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Related Concept Videos

Glaucoma: Overview01:25

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Glaucoma is an eye condition characterized by increased intraocular pressure that damages the retina and optic nerve, leading to irreversible blindness if left untreated. The human eye has various components, including the cornea, iris, pupil, lens, and optic nerve. Aqueous humor is secreted by the epithelium of the ciliary body in the posterior chamber and flows through the trabecular meshwork and canal of Schlemm, maintaining normal intraocular pressure. The trabecular meshwork and the canal...
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Open Angle Glaucoma: Treatment01:27

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In open-angle glaucoma, the iridocorneal angle remains open, but the trabecular meshwork becomes stiff, slowing down the outflow of aqueous humor. This causes a buildup of aqueous humor in the anterior chamber, leading to a sudden increase in intraocular pressure. The treatment for open-angle glaucoma focuses on reducing the elevated intraocular pressure by either decreasing the secretion of aqueous humor or increasing its outflow.
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Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential
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Quantification of Visual Field Variability in Glaucoma: Implications for Visual Field Prediction and Modeling.

Alessandro Rabiolo1,2, Esteban Morales1, Abdelmonem A Afifi3

  • 1Stein Eye Institute, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.

Translational Vision Science & Technology
|October 23, 2019
PubMed
Summary
This summary is machine-generated.

Visual field variability in glaucoma increases with disease severity and decreases with eccentricity. Pointwise exponential regression (PER) best predicts future sensitivity, outperforming linear models.

Keywords:
heteroscedasticityperimetrypointwise exponential regressionpredictionregression modelingvisual field progressionweighted linear regression

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Area of Science:

  • Ophthalmology
  • Glaucoma Research
  • Visual Field Analysis

Background:

  • Visual field (VF) variability is a critical factor in glaucoma diagnosis and progression monitoring.
  • Understanding VF variability's relationship with sensitivity and location is essential for accurate modeling.
  • Existing regression models may not fully capture the complex nature of VF changes over time.

Purpose of the Study:

  • To quantify visual field (VF) variability based on threshold sensitivity and location in glaucoma patients.
  • To compare the data fit and prediction capabilities of weighted pointwise linear regression (PLR), unweighted PLR, and pointwise exponential regression (PER).

Main Methods:

  • Retrospective analysis of two glaucoma patient datasets with extensive visual field testing and follow-up.
  • Characterization of VF variability using standard deviation of residuals from PER.
  • Comparison of unweighted PLR, weighted PLR, and PER for model fit and prediction accuracy.

Main Results:

  • VF variability exhibited a zenith at 33 dB and a nadir at 11 dB of threshold sensitivity.
  • Variability decreased with eccentricity, being significantly higher in the central 10° (P < 0.001).
  • Pointwise exponential regression (PER) demonstrated superior ability in predicting future visual field sensitivity in the mid-to-long term.

Conclusions:

  • Glaucomatous visual field variability is influenced by disease severity and retinal location.
  • Weighted linear regression offers no significant advantage over unweighted models for VF data fit or prediction.
  • PER's superior predictive performance is attributed to its ability to model the nonlinear decay characteristic of long-term glaucomatous perimetric progression.