Routine blood analysis greatly reduces the false-negative rate of RT-PCR testing for Covid-19.
Identifieur interne : 000251 ( Main/Exploration ); précédent : 000250; suivant : 000252Routine blood analysis greatly reduces the false-negative rate of RT-PCR testing for Covid-19.
Auteurs : Davide Ferrari [Italie] ; Eleonora Sabetta [Italie] ; Daniele Ceriotti [Italie] ; Andrea Motta [Italie] ; Marta Strollo [Italie] ; Giuseppe Banfi [Italie] ; Massimo Locatelli [Italie]Source :
- Acta bio-medica : Atenei Parmensis [ 2531-6745 ] ; 2020.
Descripteurs français
- KwdFr :
- ARN viral (analyse), Adulte (MeSH), Adulte d'âge moyen (MeSH), Aspartate aminotransferases (sang), Betacoronavirus (génétique), Diagnostic différentiel (MeSH), Faux négatifs (MeSH), Femelle (MeSH), Humains (MeSH), Infections à coronavirus (diagnostic), Infections à coronavirus (sang), Infections à coronavirus (épidémiologie), Italie (épidémiologie), L-Lactate dehydrogenase (sang), Marqueurs biologiques (sang), Mâle (MeSH), Pandémies (MeSH), Pneumopathie virale (diagnostic), Pneumopathie virale (sang), Pneumopathie virale (épidémiologie), Reproductibilité des résultats (MeSH), Réaction de polymérisation en chaine en temps réel (méthodes), Sujet âgé (MeSH), Sujet âgé de 80 ans ou plus (MeSH), Tests hématologiques (méthodes), Études de suivi (MeSH), Études rétrospectives (MeSH).
- MESH :
- analyse : ARN viral.
- diagnostic : Infections à coronavirus, Pneumopathie virale.
- génétique : Betacoronavirus.
- méthodes : Réaction de polymérisation en chaine en temps réel, Tests hématologiques.
- sang : Aspartate aminotransferases, Infections à coronavirus, L-Lactate dehydrogenase, Marqueurs biologiques, Pneumopathie virale.
- épidémiologie : Infections à coronavirus, Italie, Pneumopathie virale.
- Adulte, Adulte d'âge moyen, Diagnostic différentiel, Faux négatifs, Femelle, Humains, Mâle, Pandémies, Reproductibilité des résultats, Sujet âgé, Sujet âgé de 80 ans ou plus, Études de suivi, Études rétrospectives.
- Wicri :
- geographic : Italie.
English descriptors
- KwdEn :
- Adult (MeSH), Aged (MeSH), Aged, 80 and over (MeSH), Aspartate Aminotransferases (blood), Betacoronavirus (genetics), Biomarkers (blood), Coronavirus Infections (blood), Coronavirus Infections (diagnosis), Coronavirus Infections (epidemiology), Diagnosis, Differential (MeSH), False Negative Reactions (MeSH), Female (MeSH), Follow-Up Studies (MeSH), Hematologic Tests (methods), Humans (MeSH), Italy (epidemiology), L-Lactate Dehydrogenase (blood), Male (MeSH), Middle Aged (MeSH), Pandemics (MeSH), Pneumonia, Viral (blood), Pneumonia, Viral (diagnosis), Pneumonia, Viral (epidemiology), RNA, Viral (analysis), Real-Time Polymerase Chain Reaction (methods), Reproducibility of Results (MeSH), Retrospective Studies (MeSH).
- MESH :
- chemical , analysis : RNA, Viral.
- chemical , blood : Aspartate Aminotransferases, Biomarkers, L-Lactate Dehydrogenase.
- geographic , epidemiology : Italy.
- blood : Coronavirus Infections, Pneumonia, Viral.
- diagnosis : Coronavirus Infections, Pneumonia, Viral.
- epidemiology : Coronavirus Infections, Pneumonia, Viral.
- genetics : Betacoronavirus.
- methods : Hematologic Tests, Real-Time Polymerase Chain Reaction.
