Juan Miguel Fernández-Alvira1, Valentín Fuster2, Stuart Pocock3, Javier Sanz4, Leticia Fernández-Friera5, Martín Laclaustra6, Rodrigo Fernández-Jiménez7, José Mendiguren8, Antonio Fernández-Ortiz9, Borja Ibáñez10, Héctor Bueno11. 1. Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain. 2. Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain; Icahn School of Medicine at Mount Sinai, New York, New York. Electronic address: vfuster@cnic.es. 3. Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain; London School of Hygiene and Tropical Medicine, London, United Kingdom. 4. Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain; Icahn School of Medicine at Mount Sinai, New York, New York. 5. Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain; Departamento de Cardiología, Hospital Universitario HM Montepríncipe, Centro Integral de Enfermedades Cardiovasculares (CIEC), Madrid, Spain; Centro de Investigación Biomédica en Red (CIBER) de Enfermedades Cardiovasculares, Spain. 6. Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain; Aragon Institute for Health Research, Translational Research Unit, Hospital Universitario Miguel Servet, Zaragoza, Spain. 7. Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain; Icahn School of Medicine at Mount Sinai, New York, New York; Centro de Investigación Biomédica en Red (CIBER) de Enfermedades Cardiovasculares, Spain. 8. Banco de Santander, Madrid, Spain. 9. Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain; Departamento de Cardiología, Hospital Clínico San Carlos, Madrid, Spain; Facultad de Medicina, Universidad Complutense de Madrid, Madrid, Spain. 10. Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain; Centro de Investigación Biomédica en Red (CIBER) de Enfermedades Cardiovasculares, Spain; Departamento de Cardiología, Instituto de Investigación Sanitaria (IIS)-Fundación Jiménez Díaz Hospital, Madrid, Spain. 11. Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain; Instituto de Investigación i+12, Cardiology Department, Hospital Universitario 12 de Octubre, Madrid, Spain; Facultad de Medicina, Universidad Complutense de Madrid, Madrid, Spain. Electronic address: hector.bueno@cnic.es.
Abstract
BACKGROUND: The ideal cardiovascular health score (ICHS) is recommended for use in primary prevention. Simpler tools not requiring laboratory tests, such as the Fuster-BEWAT (blood pressure [B], exercise [E], weight [W], alimentation [A], and tobacco [T]) score (FBS), are also available. OBJECTIVES: The purpose of this study was to compare the effectiveness of ICHS and FBS in predicting the presence and extent of subclinical atherosclerosis. METHODS: A total of 3,983 participants 40 to 54 years of age were enrolled in the PESA (Progression of Early Subclinical Atherosclerosis) cohort. Subclinical atherosclerosis was measured in right and left carotids, abdominal aorta, right and left iliofemoral arteries, and coronary arteries. Subjects were classified as having poor, intermediate, or ideal cardiovascular health based on the number of favorable ICHS or FBS. RESULTS: With poor ICHS and FBS as references, individuals with ideal ICHS and FBS showed lower adjusted odds of having atherosclerotic plaques (ICHS odds ratio [OR]: 0.41; 95% confidence interval [CI]: 0.31 to 0.55 vs. FBS OR: 0.49; 95% CI: 0.36 to 0.66), coronary artery calcium (CACS) ≥1 (CACS OR: 0.41; 95% CI: 0.28 to 0.60 vs. CACS OR: 0.53; 95% CI: 0.38 to 0.74), higher number of affected territories (OR: 0.32; 95% CI: 0.26 to 0.41 vs. OR: 0.39; 95% CI: 0.31 to 0.50), and higher CACS level (OR: 0.40; 95% CI: 0.28 to 0.58 vs. OR: 0.52; 95% CI: 0.38 to 0.72). Similar levels of significantly discriminating accuracy were found for ICHS and FBS with respect to the presence of plaques (C-statistic: 0.694; 95% CI: 0.678 to 0.711 vs. 0.692; 95% CI: 0.676 to 0.709, respectively) and for CACS ≥1 (C-statistic: 0.782; 95% CI: 0.765 to 0.800 vs. 0.780; 95% CI: 0.762 to 0.798, respectively). CONCLUSIONS: Both scores predict the presence and extent of subclinical atherosclerosis with similar accuracy, highlighting the value of the FBS as a simpler and more affordable score for evaluating the risk of subclinical disease.
BACKGROUND: The ideal cardiovascular health score (ICHS) is recommended for use in primary prevention. Simpler tools not requiring laboratory tests, such as the Fuster-BEWAT (blood pressure [B], exercise [E], weight [W], alimentation [A], and tobacco [T]) score (FBS), are also available. OBJECTIVES: The purpose of this study was to compare the effectiveness of ICHS and FBS in predicting the presence and extent of subclinical atherosclerosis. METHODS: A total of 3,983 participants 40 to 54 years of age were enrolled in the PESA (Progression of Early Subclinical Atherosclerosis) cohort. Subclinical atherosclerosis was measured in right and left carotids, abdominal aorta, right and left iliofemoral arteries, and coronary arteries. Subjects were classified as having poor, intermediate, or ideal cardiovascular health based on the number of favorable ICHS or FBS. RESULTS: With poor ICHS and FBS as references, individuals with ideal ICHS and FBS showed lower adjusted odds of having atherosclerotic plaques (ICHS odds ratio [OR]: 0.41; 95% confidence interval [CI]: 0.31 to 0.55 vs. FBS OR: 0.49; 95% CI: 0.36 to 0.66), coronary artery calcium (CACS) ≥1 (CACS OR: 0.41; 95% CI: 0.28 to 0.60 vs. CACS OR: 0.53; 95% CI: 0.38 to 0.74), higher number of affected territories (OR: 0.32; 95% CI: 0.26 to 0.41 vs. OR: 0.39; 95% CI: 0.31 to 0.50), and higher CACS level (OR: 0.40; 95% CI: 0.28 to 0.58 vs. OR: 0.52; 95% CI: 0.38 to 0.72). Similar levels of significantly discriminating accuracy were found for ICHS and FBS with respect to the presence of plaques (C-statistic: 0.694; 95% CI: 0.678 to 0.711 vs. 0.692; 95% CI: 0.676 to 0.709, respectively) and for CACS ≥1 (C-statistic: 0.782; 95% CI: 0.765 to 0.800 vs. 0.780; 95% CI: 0.762 to 0.798, respectively). CONCLUSIONS: Both scores predict the presence and extent of subclinical atherosclerosis with similar accuracy, highlighting the value of the FBS as a simpler and more affordable score for evaluating the risk of subclinical disease.
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