Impact of the Coronary Artery Calcium Score on Mid- to Long-Term Cardiovascular Mortality and Morbidity Measured With Coronary Computed Tomography Angiography

Contemporary Review of Risk Scores in Prediction of Coronary and Cardiovascular Deaths

PURPOSE OF REVIEW

Explore the current literature supporting risk stratification scores for prediction of coronary and cardiovascular disease deaths.

RECENT FINDINGS

Accurate risk prediction remains the foundation of management choice in primary prevention. When applied to new populations, the calibration of a predictive model will deteriorate, although discrimination changes minimally. One of the approaches with better performance and validation is the initial use of pooled cohort equation to identify low and high-risk patients, followed by coronary artery calcium scoring in those with borderline to intermediate risk. It is important to utilize a risk stratification tool that has been validated in a patient population that resembles the one used to develop the original tool to maintain adequate calibration. It is likely that the future of mortality risk prediction will develop in combined clinical risk predictors and cardiovascular imaging, such coronary artery calcium (CAC) scoring that renders the highest predictive accuracy.

Relationship between Cardiovascular Calcium and Atrial Fibrillation

Coronary artery calcium score (CACS) is associated with increased risk of atrial fibrillation (AF). However, the relationship between the burden of CACS and extra-coronary calcium and the AF is unclear. This cross-sectional study retrospectively analyzed the data of 143,529 participants (74.9% men; mean age, 41.7 ± 8.6 years) who underwent health examination including non-contrast cardiac CT and electrocardiography, from 2010 to 2018 to evaluate the association between cardiac calcium and AF. AF was diagnosed in 679 participants. The prevalence of AF was significantly increased as the CACS increased (p < 0.01). Multivariable analysis adjusted for age, sex, body mass index, hypertension, diabetes, hyperlipidemia, smoking, alcohol, and history of coronary artery disease showed a significant association between a high CACS ≥1000 and AF (OR 2.26, 95% CI 1.07–4.77, p = 0.032). In a subgroup analysis of participants with a CACS ≥100, aortic valve and thoracic aorta calcium were significantly associated with AF (OR 3.49, 95% CI 1.57–7.77, p = 0.002 and OR 2.19, 95% CI 1.14–4.21, p = 0.01, respectively). High CACS was associated with AF, and extra-coronary atherosclerosis was associated with AF in participants with a moderate to very high CACS.

Coronary artery calcium score above 250 confirms the presence of significant stenosis in coronary CT angiography of symptomatic patients

OBJECTIVES

Evaluation of coronary artery calcium score (CACS) at multiple low and high cutoff values for the detection of significant coronary stenosis at two different cutoffs (50 and 70%) in a large number of symptomatic patients was not investigated previously in one study. This study aims to investigate if there are a correlation and statistical significance between different CACS cutoffs and the severity of coronary artery stenosis by coronary CT angiography (CCTA) in symptomatic patients.

METHODS

This is a retrospective study that included all symptomatic patients who had CCTA in a tertiary care hospital over a period of 7 years.

RESULTS

CCTA of 502 patients was evaluated (406 included, mean age 56.2 years); 230 were males (56.7%). The prevalence of stenosis at any percentage was 53.7%, ≥50% was 26.6% and ≥70% was 12.3%. The mean CACS was 84.5 (range 0-1860), for males was 124.5 and for females was 32.1. Patients with CACS of zero (59%) and CACS of ≥1 (41%) had a mean stenosis of 8.9% (range 0-75%) and 52.6% (range 0-100%), respectively. All patients with a CACS of ≥250 were found to have ≥50% stenosis (100% specificity and positive predictive value, 35.2% sensitivity, 81% negative predictive value and 82.6% accuracy). The percentage of stenosis increased as CACS increased with strong statistical significance (P value < 0.0001) and a positive correlation (r = 0.58).

CONCLUSIONS

CACS is a valuable diagnostic tool to predict the severity of coronary artery stenosis. A cutoff value of 250 confirmed the presence of at least 50% stenosis in symptomatic patients.

Importance of the Corrected Calcium Level in Patients With Acute Heart Failure Requiring Intensive Care

Background: Serum calcium (Ca) concentrations in the acute phase of acute heart failure (AHF) have not been not sufficiently investigated.

