A Clinical model to identify patients with high-risk coronary artery disease

Yelin Yang, Li Chen, Yeung Yam, Stephan Achenbach, Mouaz Al-Mallah, Daniel S. Berman, Matthew J. Budoff, Filippo Cademartiri, Tracy Q. Callister, Hyuk-Jae Chang, Victor Y. Cheng, Kavitha Chinnaiyan, Ricardo Cury, Augustin Delago, Allison Dunning, Gudrun Feuchtner, Martin Hadamitzky, Jörg Hausleiter, Ronald P. Karlsberg, Philipp A. KaufmannYong Jin Kim, Jonathon Leipsic, Troy Labounty, Fay Lin, Erica Maffei, Gilbert L. Raff, Leslee J. Shaw, Todd C. Villines, James K. Min, Benjamin J.W. Chow

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

Objectives This study sought to develop a clinical model that identifies patients with and without high-risk coronary artery disease (CAD). Background Although current clinical models help to estimate a patient's pre-test probability of obstructive CAD, they do not accurately identify those patients with and without high-risk coronary anatomy. Methods Retrospective analysis of a prospectively collected multinational coronary computed tomographic angiography (CTA) cohort was conducted. High-risk anatomy was defined as left main diameter stenosis ≥50%, 3-vessel disease with diameter stenosis ≥70%, or 2-vessel disease involving the proximal left anterior descending artery. Using a cohort of 27,125, patients with a history of CAD, cardiac transplantation, and congenital heart disease were excluded. The model was derived from 24,251 consecutive patients in the derivation cohort and an additional 7,333 nonoverlapping patients in the validation cohort. Results The risk score consisted of 9 variables: age, sex, diabetes, hypertension, current smoking, hyperlipidemia, family history of CAD, history of peripheral vascular disease, and chest pain symptoms. Patients were divided into 3 risk categories: low (≤7 points), intermediate (8 to 17 points) and high (≥18 points). The model was statistically robust with area under the curve of 0.76 (95% confidence interval [CI]: 0.75 to 0.78) in the derivation cohort and 0.71 (95% CI: 0.69 to 0.74) in the validation cohort. Patients who scored ≤7 points had a low negative likelihood ratio (<0.1), whereas patients who scored ≥18 points had a high specificity of 99.3% and a positive likelihood ratio (8.48). In the validation group, the prevalence of high-risk CAD was 1% in patients with ≤7 points and 16.7% in those with ≥18 points. Conclusions We propose a scoring system, based on clinical variables, that can be used to identify patients at high and low pre-test probability of having high-risk CAD. Identification of these populations may detect those who may benefit from a trial of medical therapy and those who may benefit most from an invasive strategy.

Original languageEnglish
Pages (from-to)427-434
Number of pages8
JournalJACC: Cardiovascular Imaging
Volume8
Issue number4
DOIs
Publication statusPublished - 2015 Apr 1

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Coronary Artery Disease
Anatomy
Pathologic Constriction
Confidence Intervals
Peripheral Vascular Diseases
Heart Transplantation
Hyperlipidemias
Chest Pain
Area Under Curve
Heart Diseases
Angiography
Arteries
Smoking
Hypertension

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging
  • Cardiology and Cardiovascular Medicine

