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Retinal vascular tortuosity, blood pressure, and cardiovascular risk factors.

Publication ,  Journal Article
Cheung, CY-L; Zheng, Y; Hsu, W; Lee, ML; Lau, QP; Mitchell, P; Wang, JJ; Klein, R; Wong, TY
Published in: Ophthalmology
May 2011

OBJECTIVE: To examine the relationship of retinal vascular tortuosity to age, blood pressure, and other cardiovascular risk factors. DESIGN: Population-based, cross-sectional study. PARTICIPANTS: A total of 3280 participants aged 40 to 80 years from the Singapore Malay Eye Study (78.7% response rate). METHODS: Retinal arteriolar and venular (vascular) tortuosity were quantitatively measured from fundus images using a computer-assisted program. Retinal vascular tortuosity was defined as the integral of the curvature square along the path of the vessel, normalized by the total path length. Data on blood pressure and major cardiovascular disease (CVD) risk factors were collected from all participants. MEAN OUTCOME MEASURES: Retinal arteriolar and venular tortuosity. RESULTS: A total of 2915 participants contributed data to this study. The mean (standard deviation) and median were 2.99 (1.40) and 2.73 for retinal arteriolar tortuosity (×10(4)), and 4.64 (2.39) and 4.19 for retinal venular tortuosity (×10(4)), respectively. Retinal venules were significantly more tortuous than retinal arterioles (P<0.001). In multivariable-adjusted linear regression models, less arteriolar tortuosity was independently associated with older age, higher blood pressure, higher body mass index (BMI), and narrower retinal arteriolar caliber (all P<0.05); greater venular tortuosity was independently associated with younger age, higher blood pressure, lower high-density lipoprotein (HDL) cholesterol level, and wider retinal venular caliber (all P<0.05). CONCLUSIONS: Retinal arteriolar tortuosity was associated with older age and higher levels of blood pressure and BMI, whereas venular tortuosity was also associated with lower HDL level. The quantitative assessment of retinal vascular tortuosity from retinal images may provide further information regarding effects of cardiovascular risk factors on the retinal vasculature.

Duke Scholars

Published In

Ophthalmology

DOI

EISSN

1549-4713

Publication Date

May 2011

Volume

118

Issue

5

Start / End Page

812 / 818

Location

United States

Related Subject Headings

  • Urban Population
  • Singapore
  • Risk Factors
  • Retinal Vessels
  • Retinal Diseases
  • Ophthalmology & Optometry
  • Middle Aged
  • Male
  • Image Processing, Computer-Assisted
  • Hypertension
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Cheung, C.-L., Zheng, Y., Hsu, W., Lee, M. L., Lau, Q. P., Mitchell, P., … Wong, T. Y. (2011). Retinal vascular tortuosity, blood pressure, and cardiovascular risk factors. Ophthalmology, 118(5), 812–818. https://doi.org/10.1016/j.ophtha.2010.08.045
Cheung, Carol Yim-Lui, Yingfeng Zheng, Wynne Hsu, Mong Li Lee, Qiangfeng Peter Lau, Paul Mitchell, Jie Jin Wang, Ronald Klein, and Tien Yin Wong. “Retinal vascular tortuosity, blood pressure, and cardiovascular risk factors.Ophthalmology 118, no. 5 (May 2011): 812–18. https://doi.org/10.1016/j.ophtha.2010.08.045.
Cheung CY-L, Zheng Y, Hsu W, Lee ML, Lau QP, Mitchell P, et al. Retinal vascular tortuosity, blood pressure, and cardiovascular risk factors. Ophthalmology. 2011 May;118(5):812–8.
Cheung, Carol Yim-Lui, et al. “Retinal vascular tortuosity, blood pressure, and cardiovascular risk factors.Ophthalmology, vol. 118, no. 5, May 2011, pp. 812–18. Pubmed, doi:10.1016/j.ophtha.2010.08.045.
Cheung CY-L, Zheng Y, Hsu W, Lee ML, Lau QP, Mitchell P, Wang JJ, Klein R, Wong TY. Retinal vascular tortuosity, blood pressure, and cardiovascular risk factors. Ophthalmology. 2011 May;118(5):812–818.
Journal cover image

Published In

Ophthalmology

DOI

EISSN

1549-4713

Publication Date

May 2011

Volume

118

Issue

5

Start / End Page

812 / 818

Location

United States

Related Subject Headings

  • Urban Population
  • Singapore
  • Risk Factors
  • Retinal Vessels
  • Retinal Diseases
  • Ophthalmology & Optometry
  • Middle Aged
  • Male
  • Image Processing, Computer-Assisted
  • Hypertension