The Gupta perioperative risk for myocardial infarct or cardiac arrest (MICA) calculator as an intraoperative neurologic deficit predictor in carotid endarterectomy

Detalhes bibliográficos
Autor(a) principal: Pereira-Macedo, Juliana
Data de Publicação: 2022
Outros Autores: Fernandes, Beatriz, Duarte-Gamas, Luís, Pereira-Neves, António, Mourão, Joana, Khairy, Ahmed, Andrade, José Paulo, Marreiros, Ana, Rocha-Neves, João
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.1/18493
Resumo: Background: Patients undergoing carotid endarterectomy (CEA) may experiment intraoperative neurologic deficits (IND) during carotid cross-clamping. This work aimed to assess the impact of the Gupta Perioperative Myocardial Infarct or Cardiac Arrest (MICA) risk calculator in the IND. Methods: From January 2012 to April 2021, patients undergoing CEA with regional anaesthesia for carotid stenosis with IND and consecutively control operated patients without IND were selected. A regressive predictive model was created, and a receiver operating characteristic (ROC) curve was applied for comparison. A multivariable dependence analysis was conducted using a classification and regression tree (CRT) algorithm. Results: A total of 97 out of 194 included patients developed IND. Obesity showed aOR = 4.01 (95% CI: 1.66–9.67) and MICA score aOR = 1.21 (1.03–1.43). Higher contralateral stenosis showed aOR = 1.29 (1.08–1.53). The AUROC curve was 0.656. The CRT algorithm differentiated obese patients with a MICA score ≥ 8. Regarding non-obese patients, the model identified the presence of contralateral stenosis ≥ 55% with a MICA ≥ 10. Conclusion: MICA score might play an additional role in stratifying patients for IND in CEA. Obesity was determined as the best discrimination factor, followed by a score ≥ 8. A higher ipsilateral stenosis degree is suggested to have a part in avoiding procedure-related IND. Larger studies might validate the benefit of MICA score regarding the risk of IND.
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spelling The Gupta perioperative risk for myocardial infarct or cardiac arrest (MICA) calculator as an intraoperative neurologic deficit predictor in carotid endarterectomyCarotid endarterectomyCarotid stenosisMajor adverse cardiovascular eventsSurvival analysisMICA scoreAtherosclerosisPerioperative strokeBackground: Patients undergoing carotid endarterectomy (CEA) may experiment intraoperative neurologic deficits (IND) during carotid cross-clamping. This work aimed to assess the impact of the Gupta Perioperative Myocardial Infarct or Cardiac Arrest (MICA) risk calculator in the IND. Methods: From January 2012 to April 2021, patients undergoing CEA with regional anaesthesia for carotid stenosis with IND and consecutively control operated patients without IND were selected. A regressive predictive model was created, and a receiver operating characteristic (ROC) curve was applied for comparison. A multivariable dependence analysis was conducted using a classification and regression tree (CRT) algorithm. Results: A total of 97 out of 194 included patients developed IND. Obesity showed aOR = 4.01 (95% CI: 1.66–9.67) and MICA score aOR = 1.21 (1.03–1.43). Higher contralateral stenosis showed aOR = 1.29 (1.08–1.53). The AUROC curve was 0.656. The CRT algorithm differentiated obese patients with a MICA score ≥ 8. Regarding non-obese patients, the model identified the presence of contralateral stenosis ≥ 55% with a MICA ≥ 10. Conclusion: MICA score might play an additional role in stratifying patients for IND in CEA. Obesity was determined as the best discrimination factor, followed by a score ≥ 8. A higher ipsilateral stenosis degree is suggested to have a part in avoiding procedure-related IND. Larger studies might validate the benefit of MICA score regarding the risk of IND.MDPISapientiaPereira-Macedo, JulianaFernandes, BeatrizDuarte-Gamas, LuísPereira-Neves, AntónioMourão, JoanaKhairy, AhmedAndrade, José PauloMarreiros, AnaRocha-Neves, João2022-11-11T11:47:10Z2022-10-282022-11-10T14:27:50Z2022-10-28T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.1/18493engJournal of Clinical Medicine 11 (21): 6367 (2022)10.3390/jcm112163672077-0383info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-24T10:30:44Zoai:sapientia.ualg.pt:10400.1/18493Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:08:14.957584Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv The Gupta perioperative risk for myocardial infarct or cardiac arrest (MICA) calculator as an intraoperative neurologic deficit predictor in carotid endarterectomy
