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Expert Evaluation of Visual Field Decay in Glaucoma Correlates With the Fast Component of Visual Field Loss
- Source :
- Journal of glaucoma. 26(10)
- Publication Year :
- 2017
-
Abstract
- PURPOSE To compare the assessment of serial visual fields (VFs) based on subjective expert evaluation with the fast and slow VF component rates determined with pointwise exponential regression (PER) and pointwise linear regression (PLR). MATERIALS AND METHODS A total of 5272 VF examinations from 376 eyes diagnosed with open-angle glaucoma were included. Three glaucoma specialists assessed each VF qualitatively to evaluate progression status and the qualitative rate of progression. The rates of VF decay were determined with PER and PLR at each VF location, which were ranked according to the regression coefficient and partitioned into 2 groups (fast and slow). A mean rate for the fast and slow partitions was obtained based on the average of the regression coefficients in each partition. κ-values were used to measure the agreement among the experts and the PER and PLR algorithms. RESULTS The average baseline VF mean deviation for the study sample was -6.6 (±5.9) dB. The agreement of the likelihood of progression among the dichotomized experts' score and PER was moderate (κ=0.41, P
- Subjects :
- medicine.medical_specialty
Vision Disorders
Glaucoma
Exponential regression
Audiology
03 medical and health sciences
0302 clinical medicine
Linear regression
Statistics
Expert evaluation
Medicine
Humans
Aged
Retrospective Studies
business.industry
Regression analysis
Middle Aged
medicine.disease
Visual field
Ophthalmology
030221 ophthalmology & optometry
Disease Progression
Regression Analysis
Visual Field Tests
Component (group theory)
Visual field loss
Visual Fields
business
030217 neurology & neurosurgery
Algorithms
Glaucoma, Open-Angle
Follow-Up Studies
Subjects
Details
- ISSN :
- 1536481X
- Volume :
- 26
- Issue :
- 10
- Database :
- OpenAIRE
- Journal :
- Journal of glaucoma
- Accession number :
- edsair.doi.dedup.....0a5cc2737f2c6438a1cfa0c08d793f5c