A Multivariate Model for Prediction of Obstructive Coronary Disease in Patients with Acute Chest Pain: Development and Validation

Detalhes bibliográficos
Autor(a) principal: Correia,Luis Cláudio Lemos
Data de Publicação: 2017
Outros Autores: Cerqueira,Maurício, Carvalhal,Manuela, Ferreira,Felipe, Garcia,Guilherme, Silva,André Barcelos da, Sá,Nicole de, Lopes,Fernanda, Barcelos,Ana Clara, Noya-Rabelo,Márcia
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Arquivos Brasileiros de Cardiologia (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0066-782X2017000400304
Resumo: Abstract Background: Currently, there is no validated multivariate model to predict probability of obstructive coronary disease in patients with acute chest pain. Objective: To develop and validate a multivariate model to predict coronary artery disease (CAD) based on variables assessed at admission to the coronary care unit (CCU) due to acute chest pain. Methods: A total of 470 patients were studied, 370 utilized as the derivation sample and the subsequent 100 patients as the validation sample. As the reference standard, angiography was required to rule in CAD (stenosis ≥ 70%), while either angiography or a negative noninvasive test could be used to rule it out. As predictors, 13 baseline variables related to medical history, 14 characteristics of chest discomfort, and eight variables from physical examination or laboratory tests were tested. Results: The prevalence of CAD was 48%. By logistic regression, six variables remained independent predictors of CAD: age, male gender, relief with nitrate, signs of heart failure, positive electrocardiogram, and troponin. The area under the curve (AUC) of this final model was 0.80 (95% confidence interval [95%CI] = 0.75 - 0.84) in the derivation sample and 0.86 (95%CI = 0.79 - 0.93) in the validation sample. Hosmer-Lemeshow's test indicated good calibration in both samples (p = 0.98 and p = 0.23, respectively). Compared with a basic model containing electrocardiogram and troponin, the full model provided an AUC increment of 0.07 in both derivation (p = 0.0002) and validation (p = 0.039) samples. Integrated discrimination improvement was 0.09 in both derivation (p < 0.001) and validation (p < 0.0015) samples. Conclusion: A multivariate model was derived and validated as an accurate tool for estimating the pretest probability of CAD in patients with acute chest pain.
id SBC-1_8ced145f485c43472c8b7a864be5c0d9
oai_identifier_str oai:scielo:S0066-782X2017000400304
network_acronym_str SBC-1
network_name_str Arquivos Brasileiros de Cardiologia (Online)
repository_id_str
spelling A Multivariate Model for Prediction of Obstructive Coronary Disease in Patients with Acute Chest Pain: Development and ValidationCoronaryArtery DiseaseMethodsChest PainModels StatisticalCoronary AngiographyTroponinElectrocardiographyAbstract Background: Currently, there is no validated multivariate model to predict probability of obstructive coronary disease in patients with acute chest pain. Objective: To develop and validate a multivariate model to predict coronary artery disease (CAD) based on variables assessed at admission to the coronary care unit (CCU) due to acute chest pain. Methods: A total of 470 patients were studied, 370 utilized as the derivation sample and the subsequent 100 patients as the validation sample. As the reference standard, angiography was required to rule in CAD (stenosis ≥ 70%), while either angiography or a negative noninvasive test could be used to rule it out. As predictors, 13 baseline variables related to medical history, 14 characteristics of chest discomfort, and eight variables from physical examination or laboratory tests were tested. Results: The prevalence of CAD was 48%. By logistic regression, six variables remained independent predictors of CAD: age, male gender, relief with nitrate, signs of heart failure, positive electrocardiogram, and troponin. The area under the curve (AUC) of this final model was 0.80 (95% confidence interval [95%CI] = 0.75 - 0.84) in the derivation sample and 0.86 (95%CI = 0.79 - 0.93) in the validation sample. Hosmer-Lemeshow's test indicated good calibration in both samples (p = 0.98 and p = 0.23, respectively). Compared with a basic model containing electrocardiogram and troponin, the full model provided an AUC increment of 0.07 in both derivation (p = 0.0002) and validation (p = 0.039) samples. Integrated discrimination improvement was 0.09 in both derivation (p < 0.001) and validation (p < 0.0015) samples. Conclusion: A multivariate model was derived and validated as an accurate tool for estimating the pretest probability of CAD in patients with acute chest pain.Sociedade Brasileira de Cardiologia - SBC2017-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0066-782X2017000400304Arquivos Brasileiros de Cardiologia v.108 n.4 2017reponame:Arquivos Brasileiros de Cardiologia (Online)instname:Sociedade Brasileira de Cardiologia (SBC)instacron:SBC10.5935/abc.20170037info:eu-repo/semantics/openAccessCorreia,Luis Cláudio LemosCerqueira,MaurícioCarvalhal,ManuelaFerreira,FelipeGarcia,GuilhermeSilva,André Barcelos daSá,Nicole deLopes,FernandaBarcelos,Ana ClaraNoya-Rabelo,Márciaeng2017-05-12T00:00:00Zoai:scielo:S0066-782X2017000400304Revistahttp://www.arquivosonline.com.br/https://old.scielo.br/oai/scielo-oai.php||arquivos@cardiol.br1678-41700066-782Xopendoar:2017-05-12T00:00Arquivos Brasileiros de Cardiologia (Online) - Sociedade Brasileira de Cardiologia (SBC)false
