| Autor: |
McCarthy CP; Division of Cardiology Massachusetts General Hospital Boston MA., Neumann JT; Department of Cardiology University Heart & Vascular Center Hamburg Germany.; German Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Kiel/Lübeck Hamburg Germany., Michelhaugh SA; Division of Cardiology Massachusetts General Hospital Boston MA., Ibrahim NE; Division of Cardiology Massachusetts General Hospital Boston MA., Gaggin HK; Division of Cardiology Massachusetts General Hospital Boston MA.; Cardiometabolic Trials Baim Institute for Clinical Research Boston MA., Sörensen NA; Department of Cardiology University Heart & Vascular Center Hamburg Germany.; German Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Kiel/Lübeck Hamburg Germany., Schäefer S; Department of Cardiology University Heart & Vascular Center Hamburg Germany., Zeller T; Department of Cardiology University Heart & Vascular Center Hamburg Germany.; German Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Kiel/Lübeck Hamburg Germany., Magaret CA; Prevencio, Inc Kirkland WA., Barnes G; Prevencio, Inc Kirkland WA., Rhyne RF; Prevencio, Inc Kirkland WA., Westermann D; Department of Cardiology University Heart & Vascular Center Hamburg Germany.; German Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Kiel/Lübeck Hamburg Germany., Januzzi JL Jr; Division of Cardiology Massachusetts General Hospital Boston MA.; Cardiometabolic Trials Baim Institute for Clinical Research Boston MA. |
| Jazyk: |
angličtina |
| Zdroj: |
Journal of the American Heart Association [J Am Heart Assoc] 2020 Aug 18; Vol. 9 (16), pp. e017221. Date of Electronic Publication: 2020 Aug 06. |
| DOI: |
10.1161/JAHA.120.017221 |
| Abstrakt: |
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. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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