Cargando…
Derivation and External Validation of a High‐Sensitivity Cardiac Troponin–Based Proteomic Model to Predict the Presence of Obstructive Coronary Artery Disease
BACKGROUND: Current noninvasive modalities to diagnose coronary artery disease (CAD) have several limitations. We sought to derive and externally validate a hs‐cTn (high‐sensitivity cardiac troponin)–based proteomic model to diagnose obstructive coronary artery disease. METHODS AND RESULTS: In a der...
Autores principales: | , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660799/ https://www.ncbi.nlm.nih.gov/pubmed/32757795 http://dx.doi.org/10.1161/JAHA.120.017221 |
_version_ | 1783609084448079872 |
---|---|
author | McCarthy, Cian P. Neumann, Johannes T. Michelhaugh, Sam A. Ibrahim, Nasrien E. Gaggin, Hanna K. Sörensen, Nils A. Schäefer, Sarina Zeller, Tanja Magaret, Craig A. Barnes, Grady Rhyne, Rhonda F. Westermann, Dirk Januzzi, James L. |
author_facet | McCarthy, Cian P. Neumann, Johannes T. Michelhaugh, Sam A. Ibrahim, Nasrien E. Gaggin, Hanna K. Sörensen, Nils A. Schäefer, Sarina Zeller, Tanja Magaret, Craig A. Barnes, Grady Rhyne, Rhonda F. Westermann, Dirk Januzzi, James L. |
author_sort | McCarthy, Cian P. |
collection | PubMed |
description | BACKGROUND: Current noninvasive modalities to diagnose coronary artery disease (CAD) have several limitations. We sought to derive and externally validate a hs‐cTn (high‐sensitivity cardiac troponin)–based proteomic model to diagnose obstructive coronary artery disease. METHODS AND RESULTS: In a derivation cohort of 636 patients referred for coronary angiography, predictors of ≥70% coronary stenosis were identified from 6 clinical variables and 109 biomarkers. The final model was first internally validated on a separate cohort (n=275) and then externally validated on a cohort of 241 patients presenting to the ED with suspected acute myocardial infarction where ≥50% coronary stenosis was considered significant. The resulting model consisted of 3 clinical variables (male sex, age, and previous percutaneous coronary intervention) and 3 biomarkers (hs‐cTnI [high‐sensitivity cardiac troponin I], adiponectin, and kidney injury molecule‐1). In the internal validation cohort, the model yielded an area under the receiver operating characteristic curve of 0.85 for coronary stenosis ≥70% (P<0.001). At the optimal cutoff, we observed 80% sensitivity, 71% specificity, a positive predictive value of 83%, and negative predictive value of 66% for ≥70% stenosis. Partitioning the score result into 5 levels resulted in a positive predictive value of 97% and a negative predictive value of 89% at the highest and lowest levels, respectively. In the external validation cohort, the score performed similarly well. Notably, in patients who had myocardial infarction neither ruled in nor ruled out via hs‐cTnI testing (“indeterminate zone,” n=65), the score had an area under the receiver operating characteristic curve of 0.88 (P<0.001). CONCLUSIONS: A model including hs‐cTnI can predict the presence of obstructive coronary artery disease with high accuracy including in those with indeterminate hs‐cTnI concentrations. |
format | Online Article Text |
id | pubmed-7660799 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-76607992020-11-17 Derivation and External Validation of a High‐Sensitivity Cardiac Troponin–Based Proteomic Model to Predict the Presence of Obstructive Coronary Artery Disease McCarthy, Cian P. Neumann, Johannes T. Michelhaugh, Sam A. Ibrahim, Nasrien E. Gaggin, Hanna K. Sörensen, Nils A. Schäefer, Sarina Zeller, Tanja Magaret, Craig A. Barnes, Grady Rhyne, Rhonda F. Westermann, Dirk Januzzi, James L. J Am Heart Assoc Original Research BACKGROUND: Current noninvasive modalities to diagnose coronary artery disease (CAD) have several limitations. We sought to derive and externally validate a hs‐cTn (high‐sensitivity cardiac troponin)–based proteomic model to diagnose obstructive coronary artery disease. METHODS AND RESULTS: In a derivation cohort of 636 patients referred for coronary angiography, predictors of ≥70% coronary stenosis were identified from 6 clinical variables and 109 biomarkers. The final model was first internally validated on a separate cohort (n=275) and then externally validated on a cohort of 241 patients presenting to the ED with suspected acute myocardial infarction where ≥50% coronary stenosis was considered significant. The resulting model consisted of 3 clinical variables (male sex, age, and previous percutaneous coronary intervention) and 3 biomarkers (hs‐cTnI [high‐sensitivity cardiac troponin I], adiponectin, and kidney injury molecule‐1). In the internal validation cohort, the model yielded an area under the receiver operating characteristic curve of 0.85 for