The Multi-Ethnic Study of Atherosclerosis
AUTHORS (FIRST NAME, LAST NAME):
Morteza Naghavi, MD, Anthony P. Reeves, PhD, Kyle Atlas, BS, Chenyu Zhang, MS, Thomas Atlas, MD, Claudia Henschke, PhD., MD, David Yankelevitz, MD, Matthew J. Budoff, MD, Dong Li, PhD, Wenjun Fan, MD, PhD, Ruilin Yu, MPH, Andrea Branch, MD, Ning Ma, PhD, Rowena Yip, PhD, Sion K. Roy, MD, Khurram Nasir, M.D, Sabee Molloi, PhD, Zahi Fayad, PhD, Michael V. McConnell, MD, MSEE, Ioannis Kakadiaris, MD, Javier Zuelueta, MD, David J. Maron, MD, Jagat Narula, MD, PhD, Prediman Shah, MD, Kim Williams, MD, Daniel Levy, M.D, and Nathan D. Wong, PhD.
a. HeartLung.AI, Houston, TX, 77021
b. Department of Electrical and Computer Engineering, Cornell University, Ithaca, NY 14853
c. Tustin Teleradiology, Tustin, CA 92780
d. Mount Sinai Hospital, New York, NY 10029
e. The Lundquist Institute, Torrance, CA 90502
f. Houston Methodist Hospital, Houston, TX 77030
g. Department of Radiology, University of California Irvine, CA 92697
h. Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305
i. The University of Texas Health Science Center at Houston, TX, 77030
j. University of Louisville, Louisville, KY
k. Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, 20824
l. Heart Disease Prevention Program, Division of Cardiology, University of California Irvine, CA 92697
m. Department of Epidemiology & Biostatistics, University of California Irvine, CA 92697
n. Department of Epidemiology, University of California, Los Angeles, CA 90095
o. Cedars-Sinai Medical Center, Los Angeles, CA, 90048
Abstract:
Background:
The CHA2Ds2-VASc risk score is a clinical tool for stroke prediction. It is mainly used in patients with atrial fibrillation (AF) but is also applied to the non-AF population. We previously reported that artificial intelligence (AI)-enabled left atrial (LA) volumetry from coronary artery calcium (CAC) scans (AI-CAC) predicts AF as early as one year and outperformed CHARGE-AF and NT-proBNP. In this report, we compare AI-CAC LA volumetry to the CHA2DS2-VASc risk score and evaluate the incremental value of incorporating AI-CAC LA volume to CHA2DS2-VASc for incident stroke prediction in the non-AF population.
Methods:
We applied AI-CAC LA volumetry to CAC scans of 5830 people without AF (52.2% women, age 61.7±10.2 years) enrolled in the Multi-Ethnic Study of Atherosclerosis (MESA) baseline (2000-2002). We used the 15-year outcomes data for incident stroke (ischemic and hemorrhagic) and assessed discrimination using the time-dependent area under the curve (AUC) between AI-CAC LA volume vs. CHA2DS2-VASc risk score. Notably, the CHA2DS2-VASc score in this non-AF population ranges from 0 to 5, whereas in the AF population it typically ranges from 0 to 9 points.
Results:
252 cases of stroke accrued over 15 years. The median and mean ± SD of CHA2DS2-VASc score at baseline were 1.0 and 1.58 ± 1.15, respectively. The cumulative incidence of stroke for the 95th percentile of AI-CAC LA volume (n=291) vs. CHA2DS2-VASc 4 or 5 points (n=364) was 13.0% and 13.7%, respectively. AI-CAC LA volume significantly improved the AUC of CHA2DS2-VASc for stroke prediction at 2-year follow-up (0.76 for CHA2Ds2-VASc vs. 0.81 for CHA2DS2-VASc plus LA volume, p=0.03), 5-year follow-up (0.73 vs. 0.77, p=0.01), 10-year follow-up (0.70 vs. 0.75, p<0.0001) and 15- year follow-up (0.70 vs. 0.74, p<0.0001).
Conclusion:
In this multi-ethnic longitudinal cohort of people without AF, addition of LA volume significantly improved performance of the CHA2DS2-VASc risk score for stroke prediction from 2 to 15 years follow-up. Further studies are needed to evaluate the clinical utility of adding LA volume to CHA2DS2-VASc risk score in people with and without AF.
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