Kumar P Praveen, Shajahan T, Hussaindeen Jameel Rizwana
Binocular Vision and Vision Therapy Clinic, Sankara Nethralaya, Chennai, Tamil Nadu, India.
Srimathi Sundari Subramanian Department of Visual Psychophysics, Units of Medical Research Foundation, Nungambakkam, Chennai, Tamil Nadu, India.
Oman J Ophthalmol. 2022 Jun 29;15(2):163-167. doi: 10.4103/ojo.ojo_460_20. eCollection 2022 May-Aug.
The increased prevalence of nonstrabismic binocular vision anomalies (NSBVA) has given rise to the need for cost-effective screening and diagnostic tools.
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 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.
Receiver operating characteristic (ROC) curves were utilized to choose the cut-off points that maximize the sensitivity and specificity.
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 ( < 0.05).
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.
非斜视性双眼视觉异常（NSBVA）患病率的增加引发了对具有成本效益的筛查和诊断工具的需求。
本研究的目的是评估一种自主研发的基于计算机的双眼视觉评估软件（“训练你的眼睛”®）在筛查NSBVA方面的有效性。
纳入2019年1月至2020年1月期间因视疲劳症状前往三级眼科护理中心双眼视觉门诊就诊的受试者。排除患有其他眼部合并症以及立体视锐度低于500角秒的患者。所有受试者均接受了全面的眼科检查，随后使用手动和基于计算机的方法进行双眼视觉评估。
采用受试者工作特征（ROC）曲线来选择能使灵敏度和特异性最大化的截断点。
88名受试者的平均（标准差）年龄为22（4.5）岁，其中男性34名。基于传统的手动评估，71名（81%）被诊断为患有NSBVA，17名（19%）双眼视觉正常。基于ROC分析，提出以下截断点：近距正融像性聚散幅度为14棱镜度（PD），近距负融像性聚散幅度为4.5 PD，双眼调节灵活度为4.5周/分钟（cpm），单眼调节灵活度为3.5 cpm。所有双眼视觉参数在ROC分析中均具有统计学意义（<0.05）。
基于软件的筛查工具在识别NSBVA方面具有高度敏感性，因此可作为临床和社区潜在的筛查工具。