coronary stenosis ≥70% (P<0.001). At the optimal cutoff, we observed 80% sensitivity, 71% specificity, a positive predictive value of 83%, and negative predictive value of 66% for ≥70% stenosis. Partitioning the score result into 5 levels resulted in a positive predictive value of 97% and a negative predictive value of 89% at the highest and lowest levels, respectively. In the external validation cohort, the score performed similarly well. Notably, in patients who had myocardial infarction neither ruled in nor ruled out via hs‐cTnI testing (“indeterminate zone,” n=65), the score had an area under the receiver operating characteristic curve of 0.88 (P<0.001). CONCLUSIONS: A model including hs‐cTnI can predict the presence of obstructive coronary artery disease with high accuracy including in those with indeterminate hs‐cTnI concentrations. John Wiley and Sons Inc. 2020-08-06 /pmc/articles/PMC7660799/ /pubmed/32757795 http://dx.doi.org/10.1161/JAHA.120.017221 Text en © 2020 The Authors and Prevencio Inc. Published on behalf of the American Heart Association, Inc., by Wiley. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Original Research McCarthy, Cian P. Neumann, Johannes T. Michelhaugh, Sam A. Ibrahim, Nasrien E. Gaggin, Hanna K. Sörensen, Nils A. Schäefer, Sarina Zeller, Tanja Magaret, Craig A. Barnes, Grady Rhyne, Rhonda F. Westermann, Dirk Januzzi, James L. Derivation and External Validation of a High‐Sensitivity Cardiac Troponin–Based Proteomic Model to Predict the Presence of Obstructive Coronary Artery Disease |
title | Derivation and External Validation of a High‐Sensitivity Cardiac Troponin–Based Proteomic Model to Predict the Presence of Obstructive Coronary Artery Disease |
title_full | Derivation and External Validation of a High‐Sensitivity Cardiac Troponin–Based Proteomic Model to Predict the Presence of Obstructive Coronary Artery Disease |
title_fullStr | Derivation and External Validation of a High‐Sensitivity Cardiac Troponin–Based Proteomic Model to Predict the Presence of Obstructive Coronary Artery Disease |
title_full_unstemmed | Derivation and External Validation of a High‐Sensitivity Cardiac Troponin–Based Proteomic Model to Predict the Presence of Obstructive Coronary Artery Disease |
title_short | Derivation and External Validation of a High‐Sensitivity Cardiac Troponin–Based Proteomic Model to Predict the Presence of Obstructive Coronary Artery Disease |
title_sort | derivation and external validation of a high‐sensitivity cardiac troponin–based proteomic model to predict the presence of obstructive coronary artery disease |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660799/ https://www.ncbi.nlm.nih.gov/pubmed/32757795 http://dx.doi.org/10.1161/JAHA.120.017221 |
work_keys_str_mv | AT mccarthycianp derivationandexternalvalidationofahighsensitivitycardiactroponinbasedproteomicmodeltopredictthepresenceofobstructivecoronaryarterydisease AT neumannjohannest derivationandexternalvalidationofahighsensitivitycardiactroponinbasedproteomicmodeltopredictthepresenceofobstructivecoronaryarterydisease AT michelhaughsama derivationandexternalvalidationofahighsensitivitycardiactroponinbasedproteomicmodeltopredictthepresenceofobstructivecoronaryarterydisease AT ibrahimnasriene derivationandexternalvalidationofahighsensitivitycardiactroponinbasedproteomicmodeltopredictthepresenceofobstructivecoronaryarterydisease AT gagginhannak derivationandexternalvalidationofahighsensitivitycardiactroponinbasedproteomicmodeltopredictthepresenceofobstructivecoronaryarterydisease AT sorensennilsa derivationandexternalvalidationofahighsensitivitycardiactroponinbasedproteomicmodeltopredictthepresenceofobstructivecoronaryarterydisease AT schaefersarina derivationandexternalvalidationofahighsensitivitycardiactroponinbasedproteomicmodeltopredictthepresenceofobstructivecoronaryarterydisease AT zellertanja derivationandexternalvalidationofahighsensitivitycardiactroponinbasedproteomicmodeltopredictthepresenceofobstructivecoronaryarterydisease AT magaretcraiga derivationandexternalvalidationofahighsensitivitycardiactroponinbasedproteomicmodeltopredictthepresenceofobstructivecoronaryarterydisease AT barnesgrady derivationandexternalvalidationofahighsensitivitycardiactroponinbasedproteomicmodeltopredictthepresenceofobstructivecoronaryarterydisease AT rhynerhondaf derivationandexternalvalidationofahighsensitivitycardiactroponinbasedproteomicmodeltopredictthepresenceofobstructivecoronaryarterydisease AT westermanndirk derivationandexternalvalidationofahighsensitivitycardiactroponinbasedproteomicmodeltopredictthepresenceofobstructivecoronaryarterydisease AT januzzijamesl derivationandexternalvalidationofahighsensitivitycardiactroponinbasedproteomicmodeltopredictthepresenceofobstructivecoronaryarterydisease |