- Adult, Aged, Aged, 80 and over, Diagnosis, Differential, False Negative Reactions, Female, Follow-Up Studies, Humans, Male, Middle Aged, Pandemics, Reproducibility of Results, Retrospective Studies.
Abstract
BACKGROUND
The COVID-19 outbreak is now a pandemic disease reaching as much as 210 countries worldwide with more than 2.5 million infected people and nearly 200.000 deaths. Amplification of viral RNA by RT-PCR represents the gold standard for confirmation of infection, yet it showed false-negative rates as large as 15-20% which may jeopardize the effect of the restrictive measures taken by governments. We previously showed that several hematological parameters were significantly different between COVID-19 positive and negative patients. Among them aspartate aminotransferase and lactate dehydrogenase had predictive values as large as 90%. Thus a combination of RT-PCR and blood tests could reduce the false-negative rate of the genetic test.
METHODS
We retrospectively analyzed 24 patients showing multiple and inconsistent RT-PCR, test during their first hospitalization period, and compared the genetic tests results with their AST and LDH levels.
RESULTS
We showed that when considering the hematological parameters, the RT-PCR false-negative rates were reduced by almost 4-fold.
CONCLUSIONS
The study represents a preliminary work aiming at the development of strategies that, by combining RT-PCR tests with routine blood tests, will lower or even abolish the rate of RT-PCR false-negative results and thus will identify, with high accuracy, patients infected by COVID-19.
DOI: 10.23750/abm.v91i3.9843
PubMed: 32921701
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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wicri:rule="url">Italie</country></affiliation></author><author><name sortKey="Locatelli, Massimo" sort="Locatelli, Massimo" uniqKey="Locatelli M" first="Massimo" last="Locatelli">Massimo Locatelli</name><affiliation wicri:level="1"><nlm:affiliation>San Raffaele Hospital. locatelli.massimo@hsr.it.</nlm:affiliation><country wicri:rule="url">Italie</country></affiliation></author></analytic><series><title level="j">Acta bio-medica : Atenei Parmensis</title><idno type="eISSN">2531-6745</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adult (MeSH)</term><term>Aged (MeSH)</term><term>Aged, 80 and over (MeSH)</term><term>Aspartate Aminotransferases (blood)</term><term>Betacoronavirus (genetics)</term><term>Biomarkers (blood)</term><term>Coronavirus Infections (blood)</term><term>Coronavirus Infections (diagnosis)</term><term>Coronavirus Infections (epidemiology)</term><term>Diagnosis, Differential (MeSH)</term><term>False Negative Reactions (MeSH)</term><term>Female (MeSH)</term><term>Follow-Up Studies (MeSH)</term><term>Hematologic Tests (methods)</term><term>Humans (MeSH)</term><term>Italy (epidemiology)</term><term>L-Lactate Dehydrogenase (blood)</term><term>Male (MeSH)</term><term>Middle Aged (MeSH)</term><term>Pandemics (MeSH)</term><term>Pneumonia, Viral (blood)</term><term>Pneumonia, Viral (diagnosis)</term><term>Pneumonia, Viral (epidemiology)</term><term>RNA, Viral (analysis)</term><term>Real-Time Polymerase Chain Reaction (methods)</term><term>Reproducibility of Results (MeSH)</term><term>Retrospective Studies (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>ARN viral (analyse)</term><term>Adulte (MeSH)</term><term>Adulte d'âge moyen (MeSH)</term><term>Aspartate aminotransferases (sang)</term><term>Betacoronavirus (génétique)</term><term>Diagnostic différentiel (MeSH)</term><term>Faux négatifs (MeSH)</term><term>Femelle (MeSH)</term><term>Humains (MeSH)</term><term>Infections à coronavirus (diagnostic)</term><term>Infections à coronavirus (sang)</term><term>Infections à coronavirus (épidémiologie)</term><term>Italie (épidémiologie)</term><term>L-Lactate dehydrogenase (sang)</term><term>Marqueurs biologiques (sang)</term><term>Mâle (MeSH)</term><term>Pandémies (MeSH)</term><term>Pneumopathie virale (diagnostic)</term><term>Pneumopathie virale (sang)</term><term>Pneumopathie virale (épidémiologie)</term><term>Reproductibilité des résultats (MeSH)</term><term>Réaction de polymérisation en chaine en temps réel (méthodes)</term><term>Sujet âgé (MeSH)</term><term>Sujet âgé de 80 ans ou plus (MeSH)</term><term>Tests hématologiques (méthodes)</term><term>Études de suivi (MeSH)</term><term>Études