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Coronary Calcium Score for the Prediction of Asymptomatic Coronary Artery Disease in Patients With Ischemic Stroke.

ABSTRACT: Purpose: Many patients with ischemic stroke have concomitant coronary artery disease (CAD). However, it remains unclear which stroke patients should undergo evaluation for asymptomatic CAD, and which screening tools are appropriate. We investigated the role of coronary artery calcium (CAC) score as a screening tool for asymptomatic but severe CAD in acute stroke patients. We determined the selection criteria for CAC screening based on risk factors and cerebral atherosclerosis. Materials and Methods: The present study included consecutive patients with acute stroke who had undergone cerebral angiography and multi-detector computed tomography coronary angiography. Severe CAD was defined as left main artery disease or three-vessel disease. Enrolled patients were randomly assigned to two sets; a set for developing selection criteria and a set for validation. To develop selection criteria, we identified associated factors with severe CAD regarding clinical factors and cerebral atherosclerosis. CAD predictability of selection criteria with the CAC score was calculated. Results: Overall, 2,658 patients were included. Severe CAD was present in 360 patients (13.5%). CAC score was associated with CAD severity (P < 0.001). In the development set (N = 1,860), severe CAD was associated with age >65 years [odds ratio (95% confidence interval), 2.62 (1.93-3.55)], male sex (1.81 [1.33-2.46]), dyslipidemia (1.77 [1.25-2.61]), peripheral artery disease (2.64 [1.37-5.06]) and stenosis in the cervicocephalic branches, including the internal carotid (2.79 [2.06-3.78]) and vertebrobasilar arteries (2.08 [1.57-2.76]). We determined the combination of clinical and arterial factors as the selection criteria for CAC evaluation. The cut-off criterion was two or more elements of the selection criteria. The area under the curve (AUC) of the selection criteria was 0.701. The AUC significantly improved to 0.836 when the CAC score was added (P < 0.001). In the validation set (N = 798), the AUC of the selection criteria only was 0.661, and that of the CAC score was 0.833. The AUC of the selection criteria + CAC score significantly improved to 0.861(P < 0.001). Conclusion: The necessity for CAC evaluation could be determined based on the presence of risk factors and significant stenosis of the cervicocephalic arteries. CAC evaluation may be useful for screening for severe CAD in stroke patients.

SUBMITTER: Choi HY

PROVIDER: S-EPMC7134382 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Coronary Calcium Score for the Prediction of Asymptomatic Coronary Artery Disease in Patients With Ischemic Stroke.

Choi Hye-Yeon HY Shin Soo Jeong SJ Yoo Joonsang J Lee Kijeong K Song Dongbeom D Kim Young Dae YD Nam Hyo Suk HS Lee Kyung Yul KY Lee Hye Sun HS Kim Dong Joon DJ Heo Ji Hoe JH

Frontiers in neurology 20200327

<b>Purpose:</b> Many patients with ischemic stroke have concomitant coronary artery disease (CAD). However, it remains unclear which stroke patients should undergo evaluation for asymptomatic CAD, and which screening tools are appropriate. We investigated the role of coronary artery calcium (CAC) score as a screening tool for asymptomatic but severe CAD in acute stroke patients. We determined the selection criteria for CAC screening based on risk factors and cerebral atherosclerosis. <b>Material ...[more]

PMID: 32292387

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Project description:Study Objectives: Coronary artery disease is considered to be the major cause of death amongst patients with ischemic stroke. The coronary artery calcium (CAC) score is related not only to sleep-disordered breathing, but also with future risk of cardiovascular mortality. We investigated the association between the severity of sleep-disordered breathing and CAC score in patients with ischemic stroke. Methods: We included 32 patients who underwent coronary multichannel computed tomography and polysomnography (within 2 years of the stroke event) amongst the patients admitted to our clinic due to acute ischemic stroke. We investigated vascular risk factors, polysomnography findings, and sleep questionnaire scores, and their relationships with the CAC score. Results: All patients were found to have sleep apnea of any degree, and 23 (72%) had severe sleep apnea. Twenty-three (72%) patients had a positive CAC score. Higher CAC scores were associated with elevated respiratory disturbance index (RDI), apnea index, oxygen desaturation index, and STOP-BANG test scores. Multivariate analysis after adjusting for potential confounding factors revealed independent relationships between the CAC score and the RDI (ß [SE] = 5.3 [2.1], p = 0.01), oxygen desaturation index (ß [SE] = 6.8 [2.8], p = 0.02), and STOP-BANG test score (ß [SE] = 90.3 [37.7], p = 0.02). Conclusion: Our findings indicate a relationship between coronary atherosclerotic burden measured by the CAC score and the severity of sleep apnea. Performing polysomnography could be useful for investigating the severity of hidden coronary artery disease among these patients.Brief summaryCurrent Knowledge/Study Rationale: The effect of sleep apnea on coronary artery disease in patients with ischemic stroke has not been explored. We investigated the relationship between sleep apnea, its related characteristics and the coronary artery calcium score in patients with stroke.Study Impact: Our findings reveal a close relationship between the atherosclerosis-related burden measured by the coronary artery calcium score and the severity of sleep apnea that persisted after adjusting for confounding variables related to the risk of coronary artery disease. Proper detection and treatment of sleep apnea might mitigate the risk of future coronary events in patients with ischemic stroke.

Project description:Coronary artery calcium score (CACS) is a reliable predictor for future cardiovascular disease risk. Although deep learning studies using computed tomography (CT) images to predict CACS have been reported, no study has assessed the feasibility of machine learning (ML) algorithms to predict the CACS using clinical variables in a healthy general population. Therefore, we aimed to assess whether ML algorithms other than binary logistic regression (BLR) could predict high CACS in a healthy population with general health examination data. This retrospective observational study included participants who had regular health screening including coronary CT angiography. High CACS was defined by the Agatston score ≥ 100. Univariable and multivariable BLR was performed to assess predictors for high CACS in the entire dataset. When performing ML prediction for high CACS, the dataset was randomly divided into a training and test dataset with a 7:3 ratio. BLR, catboost, and xgboost algorithms with 5-fold cross-validation and grid search technique were used to find the best performing classifier. Performance comparison of each ML algorithm was evaluated with the area under the receiver operating characteristic (AUROC) curve. A total of 2133 participants were included in the final analysis. Mean age and proportion of male sex were 55.4 ± 11.3 years and 1483 (69.5%), respectively. In multivariable BLR analysis, age (odds ratio [OR], 1.12; 95% confidence interval [CI], 1.10-1.15, p < 0.001), male sex (OR, 2.91; 95% CI, 1.57-5.38, p < 0.001), systolic blood pressure (OR, 1.02; 95% CI, 1.00-1.03, p = 0.019), and low-density lipoprotein cholesterol (OR, 1.00; 95% CI, 0.99-1.00, p = 0.047) were significant predictors for high CACS. Performance in predicting high CACS of xgboost was AUROC of 0.823, followed by catboost (0.750) and BLR (0.585). The comparison of AUROC between xgboost and BLR was significant (p for AUROC comparison < 0.001). Xgboost ML algorithm was found to be a more reliable predictor of CACS in healthy participants compared to the BLR algorithm. ML algorithms may be useful for predicting CACS with only laboratory data in healthy participants.

Dataset Information

Coronary Calcium Score for the Prediction of Asymptomatic Coronary Artery Disease in Patients With Ischemic Stroke.

Publications

Coronary Calcium Score for the Prediction of Asymptomatic Coronary Artery Disease in Patients With Ischemic Stroke.

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