The DOI matches its Crossref record.
Effect of Myopia on the Thickness of the Retinal Nerve Fiber Layer Measured by Cirrus HD Optical Coherence Tomography
Abstract
PURPOSE: To evaluate the effect of myopia on the peripapillary retinal nerve fiber layer (RNFL) thickness measured by Cirrus HD optical coherence tomography (OCT). METHODS: Comprehensive ophthalmic examinations were performed, including measurement of visual acuity, refraction, and axial length on 269 subjects (age, 19-26 years) with no ophthalmic abnormality. Further, 200 x 200-cube optic disc scans of the subjects' eyes were obtained with Cirrus HD OCT. The RNFL thickness at 256 points of the RNFL thickness profile and the average RNFL thickness were recorded. The correlations between these values and the axial length and spherical equivalent (SE) of refractive errors were then analyzed by simple linear regression, before and after adjustment of the ocular magnification. RESULTS: Before ocular magnification adjustment, the uncorrected average RNFL thickness decreased as the axial length increased and as the SE decreased. However, after the adjustment, the corrected average RNFL thickness exhibited no correlation with the spherical equivalent and a weak positive correlation with the axial length. Myopia also affected the RNFL thickness distribution. As the axial length increased and the spherical equivalent decreased, the thickness of the temporal peripapillary RNFL increased and that of the superior, superior nasal, inferior, and inferior nasal peripapillary RNFL decreased. CONCLUSIONS: The axial length affected the average RNFL thickness, and myopia affected the RNFL thickness distribution. High myopes are likely to exhibit different RNFL distribution patterns. Since ocular magnification significantly affects the RNFL measurement in such patients, it should be considered in diagnosing glaucoma.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Retinal Nerve Fiber Layer Imaging with Spectral-Domain Optical Coherence Tomography
Leung, C. K.-S., Cheung, C. Y.-L., Weinreb, R. N., Qiu, Q., Liu, S., Li, H., Xu, G., Fan, N., Huang, L., Pang, C.-P., et al. (2009) · Ophthalmology · doi:10.1016/j.ophtha.2009.04.013 · Cited by 486
Mwanza, J.-C., Durbin, M. K., Budenz, D. L., Girkin, C. A., Leung, C. K., Liebmann, J. M., Peace, J. H., Werner, J. S., & Wollstein, G. (2011) · Investigative Opthalmology & Visual Science · doi:10.1167/iovs.11-7896 · Cited by 275
Development of machine learning models for diagnosis of glaucoma
Kim, S. J., Cho, K. J., & Oh, S. (2017) · PLOS ONE · doi:10.1371/journal.pone.0177726 · Cited by 266
Salehi, M. A., Nowroozi, A., Gouravani, M., Mohammadi, S., & Arevalo, J. F. (2022) · Survey of Ophthalmology · doi:10.1016/j.survophthal.2021.07.007 · Cited by 46
Metadata
- Authors
- Kang, S. H., Hong, S. W., Im, S. K., Lee, S. H., & Ahn, M. D.
- Venue
- Investigative Opthalmology & Visual Science
- Published
- 2010-08-01
- Volume
- 51
- Issue
- 8
- Pages
- 4075
- ISSN
- 0146-0404 (ISSN-L)
- 1552-5783
- OpenAlex
- W2015739996
- Cited by
- 401
- References
- 0
- FWCI
- 21.76
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.