rétrospectives (MeSH)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="analysis" xml:lang="en"><term>RNA, Viral</term></keywords><keywords scheme="MESH" type="chemical" qualifier="blood" xml:lang="en"><term>Aspartate Aminotransferases</term><term>Biomarkers</term><term>L-Lactate Dehydrogenase</term></keywords><keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>Italy</term></keywords><keywords scheme="MESH" qualifier="analyse" xml:lang="fr"><term>ARN viral</term></keywords><keywords scheme="MESH" qualifier="blood" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="diagnosis" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="diagnostic" xml:lang="fr"><term>Infections à coronavirus</term><term>Pneumopathie virale</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Betacoronavirus</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Betacoronavirus</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Hematologic Tests</term><term>Real-Time Polymerase Chain Reaction</term></keywords><keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Réaction de polymérisation en chaine en temps réel</term><term>Tests hématologiques</term></keywords><keywords scheme="MESH" qualifier="sang" xml:lang="fr"><term>Aspartate aminotransferases</term><term>Infections à coronavirus</term><term>L-Lactate dehydrogenase</term><term>Marqueurs biologiques</term><term>Pneumopathie virale</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Infections à coronavirus</term><term>Italie</term><term>Pneumopathie virale</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adult</term><term>Aged</term><term>Aged, 80 and over</term><term>Diagnosis, Differential</term><term>False Negative Reactions</term><term>Female</term><term>Follow-Up Studies</term><term>Humans</term><term>Male</term><term>Middle Aged</term><term>Pandemics</term><term>Reproducibility of Results</term><term>Retrospective Studies</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Adulte</term><term>Adulte d'âge moyen</term><term>Diagnostic différentiel</term><term>Faux négatifs</term><term>Femelle</term><term>Humains</term><term>Mâle</term><term>Pandémies</term><term>Reproductibilité des résultats</term><term>Sujet âgé</term><term>Sujet âgé de 80 ans ou plus</term><term>Études de suivi</term><term>Études rétrospectives</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>Italie</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>BACKGROUND</b></p><p>The COVID-19 outbreak is now a pandemic disease reaching as much as 210 countries worldwide with more than 2.5 million infected people and nearly 200.000 deaths. Amplification of viral RNA by RT-PCR represents the gold standard for confirmation of infection, yet it showed false-negative rates as large as 15-20% which may jeopardize the effect of the restrictive measures taken by governments. We previously showed that several hematological parameters were significantly different between COVID-19 positive and negative patients. Among them aspartate aminotransferase and lactate dehydrogenase had predictive values as large as 90%. Thus a combination of RT-PCR and blood tests could reduce the false-negative rate of the genetic test.</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>We retrospectively analyzed 24 patients showing multiple and inconsistent RT-PCR, test during their first hospitalization period, and compared the genetic tests results with their AST and LDH levels.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>We showed that when considering the hematological parameters, the RT-PCR false-negative rates were reduced by almost 4-fold.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b></p><p>The study represents a preliminary work aiming at the development of strategies that, by combining RT-PCR tests with routine blood tests, will lower or even abolish the rate of RT-PCR false-negative results and thus will identify, with high accuracy, patients infected by COVID-19.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32921701</PMID><DateCompleted><Year>2020</Year><Month>09</Month><Day>22</Day></DateCompleted><DateRevised><Year>2020</Year><Month>09</Month><Day>22</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">2531-6745</ISSN><JournalIssue CitedMedium="Internet"><Volume>91</Volume><Issue>3</Issue><PubDate><Year>2020</Year><Month>09</Month><Day>07</Day></PubDate></JournalIssue><Title>Acta bio-medica : Atenei Parmensis</Title><ISOAbbreviation>Acta Biomed</ISOAbbreviation></Journal><ArticleTitle>Routine blood analysis greatly reduces the false-negative rate of RT-PCR testing for Covid-19.