Elsevier

Ophthalmology

Volume 119, Issue 2, February 2012, Pages 278-282
Ophthalmology

Original article
Determinants of Angle Width in Chinese Singaporeans

https://doi.org/10.1016/j.ophtha.2011.07.049Get rights and content

Purpose

To investigate determinants of angle width and derive mathematic models to best predict angle width.

Design

Population-based, cross-sectional study.

Participants

A total of 1067 Chinese subjects aged ≥40 years.

Methods

Participants underwent gonioscopy, A-scan biometry, and imaging by anterior segment optical coherence tomography (ASOCT, Carl Zeiss Meditec, Dublin, CA). Customized software (Zhongshan Angle Assessment Program, Guangzhou, China) was used to measure ASOCT parameters. Linear regression modeling was performed with trabecular–iris space area at 750 μm (TISA750) and angle opening distance at 750 μm (AOD750) from the scleral spur as the 2 dependent angle width variables. By using a combination of ASOCT and biometric parameters, an optimal model that was predictive of angle width was determined by a forward selection regression algorithm. Validation of the results was performed in a separate set of community-based clinic study of 1293 persons aged ≥50 years.

Main Outcome Measures

Angle width and biometric parameters.

Results

The mean age (standard deviation) of the population-based subjects was 56.9 (8.5) years, and 50.2% were male. For TISA750, the strongest determinants among ASOCT and A-scan independent variables were anterior chamber volume (ACV, R2=0.51), followed by anterior chamber area (ACA, R2=0.49) and lens vault (LV, R2=0.47); for AOD750, these were LV (R2=0.56), ACA (R2=0.55), and ACV (R2=0.54). The R2 values for anterior chamber depth and axial length were 0.39 and 0.27 for TISA750, respectively, and 0.46 and 0.30 for AOD750, respectively. An optimal model consisting of 6 variables (ACV, ACA, LV, anterior chamber width [ACW], iris thickness at 750 μm, and iris area) explained 81.4% of the variability in TISA750 and 85.5% of the variability in AOD750. The results of the population-based study were validated in the community-based clinic study, where the strongest determinants of angle width (ACA, ACV, and LV) and the optimal model with 6 variables were similar.

Conclusions

Angle width is largely dependent on variations in ACA, ACV, and LV. A predictive model comprising 6 quantitative ASOCT parameters explained more than 80% of the variability of angle width and may have implications for screening for angle closure.

Financial Disclosure(s)

Proprietary or commercial disclosure may be found after the references.

Section snippets

Materials and Methods

Approval for the study was granted by the Singapore Eye Research Institute institutional review board. This study was conducted in accordance with the Declaration of Helsinki, and written informed consent was obtained from all subjects before enrollment.

The primary population consists of subjects recruited from an ongoing population-based cross-sectional study of Chinese persons aged ≥40 years (the Singapore Chinese Eye Study). The study methodology and details of the study population have been

Statistical Analysis

For the primary population, linear regression modeling using the R2 best subsets selection method was performed with TISA750 and AOD750 as the dependent angle width variables. This method finds subsets of independent variables that best predict a dependent variable by linear regression and display the models in decreasing order of R2 magnitude within each subset size. R2 is a descriptive measure between 0 and 1 indicating how well one term predicts another, with perfect prediction when R2=1.

Results

For the primary population-based study, complete data for analysis were available for 1547 subjects. Among them, 480 subjects were excluded from analysis for the following reasons: a history of intraocular surgery in 29, indeterminate sclera spurs in 279, poor-quality ASOCT images in 70, and Zhongshan Angle Assessment Program software delineation errors in 102. Final analysis was thus performed on 1067 subjects. The mean age of the subjects was 56.9±8.5 years, and 49.8% were female. There was

Discussion

The current analysis supports defining angle closure as a multifactorial condition that can be caused by either one or a combination of variations in size, shape, and position of anterior segment structures. By incorporating all the established and newly identified anatomic factors for angle closure,1, 2, 3, 4, 11, 12, 13, 14 we found that ACA, ACV, and LV were the 3 most important determinants of angle width, the pathogenic site of PACG. A predictive model comprising 6 quantitative ASOCT

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    • Ocular Biometric Determinants of Anterior Chamber Angle Width in Chinese Americans: The Chinese American Eye Study

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      These findings support mathematical models that predict a significant increase in IC secondary to pupillary block, which plays a key role in the pathogenesis of primary angle closure.28 The results of our univariate analyses are consistent with results from the population-based study of Chinese Singaporeans by Foo and associates.21 Ignoring anterior chamber area and anterior chamber volume, which were omitted from our study for the aforementioned reasons, the R2 values for the 4 strongest determinants of AOD750 were LV (0.56), ACD (0.46), IC (0.48) and AL (0.30).

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    Manuscript no. 2011-384.

    Financial Disclosure(s): The author(s) have made the following disclosure(s): Dr. T. Aung has received research funding, travel support, and honoraria from Carl Zeiss Meditec. Dr. Wong has received research funding from Carl Zeiss Meditec. Dr. Friedman has received an instrument loan from Carl Zeiss Meditec.

    Funding: Grants from the National Medical Research Council, Singapore, and the National Research Foundation, Singapore.

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