorTopicYN="N">Young Adult</DescriptorName>
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<KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="Y">Hemodialysis</Keyword>
<Keyword MajorTopicYN="Y">Middle East respiratory syndrome coronavirus (MERS-CoV)</Keyword>
<Keyword MajorTopicYN="Y">Saudi Arabia</Keyword>
<Keyword MajorTopicYN="Y">aminotransferase (AST)</Keyword>
<Keyword MajorTopicYN="Y">chest pain</Keyword>
<Keyword MajorTopicYN="Y">leukopenia</Keyword>
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<PubmedData><History><PubMedPubDate PubStatus="received"><Year>2017</Year>
<Month>12</Month>
<Day>07</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="revised"><Year>2018</Year>
<Month>02</Month>
<Day>22</Day>
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