AIM: We assessed whether there is an association between the cardio-ankle vascular index (CAVI) score and the carotid intima media thickness (IMT), the pulse wave velocity (PWV) and the central augmentation index (CAIx) that is independent of the subject's cardiovascular risk and pharmacological treatment. METHODS: The CAVI score was measured in 500 subjects using a VaSera device and the brachial ankle PWV (ba-PWV) was calculated. A carotid ultrasound was used to measure the IMT. A Mobil-O-Graph device was used to measure the carotid femoral PWV (cf-PWV) and the CAIx. The Framingham-D'Agostino and SCORE scales were used to measure the subject's cardiovascular risk. RESULTS: The mean value of the CAVI score was 8.59 ± 1.1. IMT, CAIx and PWV maintained a positive association with the CAVI score (p < 0.01) in a multiple linear regression analysis, after adjusting for the subject's cardiovascular risk, body mass index and pharmacological treatment. The cut-off level that gave the maxima sensitivity and specificity to detect a mean IMT of > 0.90 mm was 8.95 (AUC=0.67) for the CAVI score, 8.85 (AUC=0.66) for cf-PWV and 15.10 (AUC=0.66) for ba-PWV. The cut-off to detect a maxima IMT of > 0.90 mm was 8.60 (AUC=0.62) for the CAVI score, 8.85 (AUC=0.64) for cf-PWV and 15.75 (AUC=0.70) for ba-PWV. CONCLUSION: There was a positive association of the CAVI score with vascular structure and function parameters that was independent of cardiovascular risk and any medications being used by the subject. The ability of the CAVI score to predict carotid atherosclerosis is similar to that of cf-PWV and ba-PWV in Caucasian adults.
AIM: We assessed whether there is an association between the cardio-ankle vascular index (CAVI) score and the carotid intima media thickness (IMT), the pulse wave velocity (PWV) and the central augmentation index (CAIx) that is independent of the subject's cardiovascular risk and pharmacological treatment. METHODS: The CAVI score was measured in 500 subjects using a VaSera device and the brachial ankle PWV (ba-PWV) was calculated. A carotid ultrasound was used to measure the IMT. A Mobil-O-Graph device was used to measure the carotid femoral PWV (cf-PWV) and the CAIx. The Framingham-D'Agostino and SCORE scales were used to measure the subject's cardiovascular risk. RESULTS: The mean value of the CAVI score was 8.59 ± 1.1. IMT, CAIx and PWV maintained a positive association with the CAVI score (p < 0.01) in a multiple linear regression analysis, after adjusting for the subject's cardiovascular risk, body mass index and pharmacological treatment. The cut-off level that gave the maxima sensitivity and specificity to detect a mean IMT of > 0.90 mm was 8.95 (AUC=0.67) for the CAVI score, 8.85 (AUC=0.66) for cf-PWV and 15.10 (AUC=0.66) for ba-PWV. The cut-off to detect a maxima IMT of > 0.90 mm was 8.60 (AUC=0.62) for the CAVI score, 8.85 (AUC=0.64) for cf-PWV and 15.75 (AUC=0.70) for ba-PWV. CONCLUSION: There was a positive association of the CAVI score with vascular structure and function parameters that was independent of cardiovascular risk and any medications being used by the subject. The ability of the CAVI score to predict carotid atherosclerosis is similar to that of cf-PWV and ba-PWV in Caucasian adults.
Authors: Leticia Gomez-Sanchez; Luis Garcia-Ortiz; M Carmen Patino-Alonso; Jose I Recio-Rodriguez; Rigo Fernando; Ruth Marti; Cristina Agudo-Conde; Emiliano Rodriguez-Sanchez; Jose A Maderuelo-Fernandez; Rafel Ramos; Manuel A Gomez-Marcos Journal: Cardiovasc Diabetol Date: 2016-10-24 Impact factor: 9.951
Authors: Henry Boardman; Adam J Lewandowski; Merzaka Lazdam; Yvonne Kenworthy; Polly Whitworth; Charlotte L Zwager; Jane M Francis; Christina Y L Aye; Wilby Williamson; Stefan Neubauer; Paul Leeson Journal: J Hypertens Date: 2017-03 Impact factor: 4.844
Authors: Leticia Gomez-Sanchez; Luis Garcia-Ortiz; Maria C Patino-Alonso; Jose I Recio-Rodriguez; Natalia Feuerbach; Ruth Marti; Cristina Agudo-Conde; Emiliano Rodriguez-Sanchez; Jose A Maderuelo-Fernandez; Rafel Ramos; Manuel A Gomez-Marcos Journal: PLoS One Date: 2017-04-17 Impact factor: 3.240
Authors: Jirar Topouchian; Carlos Labat; Sylvie Gautier; Magnus Bäck; Apostolos Achimastos; Jacques Blacher; Marcin Cwynar; Alejandro de la Sierra; Denes Pall; Francesco Fantin; Katalin Farkas; Luis Garcia-Ortiz; Zoya Hakobyan; Piotr Jankowski; Ana Jelakovic; Zhanna Kobalava; Alexandra Konradi; Yulia Kotovskaya; Marina Kotsani; Irina Lazareva; Alexander Litvin; Viktor Milyagin; Iveta Mintale; Oscar Persson; Rafael Ramos; Anatoly Rogoza; Ligita Ryliskyte; Angelo Scuteri; Yuriy Sirenko; Georges Soulis; Nebojsa Tasic; Maryna Udovychenko; Saule Urazalina; Peter Wohlfahrt; Parounak Zelveian; Athanase Benetos; Roland Asmar Journal: J Hypertens Date: 2018-04 Impact factor: 4.844
Authors: Iuliia Pavlovska; Sarka Kunzova; Juraj Jakubik; Jana Hruskova; Maria Skladana; Irma Magaly Rivas-Serna; Jose R Medina-Inojosa; Francisco Lopez-Jimenez; Robert Vysoky; Yonas E Geda; Gorazd B Stokin; Juan P González-Rivas Journal: Lipids Health Dis Date: 2020-07-15 Impact factor: 3.876