</ArticleTitle><Pagination><MedlinePgn>e2020003</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.23750/abm.v91i3.9843</ELocationID><Abstract><AbstractText Label="BACKGROUND">The COVID-19 outbreak is now a pandemic disease reaching as much as 210 countries worldwide with more than 2.5 million infected people and nearly 200.000 deaths. Amplification of viral RNA by RT-PCR represents the gold standard for confirmation of infection, yet it showed false-negative rates as large as 15-20% which may jeopardize the effect of the restrictive measures taken by governments. We previously showed that several hematological parameters were significantly different between COVID-19 positive and negative patients. Among them aspartate aminotransferase and lactate dehydrogenase had predictive values as large as 90%. Thus a combination of RT-PCR and blood tests could reduce the false-negative rate of the genetic test.</AbstractText><AbstractText Label="METHODS">We retrospectively analyzed 24 patients showing multiple and inconsistent RT-PCR, test during their first hospitalization period, and compared the genetic tests results with their AST and LDH levels.</AbstractText><AbstractText Label="RESULTS">We showed that when considering the hematological parameters, the RT-PCR false-negative rates were reduced by almost 4-fold.</AbstractText><AbstractText Label="CONCLUSIONS">The study represents a preliminary work aiming at the development of strategies that, by combining RT-PCR tests with routine blood tests, will lower or even abolish the rate of RT-PCR false-negative results and thus will identify, with high accuracy, patients infected by COVID-19.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Ferrari</LastName><ForeName>Davide</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>SCVSA Department, University of Parma, Parma, Italy; 2 Laboratory Medicine Service, San Raffaele Hospital, Milano, Italy; 3 Vita-Salute University, San Raffaele, Milano, Italy; IRCCS Istituto Ortopedico Galeazzi, Milano, Italy. davide.ferrari@unipr.it.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Sabetta</LastName><ForeName>Eleonora</ForeName><Initials>E</Initials><AffiliationInfo><Affiliation>San Raffaele Hospital. sabetta.eleonore@hsr.it.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ceriotti</LastName><ForeName>Daniele</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>San Raffaele Hospital. Ceriotti.Daniele@hsr.it.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Motta</LastName><ForeName>Andrea</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>San Raffaele Hospital. motta.andrea@hsr.it.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Strollo</LastName><ForeName>Marta</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>San Raffaele Hospital. strollo.marta@hsr.it.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Banfi</LastName><ForeName>Giuseppe</ForeName><Initials>G</Initials><AffiliationInfo><Affiliation>San Raffaele Hospital. banfi.giuseppe@hsr.it.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Locatelli</LastName><ForeName>Massimo</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>San Raffaele Hospital. locatelli.massimo@hsr.it.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D064888">Observational Study</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>09</Month><Day>07</Day></ArticleDate></Article><MedlineJournalInfo><Country>Italy</Country><MedlineTA>Acta Biomed</MedlineTA><NlmUniqueID>101295064</NlmUniqueID><ISSNLinking>0392-4203</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D015415">Biomarkers</NameOfSubstance></Chemical><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D012367">RNA, Viral</NameOfSubstance></Chemical><Chemical><RegistryNumber>EC 1.1.1.27</RegistryNumber><NameOfSubstance UI="D007770">L-Lactate Dehydrogenase</NameOfSubstance></Chemical><Chemical><RegistryNumber>EC 2.6.1.1</RegistryNumber><NameOfSubstance UI="D001219">Aspartate Aminotransferases</NameOfSubstance></Chemical></ChemicalList><SupplMeshList><SupplMeshName Type="Disease" UI="C000657245">COVID-19</SupplMeshName><SupplMeshName Type="Organism" UI="C000656484">severe acute respiratory syndrome