External validation of novel clinical likelihood models to predict obstructive coronary artery disease and prognosis

Abstract

ObjectivesThe 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.MethodsStable 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.ResultsObstructive 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.ConclusionIn 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.