Oman Journal of Ophthalmology (Jan 2022)

Diagnostic accuracy of indigenously developed computer-based binocular vision assessment

  • P Praveen Kumar,
  • T Shajahan,
  • Jameel Rizwana Hussaindeen

DOI
https://doi.org/10.4103/ojo.ojo_460_20
Journal volume & issue
Vol. 15, no. 2
pp. 163 – 167

Abstract

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CONTEXT: The increased prevalence of nonstrabismic binocular vision anomalies (NSBVA) has given rise to the need for cost-effective screening and diagnostic tools. AIMS: The aim of the study is to assess the efficacy of an indigenously developed computer-based binocular vision assessment software (Train Your Eyes®) in screening NSBVA. SUBJECTS AND METHODS: Subjects who visited the binocular vision clinic of a tertiary eye care center with asthenopic symptoms between January 2019 and January 2020 were included in the study. Patients with other ocular comorbidities and stereopsis poorer than 500 arc seconds were excluded. All subjects underwent a comprehensive eye examination followed by binocular vision assessment using both the manual and computer-based methods. STATISTICAL ANALYSIS USED: Receiver operating characteristic (ROC) curves were utilized to choose the cut-off points that maximize the sensitivity and specificity. RESULTS: The mean (standard deviation) age of 88 subjects was 22 (4.5) years with 34 males. Based on the conventional manual assessment, 71 (81%) were diagnosed to have NSBVA and 17 (19%) had normal binocular vision. Based on the ROC analysis, the following cut-off points are proposed: 14 prism diopter (PD) for near positive fusional vergence amplitudes, 4.5 PD for near negative fusional vergence amplitudes, 4.5 cycles per minute (cpm) for binocular accommodative facility, and 3.5 cpm for monocular accommodative facility. All the binocular vision parameters demonstrated statistical significance in the ROC analysis (P < 0.05). CONCLUSIONS: The software-based screening tool was found to be highly sensitive in identifying NSBVA and thus could be used as a potential screening tool in the clinic and community.

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