Performance of pre-test probability and risk factor-weighted clinical likelihood in predicting significant coronary artery disease on CCTA in low-risk patients with chest pain and dyspnea
L Lindgren, K Hansson, M Andersson Franko, A Ugarph Morawski, T Jernberg, T Forslund, R CerratoAbstract
Background
In 2024 risk factor-weighted clinical likelihood score (RF-CL) was introduced, to assess the risk of coronary artery disease (CAD) in patients with chest pain and/or dyspnea. This study aimed to evaluate the predictive performance of both pre-test probability (PTP) and RF-CL in a low-risk population to diagnose obstructive CAD on coronary computed tomography angiography (CCTA).
Methods
The study included 240 patients, without prior diagnosis of CAD, who underwent CCTA 2023-2024 due to chest pain and/or dyspnea at an outpatient cardiology clinic. Obstructive CAD was defined as ≥50% stenosis on CCTA. Data on coronary angiography and cardiovascular risk factors (smoking, diabetes, hypertension, and hyperlipidaemia) were collected. Logistic regression was used to assess the association of PTP and RF-CL, with and without coronary artery calcium score (CACS), with the likelihood of obstructive CAD on CCTA. Areas under the receiver operating characteristic curve (AUC) were computed to assess predictive performance.
Results
The mean age was 59.9 years, and 55.4% of the cohort were women. Obstructive CAD was detected in 13.3% of the patients on CCTA, 10.4% underwent invasive coronary angiography and 7.5% had obstructive CAD. The mean PTP and RF-CL were 16.2 and 10.0, respectively. Both the PTP and the RF-CL model demonstrated similar predictive performance for obstructive CAD (AUC 0.77 vs 0.76; p=0,793). When CACS was added to the model, the predictive accuracy improved substantially for both the PTP (AUC 0.88; p<0.001) and the RF-CL model (AUC 0.88; p<0.001).
Conclusions
In this predominantly low-risk population both PTP and RF-CL were effective predictors of obstructive CAD on CCTA, with superior performance when combined with CACS.Table 1.Baseline CharacteristicsTable 2 and Table 3. Outcome on CCTA