title The Gupta perioperative risk for myocardial infarct or cardiac arrest (MICA) calculator as an intraoperative neurologic deficit predictor in carotid endarterectomy
spellingShingle The Gupta perioperative risk for myocardial infarct or cardiac arrest (MICA) calculator as an intraoperative neurologic deficit predictor in carotid endarterectomy
Pereira-Macedo, Juliana
Carotid endarterectomy
Carotid stenosis
Major adverse cardiovascular events
Survival analysis
MICA score
Atherosclerosis
Perioperative stroke
title_short The Gupta perioperative risk for myocardial infarct or cardiac arrest (MICA) calculator as an intraoperative neurologic deficit predictor in carotid endarterectomy
title_full The Gupta perioperative risk for myocardial infarct or cardiac arrest (MICA) calculator as an intraoperative neurologic deficit predictor in carotid endarterectomy
title_fullStr The Gupta perioperative risk for myocardial infarct or cardiac arrest (MICA) calculator as an intraoperative neurologic deficit predictor in carotid endarterectomy
title_full_unstemmed The Gupta perioperative risk for myocardial infarct or cardiac arrest (MICA) calculator as an intraoperative neurologic deficit predictor in carotid endarterectomy
title_sort The Gupta perioperative risk for myocardial infarct or cardiac arrest (MICA) calculator as an intraoperative neurologic deficit predictor in carotid endarterectomy
author Pereira-Macedo, Juliana
author_facet Pereira-Macedo, Juliana
Fernandes, Beatriz
Duarte-Gamas, Luís
Pereira-Neves, António
Mourão, Joana
Khairy, Ahmed
Andrade, José Paulo
Marreiros, Ana
Rocha-Neves, João
author_role author
author2 Fernandes, Beatriz
Duarte-Gamas, Luís
Pereira-Neves, António
Mourão, Joana
Khairy, Ahmed
Andrade, José Paulo
Marreiros, Ana
Rocha-Neves, João
author2_role author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Sapientia
dc.contributor.author.fl_str_mv Pereira-Macedo, Juliana
Fernandes, Beatriz
Duarte-Gamas, Luís
Pereira-Neves, António
Mourão, Joana
Khairy, Ahmed
Andrade, José Paulo
Marreiros, Ana
Rocha-Neves, João
dc.subject.por.fl_str_mv Carotid endarterectomy
Carotid stenosis
Major adverse cardiovascular events
Survival analysis
MICA score
Atherosclerosis
Perioperative stroke
topic Carotid endarterectomy
Carotid stenosis
Major adverse cardiovascular events
Survival analysis
MICA score
Atherosclerosis
Perioperative stroke
description Background: Patients undergoing carotid endarterectomy (CEA) may experiment intraoperative neurologic deficits (IND) during carotid cross-clamping. This work aimed to assess the impact of the Gupta Perioperative Myocardial Infarct or Cardiac Arrest (MICA) risk calculator in the IND. Methods: From January 2012 to April 2021, patients undergoing CEA with regional anaesthesia for carotid stenosis with IND and consecutively control operated patients without IND were selected. A regressive predictive model was created, and a receiver operating characteristic (ROC) curve was applied for comparison. A multivariable dependence analysis was conducted using a classification and regression tree (CRT) algorithm. Results: A total of 97 out of 194 included patients developed IND. Obesity showed aOR = 4.01 (95% CI: 1.66–9.67) and MICA score aOR = 1.21 (1.03–1.43). Higher contralateral stenosis showed aOR = 1.29 (1.08–1.53). The AUROC curve was 0.656. The CRT algorithm differentiated obese patients with a MICA score ≥ 8. Regarding non-obese patients, the model identified the presence of contralateral stenosis ≥ 55% with a MICA ≥ 10. Conclusion: MICA score might play an additional role in stratifying patients for IND in CEA. Obesity was determined as the best discrimination factor, followed by a score ≥ 8. A higher ipsilateral stenosis degree is suggested to have a part in avoiding procedure-related IND. Larger studies might validate the benefit of MICA score regarding the risk of IND.
publishDate 2022
dc.date.none.fl_str_mv 2022-11-11T11:47:10Z
2022-10-28
2022-11-10T14:27:50Z
2022-10-28T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.1/18493
url http://hdl.handle.net/10400.1/18493
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Journal of Clinical Medicine 11 (21): 6367 (2022)
10.3390/jcm11216367
2077-0383
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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