Yadav Ravi K, Begum Viquar U, Addepalli Uday K, Senthil Sirisha, Garudadri Chandra S, Rao Harsha L
*VST Glaucoma Center †Center for Clinical Epidemiology and Biostatistics, L V Prasad Eye Institute, Banjara Hills, Hyderabad, India.
J Glaucoma. 2016 Feb;25(2):e87-93. doi: 10.1097/IJG.0000000000000267.
To compare the abilities of retinal nerve fiber layer (RNFL) parameters of variable corneal compensation (VCC) and enhanced corneal compensation (ECC) algorithms of scanning laser polarimetry (GDx) in detecting various severities of glaucoma.
Two hundred and eighty-five eyes of 194 subjects from the Longitudinal Glaucoma Evaluation Study who underwent GDx VCC and ECC imaging were evaluated. Abilities of RNFL parameters of GDx VCC and ECC to diagnose glaucoma were compared using area under receiver operating characteristic curves (AUC), sensitivities at fixed specificities, and likelihood ratios.
After excluding 5 eyes that failed to satisfy manufacturer-recommended quality parameters with ECC and 68 with VCC, 56 eyes of 41 normal subjects and 161 eyes of 121 glaucoma patients [36 eyes with preperimetric glaucoma, 52 eyes with early (MD>-6 dB), 34 with moderate (MD between -6 and -12 dB), and 39 with severe glaucoma (MD<-12 dB)] were included for the analysis. Inferior RNFL, average RNFL, and nerve fiber indicator parameters showed the best AUCs and sensitivities both with GDx VCC and ECC in diagnosing all severities of glaucoma. AUCs and sensitivities of all RNFL parameters were comparable between the VCC and ECC algorithms (P>0.20 for all comparisons). Likelihood ratios associated with the diagnostic categorization of RNFL parameters were comparable between the VCC and ECC algorithms.
In scans satisfying the manufacturer-recommended quality parameters, which were significantly greater with ECC than VCC algorithm, diagnostic abilities of GDx ECC and VCC in glaucoma were similar.
比较扫描激光偏振仪(GDx)的可变角膜补偿(VCC)算法和增强角膜补偿(ECC)算法的视网膜神经纤维层(RNFL)参数检测不同严重程度青光眼的能力。
对纵向青光眼评估研究中194名受试者的285只眼睛进行了GDx VCC和ECC成像评估。使用受试者操作特征曲线下面积(AUC)、固定特异性下的敏感性和似然比比较GDx VCC和ECC的RNFL参数诊断青光眼的能力。
排除5只ECC和68只VCC未满足制造商推荐质量参数的眼睛后,纳入41名正常受试者的56只眼睛和121名青光眼患者的161只眼睛[36只视野前青光眼、52只早期(平均偏差>-6 dB)、34只中度(平均偏差在-6至-12 dB之间)和39只重度青光眼(平均偏差<-12 dB)]进行分析。下象限RNFL、平均RNFL和神经纤维指标参数在GDx VCC和ECC诊断所有严重程度青光眼时均显示出最佳的AUC和敏感性。VCC和ECC算法之间所有RNFL参数的AUC和敏感性相当(所有比较P>0.20)。VCC和ECC算法之间与RNFL参数诊断分类相关的似然比相当。
在满足制造商推荐质量参数的扫描中,ECC算法显著多于VCC算法,GDx ECC和VCC在青光眼诊断中的能力相似。