Key result
Adding epicardial fat volume to conventional risk factors and coronary calcium score improved the prediction of obstructive coronary artery disease (AUC increased from 0.856 to 0.874; P<0.0001).
Why the study?
Epicardial fat volume has shown potential to predict obstructive coronary artery disease, prompting development of a new pretest probability model incorporating traditional risk factors, coronary calcium score, and epicardial fat volume in Chinese patients.
Does the addition of epicardial fat volume to conventional risk factors and coronary calcium score improve the prediction of obstructive coronary artery disease in patients undergoing coronary CTA?
Cohort (n=5,743)
Does the addition of epicardial fat volume to conventional risk factors and coronary calcium score improve the prediction of obstructive coronary artery disease in patients undergoing coronary CTA?
Effect estimate: IDI 0.0487, NRI 0.1181
Absolute Event Rate: 0.874% vs 0.856%
p-value: p=<0.0001
The addition of epicardial fat volume to traditional risk factors and coronary calcium score significantly improves the pretest probability estimation of obstructive coronary artery disease.
May refine obstructive CAD risk stratification on CTA; hypothesis-generating and requires prospective validation.
BACKGROUND: Recent studies have demonstrated the tremendous potential of epicardial fat volume (EFV) to predict obstructive coronary artery disease. We aimed to develop a new model to estimate pretest probability of obstructive coronary artery disease using traditional risk factors with coronary calcium score and EFV and compare it with proposed models in Chinese patients who underwent coronary computed tomography angiography. METHODS: The new models were derived from 5743 consecutive patients using multivariate logistic regression and validated in an internal cohort using invasive coronary angiography as the outcome and an external cohort with clinical outcome data. Hosmer-Lemeshow goodness-of-fit test, area under the receiver operating characteristic curve, integrated discrimination improvement and net reclassification improvement were calculated to validate and compare the performance of models. RESULTS: EFV improved prediction above conventional risk factors and coronary calcium score (area under the receiver operating characteristic curve increased from 0.856 to 0.874, integrated discrimination improvement 0.0487, net reclassification improvement 0.1181, P<0.0001 for all). The final model included 5 predictors: age, sex, symptom, coronary calcium score, and EFV. Good internal validation and external validation of the new model were achieved, with positive net reclassification improvement and integrated discrimination improvement, excellent area under the receiver operating characteristic curve and favorable calibration. Further, the new model demonstrated a better prediction of clinical outcome, resulting in a more cost-effective risk stratification to optimize decision-making of downstream diagnosis and treatment. CONCLUSIONS: Addition of EFV to conventional risk factors and coronary calcium score offered a more accurate and effective estimation for pretest probability of obstructive coronary artery disease, which may help to improve initial management of stable chest pain.
No takes yet. Share an insight, caveat, or question.
Zhou et al. (2019) conducted a cohort in Obstructive coronary artery disease (n=5,743). Epicardial fat volume vs. Conventional risk factors and coronary calcium score was evaluated on Prediction of obstructive coronary artery disease (AUC) (IDI 0.0487, NRI 0.1181, p=<0.0001). Adding epicardial fat volume to conventional risk factors and coronary calcium score improved the prediction of obstructive coronary artery disease (AUC increased from 0.856 to 0.874; P<0.0001).
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: