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Inflammatory Risk and CV Events in Patients Without Obstructive CAD
Quick Takes
- The pericardial fat attenuation score (FAI Score) captures inflammatory risk beyond the current clinical risk stratification and CCTA plaque metrics, particularly among patients without obstructive CAD.
- The AI-Risk algorithm integrates FAI Score with traditional CV risk factors and coronary atherosclerotic plaque burden and stratifies into very high risk (≥10% 8-year risk for fatal cardiac events), high risk (5% to <10%), and low or medium risk (<5%), with good alignment between predicted and observed events, leading to significant reclassification of risk, particularly among those without obstructive CAD.
- The ability to detect inflammatory risk and CCTA plaque will help therapeutic decisions regarding intensity of lipid-lowering strategies and the potential use of anti-inflammatory and other unique strategies whose value can be assessed in randomized trials.
Study Questions:
Does coronary arterial inflammation drive cardiac mortality or major adverse cardiac events (MACE) in patients with or without coronary artery disease (CAD), and can an artificial intelligence (AI)-Risk prognostic algorithm be used as an alternative to traditional risk factor-based calculators to enhance clinical management?
Methods:
This multicenter, longitudinal cohort study included 40,091 consecutive patients undergoing clinically indicated coronary computed tomography angiography (CCTA) (Cohort A) in eight UK hospitals, who were followed up for MACE (i.e., myocardial infarction, new-onset heart failure, or cardiac death) for a median of 2.7 years (interquartile range, 1.4–5.3). Measurement of coronary inflammation from CCTA was derived from a perivascular fat attenuation index score (FAI Score). The prognostic value of FAI Score in the presence and absence of obstructive CAD was evaluated in 3,393 consecutive patients (Cohort B) from two hospitals with the longest follow-up (7.7 years). An AI-enhanced cardiac risk prediction algorithm, which integrates FAI Score, coronary plaque metrics, and clinical risk factors, was trained in the United States, then evaluated in this population to assess its ability to change clinical management effectively.
Results:
In the median follow-up of 2.7 years, patients without obstructive CAD (32,533 [81.1%] of 40,091) accounted for 2,857 (66.3%) of the 4,307 total MACE and 1,118 (63.7%) of the 1,754 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% confidence interval [CI], 13.9–63.9; p < 0.001) or MACE (HR, 12.6; 95% CI, 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 (CV) risk factors and the presence or extent of CAD. The AI-Risk classification was positively associated with cardiac mortality (HR, 6.75; 95% CI, 5.17–8.82; p < 0.001, for very high risk vs. low or medium risk) and MACE (HR, 4.68; 95% CI, 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.
Conclusions:
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.
Perspective:
The AI-Risk algorithm integrates FAI Score with traditional CV risk factors and coronary atherosclerotic plaque burden. It had previously trained to capture the absolute risk for a fatal cardiac event over an 8-year period in a US population. The AI-Risk algorithm classified individuals into very high risk (≥10% 8-year risk for fatal cardiac events), high risk (5% to <10%), and low or medium risk (<5%), with good alignment between predicted and observed events, leading to significant reclassification of risk, particularly among those without obstructive CAD on CCTA. The FAI Score and the new AI-Risk classification use routine CCTA to identify individuals with elevated risk partly due to inflammation, despite the absence of obstructive CAD. These findings set the stage for prospective validation in rigorous randomized trials testing anti-inflammatory or other risk-reduction therapies in the absence of coronary plaque.
Clinical Topics: Cardiovascular Care Team, Invasive Cardiovascular Angiography and Intervention, Noninvasive Imaging, Interventions and Imaging, Computed Tomography, Nuclear Imaging, Prevention
Keywords: Computed Tomography Angiography, Heart Disease Risk Factors, Inflammation
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