Cite this

Yang, Y., Chen, L., Yam, Y., Achenbach, S., Al-Mallah, M., Berman, D. S., ... Chow, B. J. W. (2015). A Clinical model to identify patients with high-risk coronary artery disease. JACC: Cardiovascular Imaging, 8(4), 427-434. https://doi.org/10.1016/j.jcmg.2014.11.015
Yang, Yelin ; Chen, Li ; Yam, Yeung ; Achenbach, Stephan ; Al-Mallah, Mouaz ; Berman, Daniel S. ; Budoff, Matthew J. ; Cademartiri, Filippo ; Callister, Tracy Q. ; Chang, Hyuk-Jae ; Cheng, Victor Y. ; Chinnaiyan, Kavitha ; Cury, Ricardo ; Delago, Augustin ; Dunning, Allison ; Feuchtner, Gudrun ; Hadamitzky, Martin ; Hausleiter, Jörg ; Karlsberg, Ronald P. ; Kaufmann, Philipp A. ; Kim, Yong Jin ; Leipsic, Jonathon ; Labounty, Troy ; Lin, Fay ; Maffei, Erica ; Raff, Gilbert L. ; Shaw, Leslee J. ; Villines, Todd C. ; Min, James K. ; Chow, Benjamin J.W. / A Clinical model to identify patients with high-risk coronary artery disease. In: JACC: Cardiovascular Imaging. 2015 ; Vol. 8, No. 4. pp. 427-434.
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abstract = "Objectives This study sought to develop a clinical model that identifies patients with and without high-risk coronary artery disease (CAD). Background Although current clinical models help to estimate a patient's pre-test probability of obstructive CAD, they do not accurately identify those patients with and without high-risk coronary anatomy. Methods Retrospective analysis of a prospectively collected multinational coronary computed tomographic angiography (CTA) cohort was conducted. High-risk anatomy was defined as left main diameter stenosis ≥50{\%}, 3-vessel disease with diameter stenosis ≥70{\%}, or 2-vessel disease involving the proximal left anterior descending artery. Using a cohort of 27,125, patients with a history of CAD, cardiac transplantation, and congenital heart disease were excluded. The model was derived from 24,251 consecutive patients in the derivation cohort and an additional 7,333 nonoverlapping patients in the validation cohort. Results The risk score consisted of 9 variables: age, sex, diabetes, hypertension, current smoking, hyperlipidemia, family history of CAD, history of peripheral vascular disease, and chest pain symptoms. Patients were divided into 3 risk categories: low (≤7 points), intermediate (8 to 17 points) and high (≥18 points). The model was statistically robust with area under the curve of 0.76 (95{\%} confidence interval [CI]: 0.75 to 0.78) in the derivation cohort and 0.71 (95{\%} CI: 0.69 to 0.74) in the validation cohort. Patients who scored ≤7 points had a low negative likelihood ratio (<0.1), whereas patients who scored ≥18 points had a high specificity of 99.3{\%} and a positive likelihood ratio (8.48). In the validation group, the prevalence of high-risk CAD was 1{\%} in patients with ≤7 points and 16.7{\%} in those with ≥18 points. Conclusions We propose a scoring system, based on clinical variables, that can be used to identify patients at high and low pre-test probability of having high-risk CAD. Identification of these populations may detect those who may benefit from a trial of medical therapy and those who may benefit most from an invasive strategy.",
author = "Yelin Yang and Li Chen and Yeung Yam and Stephan Achenbach and Mouaz Al-Mallah and Berman, {Daniel S.} and Budoff, {Matthew J.} and Filippo Cademartiri and Callister, {Tracy Q.} and Hyuk-Jae Chang and Cheng, {Victor Y.} and Kavitha Chinnaiyan and Ricardo Cury and Augustin Delago and Allison Dunning and Gudrun Feuchtner and Martin Hadamitzky and J{\"o}rg Hausleiter and Karlsberg, {Ronald P.} and Kaufmann, {Philipp A.} and Kim, {Yong Jin} and Jonathon Leipsic and Troy Labounty and Fay Lin and Erica Maffei and Raff, {Gilbert L.} and Shaw, {Leslee J.} and Villines, {Todd C.} and Min, {James K.} and Chow, {Benjamin J.W.}",
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Yang, Y, Chen, L, Yam, Y, Achenbach, S, Al-Mallah, M, Berman, DS, Budoff, MJ, Cademartiri, F, Callister, TQ, Chang, H-J, Cheng, VY, Chinnaiyan, K, Cury, R, Delago, A, Dunning, A, Feuchtner, G, Hadamitzky, M, Hausleiter, J, Karlsberg, RP, Kaufmann, PA, Kim, YJ, Leipsic, J, Labounty, T, Lin, F, Maffei, E, Raff, GL, Shaw, LJ, Villines, TC, Min, JK & Chow, BJW 2015, 'A Clinical model to identify patients with high-risk coronary artery disease', JACC: Cardiovascular Imaging, vol. 8, no. 4, pp. 427-434. https://doi.org/10.1016/j.jcmg.2014.11.015

A Clinical model to identify patients with high-risk coronary artery disease. / Yang, Yelin; Chen, Li; Yam, Yeung; Achenbach, Stephan; Al-Mallah, Mouaz; Berman, Daniel S.; Budoff, Matthew J.; Cademartiri, Filippo; Callister, Tracy Q.; Chang, Hyuk-Jae; Cheng, Victor Y.; Chinnaiyan, Kavitha; Cury, Ricardo; Delago, Augustin; Dunning, Allison; Feuchtner, Gudrun; Hadamitzky, Martin; Hausleiter, Jörg; Karlsberg, Ronald P.; Kaufmann, Philipp A.; Kim, Yong Jin; Leipsic, Jonathon; Labounty, Troy; Lin, Fay; Maffei, Erica; Raff, Gilbert L.; Shaw, Leslee J.; Villines, Todd C.; Min, James K.; Chow, Benjamin J.W.

In: JACC: Cardiovascular Imaging, Vol. 8, No. 4, 01.04.2015, p. 427-434.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A Clinical model to identify patients with high-risk coronary artery disease

AU - Yang, Yelin

AU - Chen, Li

AU - Yam, Yeung

AU - Achenbach, Stephan

AU - Al-Mallah, Mouaz

AU - Berman, Daniel S.

