Author Interviews, Heart Disease, JACC / 17.11.2020
Simple Clinical Tool for Estimation of Obstructive Coronary Artery Disease
MedicalResearch.com Interview with:
[caption id="attachment_55919" align="alignleft" width="200"]
Dr. Winther[/caption]
Simon Winther, MD, PhD
Associate professor
Department of Cardiology, Gødstrup Hospital
Herning, Denmark
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: Both European and American guidelines have traditionally recommended estimating the pre-test probability (PTP) of CAD based on the classic Diamond-Forrester approach using sex, age, and type of chest complaints. However, The European Society of Cardiology (ESC) has recently suggested a novel concept of Clinical Likelihood of CAD as a more comprehensive assessment of CAD probability but no strategy has been proposed.
I this study, we improve the estimation of the likelihood of obstructive coronary artery disease (CAD) by combining the classic pre-test probability model (Diamond–Forrester approach using sex, age, and symptoms) with clinical risk factors and coronary artery calcium score in symptomatic patients with suspected CAD. Hence, we propose a simple clinical tool for the individual estimation of clinical likelihood of CAD. The tool was developed by stepwise simplification of advanced machine learning models without significant loss of accuracy and the model were validated the both European and North American cohorts.
Dr. Winther[/caption]
Simon Winther, MD, PhD
Associate professor
Department of Cardiology, Gødstrup Hospital
Herning, Denmark
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: Both European and American guidelines have traditionally recommended estimating the pre-test probability (PTP) of CAD based on the classic Diamond-Forrester approach using sex, age, and type of chest complaints. However, The European Society of Cardiology (ESC) has recently suggested a novel concept of Clinical Likelihood of CAD as a more comprehensive assessment of CAD probability but no strategy has been proposed.
I this study, we improve the estimation of the likelihood of obstructive coronary artery disease (CAD) by combining the classic pre-test probability model (Diamond–Forrester approach using sex, age, and symptoms) with clinical risk factors and coronary artery calcium score in symptomatic patients with suspected CAD. Hence, we propose a simple clinical tool for the individual estimation of clinical likelihood of CAD. The tool was developed by stepwise simplification of advanced machine learning models without significant loss of accuracy and the model were validated the both European and North American cohorts.
