Performance of CAC-prob in predicting coronary artery calcium score: an external validation study in a high-CAC burden population
Pakpoom Wongyikul, Phichayut Phinyo, Pannipa Suwannasom, Apichat Tantraworasin, Chanikan Srikuenkaew, Pichyapa Jira, Kempiya Pornpipatsakul, Arachaporn Ngachuea, Phansa Chanthanom, Kanogphol Prayongkul, Warisara Chavalitjiraphan, Thitirat Rattananalin, Surasak Saokaew

TL;DR
This study validates a model called CAC-prob for predicting coronary artery calcium scores in a high-risk population in Thailand.
Contribution
The study confirms the robustness of CAC-prob in a different population with higher disease prevalence.
Findings
CAC-prob showed comparable diagnostic performance in predicting CAC > 0.
Model 2 demonstrated improved sensitivity for predicting CAC ≥ 100.
The model's calibration slope was acceptable, suggesting reasonable model fit.
Abstract
Although CAC screening is gaining recognition in developing countries such as Thailand, official guidelines for using the CAC score in cardiovascular risk assessment remain lacking. This study aims to externally validate CAC-prob, a recently developed prediction model that can estimate the probability of CAC > 0 and CAC ≥ 100, to confirm its robustness. This study externally validated the CAC-prob model using retrospective data from a tertiary care centre in northern Thailand. Patients who underwent CAC screening between 2019 and 2022 were included. CAC-prob consists of two models: one predicting the probability of CAC > 0 (Model 1) and another predicting the probability of CAC ≥ 100 (Model 2). Model performance was assessed in terms of discrimination (Ordinal C-index), calibration slope, and diagnostic indices for each model. A total of 329 patients were included. The patient…
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Taxonomy
TopicsCardiac Imaging and Diagnostics · Coronary Interventions and Diagnostics · Cardiac, Anesthesia and Surgical Outcomes