AU - Budoff, Matthew J.

AU - Cademartiri, Filippo

AU - Callister, Tracy Q.

AU - Chang, Hyuk-Jae

AU - Cheng, Victor Y.

AU - Chinnaiyan, Kavitha

AU - Cury, Ricardo

AU - Delago, Augustin

AU - Dunning, Allison

AU - Feuchtner, Gudrun

AU - Hadamitzky, Martin

AU - Hausleiter, Jörg

AU - Karlsberg, Ronald P.

AU - Kaufmann, Philipp A.

AU - Kim, Yong Jin

AU - Leipsic, Jonathon

AU - Labounty, Troy

AU - Lin, Fay

AU - Maffei, Erica

AU - Raff, Gilbert L.

AU - Shaw, Leslee J.

AU - Villines, Todd C.

AU - Min, James K.

AU - Chow, Benjamin J.W.

PY - 2015/4/1

Y1 - 2015/4/1

N2 - Objectives This study sought to develop a clinical model that identifies patients with and without high-risk coronary artery disease (CAD). Background Although current clinical models help to estimate a patient's pre-test probability of obstructive CAD, they do not accurately identify those patients with and without high-risk coronary anatomy. Methods Retrospective analysis of a prospectively collected multinational coronary computed tomographic angiography (CTA) cohort was conducted. High-risk anatomy was defined as left main diameter stenosis ≥50%, 3-vessel disease with diameter stenosis ≥70%, or 2-vessel disease involving the proximal left anterior descending artery. Using a cohort of 27,125, patients with a history of CAD, cardiac transplantation, and congenital heart disease were excluded. The model was derived from 24,251 consecutive patients in the derivation cohort and an additional 7,333 nonoverlapping patients in the validation cohort. Results The risk score consisted of 9 variables: age, sex, diabetes, hypertension, current smoking, hyperlipidemia, family history of CAD, history of peripheral vascular disease, and chest pain symptoms. Patients were divided into 3 risk categories: low (≤7 points), intermediate (8 to 17 points) and high (≥18 points). The model was statistically robust with area under the curve of 0.76 (95% confidence interval [CI]: 0.75 to 0.78) in the derivation cohort and 0.71 (95% CI: 0.69 to 0.74) in the validation cohort. Patients who scored ≤7 points had a low negative likelihood ratio (<0.1), whereas patients who scored ≥18 points had a high specificity of 99.3% and a positive likelihood ratio (8.48). In the validation group, the prevalence of high-risk CAD was 1% in patients with ≤7 points and 16.7% in those with ≥18 points. Conclusions We propose a scoring system, based on clinical variables, that can be used to identify patients at high and low pre-test probability of having high-risk CAD. Identification of these populations may detect those who may benefit from a trial of medical therapy and those who may benefit most from an invasive strategy.

AB - Objectives This study sought to develop a clinical model that identifies patients with and without high-risk coronary artery disease (CAD). Background Although current clinical models help to estimate a patient's pre-test probability of obstructive CAD, they do not accurately identify those patients with and without high-risk coronary anatomy. Methods Retrospective analysis of a prospectively collected multinational coronary computed tomographic angiography (CTA) cohort was conducted. High-risk anatomy was defined as left main diameter stenosis ≥50%, 3-vessel disease with diameter stenosis ≥70%, or 2-vessel disease involving the proximal left anterior descending artery. Using a cohort of 27,125, patients with a history of CAD, cardiac transplantation, and congenital heart disease were excluded. The model was derived from 24,251 consecutive patients in the derivation cohort and an additional 7,333 nonoverlapping patients in the validation cohort. Results The risk score consisted of 9 variables: age, sex, diabetes, hypertension, current smoking, hyperlipidemia, family history of CAD, history of peripheral vascular disease, and chest pain symptoms. Patients were divided into 3 risk categories: low (≤7 points), intermediate (8 to 17 points) and high (≥18 points). The model was statistically robust with area under the curve of 0.76 (95% confidence interval [CI]: 0.75 to 0.78) in the derivation cohort and 0.71 (95% CI: 0.69 to 0.74) in the validation cohort. Patients who scored ≤7 points had a low negative likelihood ratio (<0.1), whereas patients who scored ≥18 points had a high specificity of 99.3% and a positive likelihood ratio (8.48). In the validation group, the prevalence of high-risk CAD was 1% in patients with ≤7 points and 16.7% in those with ≥18 points. Conclusions We propose a scoring system, based on clinical variables, that can be used to identify patients at high and low pre-test probability of having high-risk CAD. Identification of these populations may detect those who may benefit from a trial of medical therapy and those who may benefit most from an invasive strategy.

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