dc.title.none.fl_str_mv A Multivariate Model for Prediction of Obstructive Coronary Disease in Patients with Acute Chest Pain: Development and Validation
title A Multivariate Model for Prediction of Obstructive Coronary Disease in Patients with Acute Chest Pain: Development and Validation
spellingShingle A Multivariate Model for Prediction of Obstructive Coronary Disease in Patients with Acute Chest Pain: Development and Validation
Correia,Luis Cláudio Lemos
CoronaryArtery Disease
Methods
Chest Pain
Models Statistical
Coronary Angiography
Troponin
Electrocardiography
title_short A Multivariate Model for Prediction of Obstructive Coronary Disease in Patients with Acute Chest Pain: Development and Validation
title_full A Multivariate Model for Prediction of Obstructive Coronary Disease in Patients with Acute Chest Pain: Development and Validation
title_fullStr A Multivariate Model for Prediction of Obstructive Coronary Disease in Patients with Acute Chest Pain: Development and Validation
title_full_unstemmed A Multivariate Model for Prediction of Obstructive Coronary Disease in Patients with Acute Chest Pain: Development and Validation
title_sort A Multivariate Model for Prediction of Obstructive Coronary Disease in Patients with Acute Chest Pain: Development and Validation
author Correia,Luis Cláudio Lemos
author_facet Correia,Luis Cláudio Lemos
Cerqueira,Maurício
Carvalhal,Manuela
Ferreira,Felipe
Garcia,Guilherme
Silva,André Barcelos da
Sá,Nicole de
Lopes,Fernanda
Barcelos,Ana Clara
Noya-Rabelo,Márcia
author_role author
author2 Cerqueira,Maurício
Carvalhal,Manuela
Ferreira,Felipe
Garcia,Guilherme
Silva,André Barcelos da
Sá,Nicole de
Lopes,Fernanda
Barcelos,Ana Clara
Noya-Rabelo,Márcia
author2_role author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Correia,Luis Cláudio Lemos
Cerqueira,Maurício
Carvalhal,Manuela
Ferreira,Felipe
Garcia,Guilherme
Silva,André Barcelos da
Sá,Nicole de
Lopes,Fernanda
Barcelos,Ana Clara
Noya-Rabelo,Márcia
dc.subject.por.fl_str_mv CoronaryArtery Disease
Methods
Chest Pain
Models Statistical
Coronary Angiography
Troponin
Electrocardiography
topic CoronaryArtery Disease
Methods
Chest Pain
Models Statistical
Coronary Angiography
Troponin
Electrocardiography
description Abstract Background: Currently, there is no validated multivariate model to predict probability of obstructive coronary disease in patients with acute chest pain. Objective: To develop and validate a multivariate model to predict coronary artery disease (CAD) based on variables assessed at admission to the coronary care unit (CCU) due to acute chest pain. Methods: A total of 470 patients were studied, 370 utilized as the derivation sample and the subsequent 100 patients as the validation sample. As the reference standard, angiography was required to rule in CAD (stenosis ≥ 70%), while either angiography or a negative noninvasive test could be used to rule it out. As predictors, 13 baseline variables related to medical history, 14 characteristics of chest discomfort, and eight variables from physical examination or laboratory tests were tested. Results: The prevalence of CAD was 48%. By logistic regression, six variables remained independent predictors of CAD: age, male gender, relief with nitrate, signs of heart failure, positive electrocardiogram, and troponin. The area under the curve (AUC) of this final model was 0.80 (95% confidence interval [95%CI] = 0.75 - 0.84) in the derivation sample and 0.86 (95%CI = 0.79 - 0.93) in the validation sample. Hosmer-Lemeshow's test indicated good calibration in both samples (p = 0.98 and p = 0.23, respectively). Compared with a basic model containing electrocardiogram and troponin, the full model provided an AUC increment of 0.07 in both derivation (p = 0.0002) and validation (p = 0.039) samples. Integrated discrimination improvement was 0.09 in both derivation (p < 0.001) and validation (p < 0.0015) samples. Conclusion: A multivariate model was derived and validated as an accurate tool for estimating the pretest probability of CAD in patients with acute chest pain.
publishDate 2017
dc.date.none.fl_str_mv 2017-04-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0066-782X2017000400304
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0066-782X2017000400304
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.5935/abc.20170037
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Cardiologia - SBC
publisher.none.fl_str_mv Sociedade Brasileira de Cardiologia - SBC
dc.source.none.fl_str_mv Arquivos Brasileiros de Cardiologia v.108 n.4 2017
reponame:Arquivos Brasileiros de Cardiologia (Online)
instname:Sociedade Brasileira de Cardiologia (SBC)
instacron:SBC
instname_str Sociedade Brasileira de Cardiologia (SBC)
instacron_str SBC
institution SBC
reponame_str Arquivos Brasileiros de Cardiologia (Online)
collection Arquivos Brasileiros de Cardiologia (Online)
repository.name.fl_str_mv Arquivos Brasileiros de Cardiologia (Online) - Sociedade Brasileira de Cardiologia (SBC)
repository.mail.fl_str_mv ||arquivos@cardiol.br
_version_ 1752126567211859968