Inflammatory risk and cardiovascular events in patients without obstructive coronary artery disease: the ORFAN multicentre, longitudinal cohort study

Abstract

Background: Coronary computed tomography angiography (CCTA) is the first line investigation for chest pain, and it is used to guide revascularisation. However, the widespread adoption of CCTA has revealed a large group of individuals without obstructive coronary artery disease (CAD), with unclear prognosis and management. Measurement of coronary inflammation from CCTA using the perivascular fat attenuation index (FAI) Score could enable cardiovascular risk prediction and guide the management of individuals without obstructive CAD. The Oxford Risk Factors And Non-invasive imaging (ORFAN) study aimed to evaluate the risk profile and event rates among patients undergoing CCTA as part of routine clinical care in the UK National Health Service (NHS); to test the hypothesis that coronary arterial inflammation drives cardiac mortality or major adverse cardiac events (MACE) in patients with or without CAD; and to externally validate the performance of the previously trained artificial intelligence (AI)-Risk prognostic algorithm and the related AI-Risk classification system in a UK population.

Methods: This multicentre, longitudinal cohort study included 40 091 consecutive patients undergoing clinically indicated CCTA in eight UK hospitals, who were followed up for MACE (ie, myocardial infarction, new onset heart failure, or cardiac death) for a median of 2·7 years (IQR 1·4-5·3). The prognostic value of FAI Score in the presence and absence of obstructive CAD was evaluated in 3393 consecutive patients from the two hospitals with the longest follow-up (7·7 years [6·4-9·1]). An AI-enhanced cardiac risk prediction algorithm, which integrates FAI Score, coronary plaque metrics, and clinical risk factors, was then evaluated in this population.

Findings: In the 2·7 year median follow-up period, patients without obstructive CAD (32 533 [81·1%] of 40 091) accounted for 2857 (66·3%) of the 4307 total MACE and 1118 (63·7%) of the 1754 total cardiac deaths in the whole of Cohort A. Increased FAI Score in all the three coronary arteries had an additive impact on the risk for cardiac mortality (hazard ratio [HR] 29·8 [95% CI 13·9-63·9], p<0·001) or MACE (12·6 [8·5-18·6], p<0·001) comparing three vessels with an FAI Score in the top versus bottom quartile for each artery. FAI Score in any coronary artery predicted cardiac mortality and MACE independently from cardiovascular risk factors and the presence or extent of CAD. The AI-Risk classification was positively associated with cardiac mortality (6·75 [5·17-8·82], p<0·001, for very high risk vs low or medium risk) and MACE (4·68 [3·93-5·57], p<0·001 for very high risk vs low or medium risk). Finally, the AI-Risk model was well calibrated against true events.

Interpretation: The FAI Score captures inflammatory risk beyond the current clinical risk stratification and CCTA interpretation, particularly among patients without obstructive CAD. The AI-Risk integrates this information in a prognostic algorithm, which could be used as an alternative to traditional risk factor-based risk calculators.

Funding: British Heart Foundation, NHS-AI award, Innovate UK, National Institute for Health and Care Research, and the Oxford Biomedical Research Centre.

Figure 1.. Study design and data flow.

HES, Hospital episodes statistics; NHS, National Health Service; NICOR, National Institute for Cardiovascular Outcomes Research; ONS, Office of National Statistics.

Figure 2:. Cardiovascular risk prediction in the presence or absence of obstructive CAD

Forrest plot showing hazard ratios for individual clinical outcomes and MACE (cardiac mortality, myocardial infarction, new heart failure) over a period of 10 years after the CCTA in 40,091 Cohort A patients. CAD=coronary artery disease. HR adjusted for age, sex, cardiovascular risk factors (diabetes, hypertension, hyperlipidaemia, smoking status), medications (betablockers, calcium channel blockers, nitrates, statins, angiotensin-converting enzyme inhibitors, antiplatelets and direct oral anticoagulants), past myocardial infarction and history of revascularisation (PCI or CABG). CAD, coronary artery disease; MACE, Major adverse cardiac events

Figure 3:. FAI Score and cardiovascular risk prediction: capturing the inflammatory risk.

Kaplan-Meier curves for the prognostic value of FAI Score in the LAD for cardiac mortality in (A) the whole cohort, (B) patients with no obstructive CAD, (C) patients with obstructive CAD. Prognostic value of FAI Score in the LAD for MACE in (D) whole cohort, (E) patients with no obstructive CAD, (F) patients with obstructive CAD. Unadjusted HR(95% CI) are represented in the images. (See supplementary figures 5 and 6 for similar results in the LCx and RCA respectively, and Supplementary Table 6 for the HRs after adjustment for risk factors and CADRADS2.0). CAD: coronary artery disease.

Figure 4:. Additive prognostic value of high coronary inflammation recorded in 1, 2 or 3 epicardial arteries.

Prognostic value for cardiac mortality in the whole population (a), patients without obstructive coronary artery disease (CAD) (B) or with obstructive CAD (C). Similarly, the prognostic value for MACE in the whole population (D), patients without obstructive coronary artery disease (CAD) (E) or with obstructive CAD (F). Define coronary artery defined as having FAI-Score >75th percentile. Reference: all 3 coronary arteries (LAD, LCx and RCA) with FAI Score <25^th percentile.

Figure 5:. AI-Risk Classification and cardiovascular risk prediction.

Kaplan-Meier curves for the ability of AI-Risk Classification to prediction cardiac mortality in (A) the whole cohort, (B) patients with no obstructive CAD, (C) patients with obstructive CAD. KM curves for prediction of MACE using the same classification are presented for (D) the whole cohort, (E) patients with no obstructive CAD, (F) patients with obstructive CAD. AI, artificial intelligence; CAD, coronary artery disease.