Methods and Results: This study enrolled 1,291 AHF patients and divided them into 3 groups based on original and corrected Ca concentrations: (1) hypocalcemia (both original and corrected Ca ≤8.7 mg/dL; n=651); (2) pseudo-hypocalcemia (original and corrected Ca ≤8.7 and >8.7 mg/dL, respectively; n=300); and (3) normal/hypercalcemia (both original and corrected Ca >8.7 mg/dL; n=340). AHF patients were also divided into 2 groups based on corrected Ca concentrations: (1) corrected hypocalcemia (corrected Ca ≤8.7 mg/dL; n=651); and (2) corrected normal/hypercalcemia (corrected Ca >8.7 mg/dL; n=640). Of the 951 patients with original hypocalcemia (≤8.7 mg/dL), 300 (31.5%) were classified as corrected normal/hypercalcemia after correction of Ca concentrations by serum albumin. The prognoses in the pseudo-hypocalcemia, low albumin, and corrected normal/hypercalcemia groups, including all-cause death within 730 days, were significantly poorer than in the other groups. Multivariate Cox regression analysis showed that classification into the pseudo-hypocalcemia, hypoalbumin, and corrected normal/hypercalcemia groups independently predicted 730-day all-cause death (hazard ratios [95% confidence intervals] of 1.497 [1.153–1.943], 2.392 [1.664–3.437], and 1.294 [1.009–1.659], respectively).

Conclusions: Corrected normal/hypercalcemia was an independent predictor of prognosis because this group included patients with pseudo-hypocalcemia, which was affected by the serum albumin concentration.

Prediction of coronary artery calcium scoring from surface electrocardiogram in atherosclerotic cardiovascular disease: a pilot study

Aims

Coronary artery calcium (CAC) scoring is an established tool for cardiovascular risk stratification. However, the lack of widespread availability and concerns about radiation exposure have limited the universal clinical utilization of CAC. In this study, we sought to explore whether machine learning (ML) approaches can aid cardiovascular risk stratification by predicting guideline recommended CAC score categories from clinical features and surface electrocardiograms.

Methods and results

In this substudy of a prospective, multicentre trial, a total of 534 subjects referred for CAC scores and electrocardiographic data were split into 80% training and 20% testing sets. Two binary outcome ML logistic regression models were developed for prediction of CAC scores equal to 0 and ≥400. Both CAC = 0 and CAC ≥400 models yielded values for the area under the curve, sensitivity, specificity, and accuracy of 84%, 92%, 70%, and 75%, and 87%, 91%, 75%, and 81%, respectively. We further tested the CAC ≥400 model to risk stratify a cohort of 87 subjects referred for invasive coronary angiography. Using an intermediate or higher pretest probability (≥15%) to predict CAC ≥400, the model predicted the presence of significant coronary artery stenosis (P = 0.025), the need for revascularization (P &lt; 0.001), notably bypass surgery (P = 0.021), and major adverse cardiovascular events (P = 0.023) during a median follow-up period of 2 years.

Conclusion

ML techniques can extract information from electrocardiographic data and clinical variables to predict CAC score categories and similarly risk-stratify patients with suspected coronary artery disease.

Predictive value of the coronary artery calcium score and advanced plaque characteristics: Post hoc analysis of the PREDICT registry

BACKGROUND

Whether coronary plaque characteristics assessed in coronary computed tomography angiography (CCTA) in association with the coronary artery calcium score (CACS) have predictive value for coronary events is unclear. We aimed to examine the predictive value of the CACS and plaque characteristics for the occurrence of coronary events.

METHODS

Among 2802 patients who were analyzed in the PREDICT registry, 2083 with suspected coronary artery disease (CAD) were studied using post hoc analysis. High-risk plaques were defined as having ≥2 adverse characteristics, such as low computed tomographic attenuation, positive remodeling, spotty calcification, and napkin-ring sign. An adjudicative composite of coronary events (cardiac death, nonfatal acute coronary syndrome, and coronary revascularization ≥3 months after indexed CCTA) were analyzed.

