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Clinical Likelihood Prediction of Hemodynamically ...
Clinical Likelihood Prediction of Hemodynamically Obstructive Coronary Artery Disease in Patients With Stable Chest Pain - JIMG October 2024
Description
BACKGROUND
: Selection for invasive angiography is recommended to be based on pretest probabilities (PTPs), and physiological measures of hemodynamical impairment by, for example, fractional flow reserve (FFR) should guide revascularization. The risk factor–weighted clinical likelihood (RF-CL) and coronary artery calcium score–weighted clinical likelihood (CACS-CL) models show superior discrimination of patients with suspected obstructive coronary artery disease (CAD), but validation against hemodynamic impairment is warranted.
OBJECTIVES
: The aim of this study was to validate the RF-CL and CACS-CL models against hemodynamically obstructive CAD.
METHODS
: Stable de novo chest pain patients (N = 4,371) underwent coronary computed tomography angiography and subsequently invasive coronary angiography with FFR measurements. Hemodynamically obstructive CAD was defined as invasive FFR ≤0.80 or high-grade stenosis by visual assessment (>90% diameter stenosis). For comparison, a guidelineendorsed basic PTP model was calculated based on age, sex, and symptom typicality. The RF-CL model additionally included the number of risk factors, and the CACS-CL model incorporated the coronary artery calcium score into the RF-CL.
RESULTS
: In total, 447 of 4,371 (10.9%) patients had hemodynamically obstructive CAD. Both the RF-CL and CACS-CL models classified more patients with a very low clinical likelihood (≤5%) of obstructive CAD compared to the basic PTP model (33.0% and 53.7% vs 12.0%; P < 0.001) with a preserved low prevalence of hemodynamically obstructive CAD (<5% for all models). Against hemodynamically obstructive CAD, calibration and discrimination of the RF-CL and CACSCL models were superior to the basic PTP model.
CONCLUSIONS
: The RF-CL and CACS-CL models are well calibrated and superior to a currently recommended basic PTP model to predict hemodynamically obstructive CAD.
Editors
Editor-in-Chief
Y.S. Chandrashekhar, MD, DM, FACC
CME Editor
Kenneth A. Ellenbogen, MD
Author
Ioannis Dimarakis, MD PhD
Important Dates
Date of Release:
October 7, 2024
Term of Approval/Date of CME/MOC Expiration:
October 6, 2025
Summary
Availability:
On-Demand
Expires on Oct 06, 2025
Cost:
FREE
Credit Offered:
1 CME Credit
1 ABIM-MOC Point
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Clinical Likelihood Prediction of Hemodynamically Obstructive Coronary Artery Disease in Patients With Stable Chest Pain - JIMG October 2024 Course List
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