To be or not to be on ECMO: can survival prediction models solve the question?
Identifieur interne : 005127 ( Ncbi/Merge ); précédent : 005126; suivant : 005128To be or not to be on ECMO: can survival prediction models solve the question?
Auteurs : Sacha Rozencwajg [France] ; John Fraser [Australie] ; Santiago Montero [France] ; Alain Combes [France] ; Matthieu Schmidt [France]Source :
- Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine [ 1441-2772 ] ; 2017.
Abstract
Over the past decade, there has been growing interest in extracorporeal membrane oxygenation (ECMO) as a rescue therapy for patients with severe acute respiratory distress syndrome (ARDS) and cardiogenic shock. Although survival of ECMO-treated patients has improved recently, the incidence of ECMO-related complications such as bleeding and nosocomial infections remains unacceptably high. In addition, patients often experience long-term physiological and psychological sequelae. Hence, identifying patients who will most likely benefit from ECMO is crucial. Because the technique exposes patients to complications and is associated with high costs and resource utilisation, prediction models have been developed to assist clinicians in identifying patients that would most likely survive after ECMO treatment. In addition, these prediction models enable comparison of risk-adjusted outcomes, both over time and between centres. Our review explores the latest predictive survival models developed for ECMO-treated severe cardiogenic shock and ARDS patients.
PubMed: 29084498
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and Adult Intensive Care Unit, Prince Charles Hospital, Brisbane, QLD, Australia.</nlm:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>Critical Care Research Group, University of Queensland; and Adult Intensive Care Unit, Prince Charles Hospital, Brisbane, QLD</wicri:regionArea><wicri:noRegion>QLD</wicri:noRegion></affiliation></author><author><name sortKey="Montero, Santiago" sort="Montero, Santiago" uniqKey="Montero S" first="Santiago" last="Montero">Santiago Montero</name><affiliation wicri:level="3"><nlm:affiliation>Medical Intensive Care Unit, Institute of Cardiometabolism and Nutrition, Hôpital de la Pitié-Salpetrière, Assistance Publique, Hôpitaux de Paris, Paris, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Medical Intensive Care Unit, Institute of Cardiometabolism and Nutrition, Hôpital de la Pitié-Salpetrière, Assistance Publique, Hôpitaux de Paris, Paris</wicri:regionArea><placeName><region type="region">Île-de-France</region><region type="old region">Île-de-France</region><settlement type="city">Paris</settlement></placeName></affiliation></author><author><name sortKey="Combes, Alain" sort="Combes, Alain" uniqKey="Combes A" first="Alain" last="Combes">Alain Combes</name><affiliation wicri:level="3"><nlm:affiliation>Medical Intensive Care Unit, Institute of Cardiometabolism and Nutrition, Hôpital de la Pitié-Salpetrière, Assistance Publique, Hôpitaux de Paris, Paris, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Medical Intensive Care Unit, Institute of Cardiometabolism and Nutrition, Hôpital de la Pitié-Salpetrière, Assistance Publique, Hôpitaux de Paris, Paris</wicri:regionArea><placeName><region type="region">Île-de-France</region><region type="old region">Île-de-France</region><settlement type="city">Paris</settlement></placeName></affiliation></author><author><name sortKey="Schmidt, Matthieu" sort="Schmidt, Matthieu" uniqKey="Schmidt M" first="Matthieu" last="Schmidt">Matthieu Schmidt</name><affiliation wicri:level="3"><nlm:affiliation>Medical Intensive Care Unit, Institute of Cardiometabolism and Nutrition, Hôpital de la Pitié-Salpetrière, Assistance Publique, Hôpitaux de Paris, Paris, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Medical Intensive Care Unit, Institute of Cardiometabolism and Nutrition, Hôpital de la Pitié-Salpetrière, Assistance Publique, Hôpitaux de Paris, Paris</wicri:regionArea><placeName><region type="region">Île-de-France</region><region type="old region">Île-de-France</region><settlement type="city">Paris</settlement></placeName></affiliation></author></analytic><series><title level="j">Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine</title><idno type="ISSN">1441-2772</idno><imprint><date when="2017" type="published">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Over the past decade, there has been growing interest in extracorporeal membrane oxygenation (ECMO) as a rescue therapy for patients with severe acute respiratory distress syndrome (ARDS) and cardiogenic shock. Although survival of ECMO-treated patients has improved recently, the incidence of ECMO-related complications such as bleeding and nosocomial infections remains unacceptably high. In addition, patients often experience long-term physiological and psychological sequelae. Hence, identifying patients who will most likely benefit from ECMO is crucial. Because the technique exposes patients to complications and is associated with high costs and resource utilisation, prediction models have been developed to assist clinicians in identifying patients that would most likely survive after ECMO treatment. In addition, these prediction models enable comparison of risk-adjusted outcomes, both over time and between centres. Our review explores the latest predictive survival models developed for ECMO-treated severe cardiogenic shock and ARDS patients.