1. AI-enabled cardiac chambers volumetry in coronary artery calcium scans (AI-CACTM) predicts heart failure and outperforms NT-proBNP: The multi-ethnic study of Atherosclerosis
- Author
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Naghavi, Morteza, Reeves, Anthony, Budoff, Matthew, Li, Dong, Atlas, Kyle, Zhang, Chenyu, Atlas, Thomas, Roy, Sion K, Henschke, Claudia I, Wong, Nathan D, Defilippi, Christopher, Levy, Daniel, and Yankelevitz, David F
- Subjects
Biomedical and Clinical Sciences ,Cardiovascular Medicine and Haematology ,Clinical Sciences ,Heart Disease ,Aging ,Cardiovascular ,Networking and Information Technology R&D (NITRD) ,Prevention ,Heart Disease - Coronary Heart Disease ,Machine Learning and Artificial Intelligence ,Atherosclerosis ,Humans ,Female ,Male ,Peptide Fragments ,Natriuretic Peptide ,Brain ,Aged ,Heart Failure ,Predictive Value of Tests ,Coronary Artery Disease ,Middle Aged ,Risk Factors ,Biomarkers ,Vascular Calcification ,Risk Assessment ,Prognosis ,United States ,Time Factors ,Incidence ,Aged ,80 and over ,Computed Tomography Angiography ,Artificial Intelligence ,Coronary Angiography ,Radiographic Image Interpretation ,Computer-Assisted ,Reproducibility of Results ,Multidetector Computed Tomography ,Asymptomatic Diseases ,Artificial intelligence ,Coronary artery calcium ,Heart failure ,Left ventricular volume ,NT-proBNP ,Cardiorespiratory Medicine and Haematology ,Cardiovascular System & Hematology ,Cardiovascular medicine and haematology ,Clinical sciences ,Applied computing - Abstract
IntroductionCoronary artery calcium (CAC) scans contain useful information beyond the Agatston CAC score that is not currently reported. We recently reported that artificial intelligence (AI)-enabled cardiac chambers volumetry in CAC scans (AI-CAC™) predicted incident atrial fibrillation in the Multi-Ethnic Study of Atherosclerosis (MESA). In this study, we investigated the performance of AI-CAC cardiac chambers for prediction of incident heart failure (HF).MethodsWe applied AI-CAC to 5750 CAC scans of asymptomatic individuals (52% female, White 40%, Black 26%, Hispanic 22% Chinese 12%) free of known cardiovascular disease at the MESA baseline examination (2000-2002). We used the 15-year outcomes data and compared the time-dependent area under the curve (AUC) of AI-CAC volumetry versus NT-proBNP, Agatston score, and 9 known clinical risk factors (age, gender, diabetes, current smoking, hypertension medication, systolic and diastolic blood pressure, LDL, HDL for predicting incident HF over 15 years.ResultsOver 15 years of follow-up, 256 HF events accrued. The time-dependent AUC [95% CI] at 15 years for predicting HF with AI-CAC all chambers volumetry (0.86 [0.82,0.91]) was significantly higher than NT-proBNP (0.74 [0.69, 0.77]) and Agatston score (0.71 [0.68, 0.78]) (p
- Published
- 2024