coronavirus 2</SupplMeshName></SupplMeshList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000369" MajorTopicYN="N">Aged, 80 and over</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D001219" MajorTopicYN="N">Aspartate Aminotransferases</DescriptorName><QualifierName UI="Q000097" MajorTopicYN="N">blood</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D000073640" MajorTopicYN="N">Betacoronavirus</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="Y">genetics</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D015415" MajorTopicYN="N">Biomarkers</DescriptorName><QualifierName UI="Q000097" MajorTopicYN="N">blood</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName><QualifierName UI="Q000097" MajorTopicYN="N">blood</QualifierName><QualifierName UI="Q000175" MajorTopicYN="Y">diagnosis</QualifierName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D003937" MajorTopicYN="N">Diagnosis, Differential</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005188" MajorTopicYN="N">False Negative Reactions</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005500" MajorTopicYN="N">Follow-Up Studies</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006403" MajorTopicYN="N">Hematologic Tests</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007558" MajorTopicYN="N" Type="Geographic">Italy</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D007770" MajorTopicYN="N">L-Lactate Dehydrogenase</DescriptorName><QualifierName UI="Q000097" MajorTopicYN="N">blood</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058873" MajorTopicYN="Y">Pandemics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011024" MajorTopicYN="N">Pneumonia, Viral</DescriptorName><QualifierName UI="Q000097" MajorTopicYN="N">blood</QualifierName><QualifierName UI="Q000175" MajorTopicYN="Y">diagnosis</QualifierName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D012367" MajorTopicYN="N">RNA, Viral</DescriptorName><QualifierName UI="Q000032" MajorTopicYN="Y">analysis</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D060888" MajorTopicYN="N">Real-Time Polymerase Chain Reaction</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D015203" MajorTopicYN="N">Reproducibility of Results</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012189" MajorTopicYN="N">Retrospective Studies</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>05</Month><Day>16</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>05</Month><Day>18</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>9</Month><Day>14</Day><Hour>5</Hour><Minute>47</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>9</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>9</Month><Day>23</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32921701</ArticleId><ArticleId IdType="doi">10.23750/abm.v91i3.9843</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Italie</li></country></list><tree><country name="Italie"><noRegion><name sortKey="Ferrari, Davide" sort="Ferrari, Davide" uniqKey="Ferrari D" first="Davide" last="Ferrari">Davide Ferrari</name></noRegion><name sortKey="Banfi, Giuseppe" sort="Banfi, Giuseppe" uniqKey="Banfi G" first="Giuseppe" last="Banfi">Giuseppe Banfi</name><name sortKey="Ceriotti, Daniele" sort="Ceriotti, Daniele" uniqKey="Ceriotti D" first="Daniele" last="Ceriotti">Daniele Ceriotti</name><name sortKey="Locatelli, Massimo" sort="Locatelli, Massimo" uniqKey="Locatelli M" first="Massimo" last="Locatelli">Massimo Locatelli</name><name sortKey="Motta, Andrea" sort="Motta, Andrea" uniqKey="Motta A" first="Andrea" last="Motta">Andrea Motta</name><name sortKey="Sabetta, Eleonora" sort="Sabetta, Eleonora" uniqKey="Sabetta E" first="Eleonora" last="Sabetta">Eleonora Sabetta</name><name sortKey="Strollo, Marta" sort="Strollo, Marta" uniqKey="Strollo M" first="Marta" last="Strollo">Marta Strollo</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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{{Explor lien
|wiki= Sante
|area= CovidSeniorV1
|flux= Main
|étape= Exploration
|type= RBID
|clé= pubmed:32921701
|texte= Routine blood analysis greatly reduces the false-negative rate of RT-PCR testing for Covid-19.
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Main/Exploration/RBID.i -Sk "pubmed:32921701" \
| HfdSelect -Kh $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd \
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