Safwat Hend, Nassar Elaraby, Rashwan Afaf
Department of Ophthalmology, Faculty of Medicine for Girls, Al-Azhar University, Cairo, Egypt.
Department of Ophthalmology, Faculty of Medicine, Al-Azhar University, Cairo, Egypt.
J Curr Glaucoma Pract. 2020 Jan-Apr;14(1):16-24. doi: 10.5005/jp-journals-10078-1271.
To develop a new structural algorithm derived from optical coherence tomography (OCT) retinal nerve fiber layer (RNFL) thickness and asymmetry and validate it as a discriminate among normal, suspect, and early primary open-angle glaucoma (POAG).
A case-controlled observational clinical study.
In total, 150 subjects (299 eyes) were selected, 61 normal, 46 suspect, and 43 early glaucoma, from Al-Azhar University Hospitals. They were in fifth decade and free from any ocular or systemic diseases affecting the retinal nerve fiber layer. They were investigated by two consecutive perimetry (1 month apart), and three scans of circumpapillary retinal nerve fiber layer (cpRNFL) by using Nidek spectral domain (SD)-OCT 3000 Lite. The cpRNFL thickness (cpRNFLT) and inter-eye asymmetry parameters were analyzed among the three groups. Then some selected parameters were selected and analyzed using a binary logistic regression analysis for developing the new algorithm. The new algorithm was tested for the best fitting, accuracy, and diagnostic ability among the three groups and was validated in the suspect group.
The new algorithm model [early glaucoma discrimination index (EGDI)] works well with only four variables; whole cpRNFLT, inferior quadrant cpRNFLT, inferotemporal clock hour (CH) cpRNFLT, and absolute inter-eye inferior quadrants asymmetry. The highest area under the curve (AUC) obtained from the EGDI among the three groups was 0.854. The validation analysis in the suspect group revealed a higher diagnostic ability in discrimination of early glaucoma with AUC of 0.989 (0.976-1.003).
The EGDI showed better diagnostic ability for diagnosis of glaucoma in the pre-perimetric stage. The new OCT algorithm is simple and can be run in any SD-OCT device without dependence on normative data.
Safwat H, Nassar E, Rashwan A. Early Glaucoma Discrimination Index. J Curr Glaucoma Pract 2020;14(1):16-24.
开发一种基于光学相干断层扫描（OCT）视网膜神经纤维层（RNFL）厚度及不对称性的新结构算法，并验证其在正常、可疑及早期原发性开角型青光眼（POAG）鉴别中的作用。
病例对照观察性临床研究。
从爱资哈尔大学医院选取150名受试者（299只眼），其中61名正常受试者、46名可疑受试者和43名早期青光眼患者。他们年龄在五十岁左右，无任何影响视网膜神经纤维层的眼部或全身性疾病。对他们进行连续两次视野检查（间隔1个月），并使用尼德克光谱域（SD）-OCT 3000 Lite对视乳头周围视网膜神经纤维层（cpRNFL）进行三次扫描。分析三组之间的cpRNFL厚度（cpRNFLT）和双眼不对称参数。然后选择一些参数并使用二元逻辑回归分析来开发新算法。对新算法在三组中的最佳拟合度、准确性和诊断能力进行测试，并在可疑组中进行验证。
新算法模型[早期青光眼鉴别指数（EGDI）]仅用四个变量就能很好地发挥作用；整个cpRNFLT、下象限cpRNFLT、颞下钟点（CH）cpRNFLT和双眼下象限绝对不对称性。三组中EGDI获得的最高曲线下面积（AUC）为0.854。可疑组的验证分析显示，在鉴别早期青光眼方面具有更高的诊断能力，AUC为0.989（0.976 - 1.003）。
EGDI在青光眼视野检查前期诊断中显示出更好的诊断能力。新的OCT算法简单，可在任何SD - OCT设备上运行，无需依赖标准数据。
Safwat H, Nassar E, Rashwan A. Early Glaucoma Discrimination Index. J Curr Glaucoma Pract 2020;14(1):16 - 24.