RESULTS

Seventy-three (3.5%) patients had coronary events and 313 (15.0%) had high-risk plaques. Multivariate Cox proportional hazard analysis showed that high-risk plaques remained an independent predictor of coronary events (adjusted hazard ratio [HR] 1.95, 95% confidence interval [CI] 1.13-3.34, P ​= ​0.0154), as well as the log-transformed CACS (adjusted HR 1.24, 95% CI 1.11-1.39, P ​= ​0.0002) and the presence of obstructive stenosis (adjusted HR 5.63, 95% CI 3.22-10.12, P 0.0001). In subgroup analyses, high-risk plaques were independently predictive only in the low CACS class (<100).

CONCLUSION

This study shows that assessment of adverse features by coronary plaque imaging independently predicts coronary events in patients with suspected CAD and a low CACS. Our findings suggest that the clinical value of high-risk plaques to CACS and stenosis assessment appears marginal.

Incidental Coronary Artery Calcification and Stroke Risk in Patients With Atrial Fibrillation

OBJECTIVE. Atrial fibrillation (AF) is a major risk factor for stroke. The CHA₂DS_2-VASc score is used to risk stratify patients, and the score includes known coronary artery disease (CAD) as a variable. The aim of this study was to assess if the presence of incidental coronary artery calcification (CAC), without known CAD, is associated with stroke independent of CHA₂DS₂-VASc variables. MATERIALS AND METHODS. A retrospective review of health records was performed for patients who had AF, a chest CT scan performed within 1 year, and a subsequent visit for stroke. Patients with CAD and other vascular disease, a mechanical valve, or who were older than 74 years old were excluded. Included patients were one-to-one matched by age and CHA₂DS₂-VASc risk factors to patients who had had similar follow-up but who did not have a stroke. Nongated CT images were reviewed for CAC. Univariate and Cox regression analyses were performed. RESULTS. A total of 203 patients met the study criteria, and 203 matched patients without stroke were identified. Median age was 61 years old with stroke and 62 years old without stroke (p = 0.99). In both groups, 82 (39.0%) were women and the median CHA₂DS₂-VASc was 2 (interquartile range, 1-2). Anticoagulation medication was prescribed to 46 (22.7%) patients in the group who had had a stroke and 52 (25.6%) in the group without stroke (p = 0.49). On Cox regression analysis, CAC was associated with stroke (hazard ratio [HR], 1.47; 95% CI, 1.10-1.97; p < 0.01) and mortality (adjusted HR, 1.41; 95% CI, 1.02-1.95; p = 0.04). CONCLUSION. Patients with AF and incidental CAC depicted on chest CT have an increased risk of stroke and mortality beyond established risk factors.

Usefulness of the Coronary Artery Calcium Score in Predicting Subsequent Coronary Interventions-A Ten-Year Single-Center Perspective

There is no consensus as to whether the Coronary Artery Calcium Score (CACS) results can affect the therapeutic approach that is selected for coronary artery disease. The aim of this study was to follow patients’ management over a period of ten years after application of the CACS. Methods: The research was conducted as a prospective, single-center, long-distance study. In 174 asymptomatic patients (78M; aged 58.9 ± 7.86), a CACS examination using 64-slice computed tomography was performed between 2008 and 2009. The patients were divided into three subgroups according to the CACS results using Agatston Units (AU)—G1: CACS = 0 AU (52 pts); G2: CACS = 1–399 AU (64 pts) and G3: CACS ≥ 400 AU (58 pts). During the ten years of follow-up, the classical cardiovascular risk factors, drugs, diseases, and information about the therapeutic approach that was used (PCI—Percutaneous Coronary Intervention; CABG—Coronary Artery Bypass Graft) were also analyzed. Results: The average time until a percutaneous intervention (PCI) was 825.2 ± 1111.7 and for CABG, it was 529.0 ± 833.6. PCI was performed in 5.8% (G1), 4.7% (G2) and 32.6% (G3) of the cases, respectively; p = 0.0000. CABG was performed in 0% (G1), 1.6% (G2) and 18.9% (G3) of the cases, respectively; 0.0035 Yates. The area under the curve in PCI was 0.783 (95% CI: 0.714–0.841); in CABG, it was 0.825 (95% CI: 0.760–0.878) and the average for both groups was 0.838 (95% CI: 0.774–0.889). Conclusions: The coronary artery calcium score can potentially help to predict the best therapeutic approach for coronary artery disease in a ten-year perspective.