Key result
CACS-CL improves obstructive CAD discrimination over ESC-PTP, safely classifying more patients as very-low risk.
Why the study?
The RF-CL and CACS-CL models improve discrimination of patients with suspected obstructive CAD, but external validation was warranted.
Do the RF-CL and CACS-CL models improve the identification of obstructive CAD and prognosis prediction compared to the ESC-PTP model in stable chest pain patients?
Cohort (n=1,585)
Yes
Do the RF-CL and CACS-CL models improve the identification of obstructive CAD and prognosis prediction compared to the ESC-PTP model in stable chest pain patients?
Effect estimate: AUC 0.89 (95% CI 0.87-0.90)
Absolute Event Rate: 0.89% vs 0.78%
p-value: p=<0.001
The novel RF-CL and CACS-CL models safely reclassify a significantly larger proportion of stable chest pain patients to a very-low clinical likelihood of obstructive CAD compared to the 2019 ESC-PTP model.
May safely defer testing in more stable chest pain patients; extends CACS-CL validation but leaves open need for prospective outcome trials.
OBJECTIVES: The risk factor-weighted and coronary artery calcium score-weighted clinical likelihood (RF-CL and CACS-CL, respectively) models improve discrimination of patients with suspected obstructive coronary artery disease (CAD). However, external validation is warranted.Compared to the 2019 European Society of Cardiology pretest probability (ESC-PTP) model, the aims were (1) to validate the RF-CL and CACS-CL models for identification of obstructive CAD and revascularisation, and (2) to investigate prognosis by CL thresholds. METHODS: Stable de novo chest pain patients (n=1585) undergoing coronary CT angiography (CTA) were investigated. Obstructive CAD was defined as >70% diameter stenosis in a major epicardial vessel on CTA. Decision of revascularisation within 120 days was based on onsite judgement. The endpoint was non-fatal myocardial infarction or cardiovascular death. The ESC-PTP was calculated based on age, sex and symptom typicality, the RF-CL additionally included number of risk factors, and the CACS-CL incorporated CACS to the RF-CL. RESULTS: Obstructive CAD was present in 386/1585 (24.4%) patients, and 91/1585 (5.7%) patients underwent revascularisation. Both the RF-CL and CACS-CL classified more patients to very-low CL (<5%) of obstructive CAD compared with the ESC-PTP model (41.4% and 52.2% vs 19.2%, p<0.001). In very-low CL patients, obstructive CAD and revascularisation prevalences (≤6% and <1%) remained similar combined with low event risk during 5.0 years follow-up. CONCLUSION: In an external validation cohort, the novel RF-CL and CACS-CL models improve categorisation to a very-low CL group with preserved prevalences of obstructive CAD, revascularisation and favourable prognosis.
No takes yet. Share an insight, caveat, or question.
Rasmussen et al. (2023) conducted a cohort in Suspected obstructive coronary artery disease (n=1,585). CACS-CL and RF-CL models vs. 2019 ESC-PTP model was evaluated on Discrimination of obstructive CAD (ROC-AUC) (AUC 0.89, 95% CI 0.87-0.90, p=<0.001). The CACS-CL model significantly improved the discrimination of obstructive coronary artery disease compared to the ESC-PTP model (AUC 0.89 vs 0.78) and safely classified more patients to a very-low clinical likelihood group.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: