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Diastolic Augmentation Index Improves Radial Augmentation Index in Assessing Arterial Stiffness

Arterial stiffness is an important risk factor for cardiovascular events. Radial augmentation index (AI (r)) can be more conveniently measured compared with carotid-femoral pulse wave velocity (cfPWV). However, the performance of AI (r) in assessing arterial stiffness is limited. This study proposes...

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Detalles Bibliográficos
Autores principales: Yao, Yang, Hao, Liling, Xu, Lisheng, Zhang, Yahui, Qi, Lin, Sun, Yingxian, Yang, Benqiang, van de Vosse, Frans N., Yao, Yudong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5517606/
https://www.ncbi.nlm.nih.gov/pubmed/28724946
http://dx.doi.org/10.1038/s41598-017-06094-2
Descripción
Sumario:Arterial stiffness is an important risk factor for cardiovascular events. Radial augmentation index (AI (r)) can be more conveniently measured compared with carotid-femoral pulse wave velocity (cfPWV). However, the performance of AI (r) in assessing arterial stiffness is limited. This study proposes a novel index AI (rd), a combination of AI (r) and diastolic augmentation index (AI (d)) with a weight α, to achieve better performance over AI (r) in assessing arterial stiffness. 120 subjects (43 ± 21 years old) were enrolled. The best-fit α is determined by the best correlation coefficient between AI (rd) and cfPWV. The performance of the method was tested using the 12-fold cross validation method. AI (rd) (r = 0.68, P < 0.001) shows a stronger correlation with cfPWV and a narrower prediction interval than AI (r) (r = 0.61, P < 0.001), AI (d) (r = −0.17, P = 0.06), the central augmentation index (AI (c)) (r = 0.61, P < 0.001) or AI (c) normalized for heart rate of 75 bpm (r = 0.65, P < 0.001). Compared with AI (r) (age, P < 0.001; gender, P < 0.001; heart rate, P < 0.001; diastolic blood pressure, P < 0.001; weight, P = 0.001), AI (rd) has fewer confounding factors (age, P < 0.001; gender, P < 0.001). In conclusion, AI (rd) derives performance improvement in assessing arterial stiffness, with a stronger correlation with cfPWV and fewer confounding factors.