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Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans
Published on: August 28, 2018
Association of coronary artery calcium score with cardiovascular events: a retrospective study
Xun Yu1, Guifang Li1, Wenbo Yin1
1Department of Radiology, Dangyang People's Hospital, Yichang, China.
Insights
The coronary artery calcium score (CACS) predicts cardiovascular events, especially in males and hypertensive patients. A high CACS (≥400) significantly increases mortality and major adverse cardiovascular events risk.
Area of Science:
- Cardiology
- Radiology
- Preventive Medicine
Background:
- Coronary artery calcium score (CACS) quantifies coronary atherosclerosis.
- Its predictive value across diverse patient groups requires further investigation.
Purpose of the Study:
- To evaluate the predictive capability of CACS for cardiovascular events in various patient populations.
- To assess the association between CACS levels and 1-year mortality and major adverse cardiovascular events (MACE).
Main Methods:
- Retrospective analysis of 100 patients undergoing coronary computed tomography angiography (CCTA).
- Patients stratified into four CACS groups (0, 1-100, 101-399, ≥400).
- Survival analysis and Cox regression utilized to determine risk predictors.
Main Results:
- CACS ≥400 demonstrated the lowest 1-year survival probability.
- High CACS (≥400) was linked to a 4.76-fold increased risk of mortality/MACE compared to CACS=0.
- Male sex, smoking, and hypertension were significant independent predictors of adverse events.
Conclusions:
- CACS is an independent predictor of mortality and MACE in symptomatic individuals.
- CACS exhibits strongest predictive power in males and hypertensive patients.
- Findings support CACS utility for risk stratification and identifying high-risk patients.
Background:
The coronary artery calcium score (CACS) reflects coronary atherosclerosis burden, but its predictive value in different populations remains to be fully elucidated. The aim of this study was to investigate the predictive value of CACS for cardiovascular events in different patient populations.
Methods:
One hundred patients (mean age 65.4±10.7 years; 63 males) who underwent coronary computed tomography angiography (CCTA) were retrospectively enrolled and classified into four CACS strata (0, 1-100, 101-399, ≥400). The primary endpoint was all-cause mortality and major adverse cardiovascular events (MACEs) at 1 year. Survival curves and Cox regression were performed.
Results:
Patients with CACS ≥400 had the lowest 1-year survival probability (log-rank P=0.011), while CACS =0 group had the highest survival. Cox regression suggested CACS ≥400 was associated with a 4.76-fold higher risk of mortality or MACE compared to CACS =0 [adjusted hazard ratio (HR) 4.76, 95% confidence interval (CI): 1.82-12.45, P=0.012], after adjusting for age, sex, hypertension, diabetes, and dyslipidemia. Significant predictors included male sex (HR 3.72, P=0.047), smoking (HR 2.87, P=0.013), and hypertension (HR 4.76, P=0.009). In subgroup analysis, the predictive value of CACS was robust in males (P=0.0031) and hypertensive patients (P=0.021), but not significant in females or normotensives (P>0.5).
Conclusions:
CACS is a significant independent predictor of mortality and MACE in symptomatic patients, with the strongest discriminative power in males and those with hypertension. These findings support the utility of CACS for risk stratification and early identification of high-risk individuals in clinical practice.
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