Improved Prediction of Cardiovascular Events Using Serial Cardio-Ankle Vascular Index (CAVI) Measurements: A 10-Year Prospective Cohort Study
Issued Date
2026-06-01
Resource Type
ISSN
01609289
eISSN
19328737
Scopus ID
2-s2.0-105041616807
Journal Title
Clinical Cardiology
Volume
49
Issue
6
Rights Holder(s)
SCOPUS
Bibliographic Citation
Clinical Cardiology Vol.49 No.6 (2026)
Suggested Citation
Limpijankit T., Vathesatogkit P., Matchariyakul D., Thongmung N., Siriyotha S., Thakkinstian A., Sritara P. Improved Prediction of Cardiovascular Events Using Serial Cardio-Ankle Vascular Index (CAVI) Measurements: A 10-Year Prospective Cohort Study. Clinical Cardiology Vol.49 No.6 (2026). doi:10.1002/clc.70382 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/117418
Title
Improved Prediction of Cardiovascular Events Using Serial Cardio-Ankle Vascular Index (CAVI) Measurements: A 10-Year Prospective Cohort Study
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Corresponding Author(s)
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Abstract
Background: Most studies evaluating the cardio-ankle vascular index (CAVI) as a marker of arterial stiffness are cross-sectional, limiting insights into long-term vascular changes. We investigated whether serial CAVI measurements improve the prediction of cardiovascular (CV) events beyond a single baseline value. Methods: The Electricity Generating Authority of Thailand (EGAT) study is a prospective cohort with 5-year follow-up intervals. Participants with prior coronary artery disease (CAD) or stroke were excluded. Demographic, clinical, laboratory data, medication use, and CAVI were collected. Serial CAVI was analyzed as a time-varying covariate in Cox proportional hazards models, incorporating baseline, 5-year, and 10-year measurements. The primary composite CV outcomes comprised CAD, stroke, or CV death. Cox proportional hazards models assessed associations between baseline or serial CAVI and CV outcomes, adjusted for conventional risk factors. Results: Among 3913 participants (mean age 49.0 ± 10.8 years; 73.4% male; BMI 24.3 ± 3.6 kg/m<sup>2</sup>), mean CAVI increased from 7.7 ± 1.1 to 8.2 ± 1.3 over 10 years (p < 0.001). During a median follow-up of 9.1 ± 3.1 years, 0.8% experienced composite CV events. Serial CAVI was independently associated with CV outcomes (HR 1.47; 95% CI 1.06–2.03; p = 0.019), whereas baseline CAVI was not (HR 1.14; 95% CI 0.93–1.40; p = 0.22). Model indices (ΔAIC = 37.1; ΔBIC = 32.7) supported superior predictive performance for serial CAVI. Conclusion: Serial CAVI measurements better predict long-term CV events than a single baseline value. Longitudinal CAVI monitoring may enhance CV risk stratification and support preventive cardiovascular care.