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Associated Factors and Distribution of Peripapillary Retinal Nerve Fiber Layer Thickness in Children by Optical Coherence Tomography: A Population-Based Study Publisher Pubmed



Hashemi H1 ; Khabazkhoob M2 ; Heydarian S4 ; Emamian MH5 ; Fotouhi A3
Authors
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Authors Affiliations
  1. 1. Noor Research Center for Ophthalmic Epidemiology, Noor Eye Hospital, Iran
  2. 2. Department of Medical Surgical Nursing, School of Nursing and Midwifery, Shahid Beheshti University of Medical Sciences, Iran
  3. 3. Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. Department of Rehabilitation Science, School of Allied Medical Sciences, Mazandaran University of Medical Sciences, Sari, Iran
  5. 5. Ophthalmic Epidemiology Research Center, Shahroud University of Medical Sciences, Shahroud, Iran

Source: Journal of Glaucoma Published:2022


Abstract

Purpose: To determine the distribution of peripapillary retinal nerve fiber layer (RNFL) thickness and its association with different demographic and ocular parameters in adolescents. Methods: The present study is part of the second phase of the Shahroud Schoolchildren Eye cohort study, which was conducted in 2018 by reinviting the participants in the first phase. First, preliminary ocular examinations were performed, including measurement of uncorrected and best-corrected visual acuity, autorefraction, and subjective refraction. All study participants underwent corneal imaging using Pentacam to measure central corneal thickness and corneal radius of curvature (keratometry), ocular biometry using Allegro Biograph to measure anterior chamber depth, crystalline lens thickness, and axial length (AL), and finally optical coherence tomography imaging to measure RNFL thickness as well as macular thickness and volume. Results: The data of 4963 right eyes were analyzed after applying the exclusion criteria. The mean age of the study participants was 12.41±1.72 (9 to 15) years. The mean total, superior, inferior, temporal, and nasal RNFL thicknesses were 98.93 [95% confidence interval (CI): 98.61-99.25], 122.84 (95% CI: 122.31-123.37), 129.17 (95% CI: 128.63-129.7), 68.02 (95% CI: 67.65-68.38), and 75.69 (95% CI: 75.3-76.07), respectively. According to the results of the multivariable regression model, macular volume (β=9.81, P=0.001) had a significant direct association, and macular thickness (β=-0.01, P=0.046) had a significant inverse association with the average RNFL thickness. In addition, AL (β=-3.14, P<0.001), mean keratometry (β=-1.38, P<0.001), and central corneal thickness (β=-0.01, P=0.011) were significantly inversely related to the average RNFL thickness. Conclusion: We report the distribution of peripapillary RNFL thickness using spectral-domain optical coherence tomography and identify macular volume, AL, and mean keratometry as significantly associated factors in children. Our findings may serve as a database to interpret RNFL thickness results in children aged 9 to 15 years with suspected ocular disease. © 2022 Lippincott Williams and Wilkins. All rights reserved.