</div></front></TEI><pubmed><MedlineCitation Status="In-Data-Review" Owner="NLM"><PMID Version="1">29084498</PMID><DateCreated><Year>2017</Year><Month>10</Month><Day>31</Day></DateCreated><DateRevised><Year>2017</Year><Month>10</Month><Day>31</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">1441-2772</ISSN><JournalIssue CitedMedium="Print"><Volume>19</Volume><Issue>Suppl 1</Issue><PubDate><Year>2017</Year><Month>Oct</Month></PubDate></JournalIssue><Title>Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine</Title><ISOAbbreviation>Crit Care Resusc</ISOAbbreviation></Journal><ArticleTitle>To be or not to be on ECMO: can survival prediction models solve the question?</ArticleTitle><Pagination><MedlinePgn>21-28</MedlinePgn></Pagination><Abstract><AbstractText>Over the past decade, there has been growing interest in extracorporeal membrane oxygenation (ECMO) as a rescue therapy for patients with severe acute respiratory distress syndrome (ARDS) and cardiogenic shock. Although survival of ECMO-treated patients has improved recently, the incidence of ECMO-related complications such as bleeding and nosocomial infections remains unacceptably high. In addition, patients often experience long-term physiological and psychological sequelae. Hence, identifying patients who will most likely benefit from ECMO is crucial. Because the technique exposes patients to complications and is associated with high costs and resource utilisation, prediction models have been developed to assist clinicians in identifying patients that would most likely survive after ECMO treatment. In addition, these prediction models enable comparison of risk-adjusted outcomes, both over time and between centres. Our review explores the latest predictive survival models developed for ECMO-treated severe cardiogenic shock and ARDS patients.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Rozencwajg</LastName><ForeName>Sacha</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Medical Intensive Care Unit, Institute of Cardiometabolism and Nutrition, Hôpital de la Pitié-Salpetrière, Assistance Publique, Hôpitaux de Paris, Paris, France. matthieu.schmidt@aphp.fr.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Fraser</LastName><ForeName>John</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Critical Care Research Group, University of Queensland; and Adult Intensive Care Unit, Prince Charles Hospital, Brisbane, QLD, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Montero</LastName><ForeName>Santiago</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Medical Intensive Care Unit, Institute of Cardiometabolism and Nutrition, Hôpital de la Pitié-Salpetrière, Assistance Publique, Hôpitaux de Paris, Paris, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Combes</LastName><ForeName>Alain</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Medical Intensive Care Unit, Institute of Cardiometabolism and Nutrition, Hôpital de la Pitié-Salpetrière, Assistance Publique, Hôpitaux de Paris, Paris, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Schmidt</LastName><ForeName>Matthieu</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Medical Intensive Care Unit, Institute of Cardiometabolism and Nutrition, Hôpital de la Pitié-Salpetrière, Assistance Publique, Hôpitaux de Paris, Paris, France.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>Australia</Country><MedlineTA>Crit Care Resusc</MedlineTA><NlmUniqueID>100888170</NlmUniqueID><ISSNLinking>1441-2772</ISSNLinking></MedlineJournalInfo></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2017</Year><Month>11</Month><Day>1</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2017</Year><Month>11</Month><Day>1</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2017</Year><Month>11</Month><Day>1</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">29084498</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Australie</li><li>France</li></country><region><li>Île-de-France</li></region><settlement><li>Paris</li></settlement></list><tree><country name="France"><region name="Île-de-France"><name sortKey="Rozencwajg, Sacha" sort="Rozencwajg, Sacha" uniqKey="Rozencwajg S" first="Sacha" last="Rozencwajg">Sacha Rozencwajg</name></region><name sortKey="Combes, Alain" sort="Combes, Alain" uniqKey="Combes A" first="Alain" last="Combes">Alain Combes</name><name sortKey="Montero, Santiago" sort="Montero, Santiago" uniqKey="Montero S" first="Santiago" last="Montero">Santiago Montero</name><name sortKey="Schmidt, Matthieu" sort="Schmidt, Matthieu" uniqKey="Schmidt M" first="Matthieu" last="Schmidt">Matthieu Schmidt</name></country><country name="Australie"><noRegion><name sortKey="Fraser, John" sort="Fraser, John" uniqKey="Fraser J" first="John" last="Fraser">John Fraser</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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