Nelson-Quigg J M, Cello K, Johnson C A
Department of Ophthalmology, University of California, Davis, USA.
Invest Ophthalmol Vis Sci. 2000 Jul;41(8):2212-21.
To compare methods of predicting binocular visual field sensitivity of patients with glaucoma from monocular visual field data.
Monocular and binocular visual fields were obtained for 111 patients with varying degrees of glaucomatous damage in one or both eyes, using the Humphrey 30-2 full-threshold procedure. Four binocular sensitivity prediction models were evaluated: BEST EYE, predictions based on individual values for the most sensitive eye, defined by mean deviation (MD); AVERAGE EYE, predictions based on the average sensitivity between eyes at each visual field location; BEST LOCATION, predictions based on the highest sensitivity between eyes at each visual field location; and BINOCUIAR SUMMATION, predictions based on binocular summation of sensitivity between eyes at each location. Differences between actual and predicted binocular sensitivities were calculated for each model.
The average difference between predicted and actual binocular sensitivities was close to zero for the BINOCULAR SUMMATION and BEST LOCATION models, with 95% of all predictions being within +/-3 dB of actual binocular sensitivities. The best eye (MD) prediction had an average error of 1.5 dB (95% confidence limits [CL], +/-3.7 dB). The average eye prediction was the poorest, with an average error of 3.7 dB (95% CL, +/-4.6 dB).
The BINOCULAR SUMMATION and BEST LOCATION models provided better predictions of binocular visual field sensitivity than the other two models, with a statistically significant difference in performance. The small difference in performance between the BINOCULAR SUMMATION and BEST LOCATION models was not statistically significant. For evaluations of functional visual field influences on task performance, daily activities, and related quality-of-life issues, either the BINOCULAR SUMMATION or BEST LOCATION model provides good estimates of binocular visual field sensitivity.
比较从单眼视野数据预测青光眼患者双眼视野敏感度的方法。
对111例一只或两只眼睛有不同程度青光眼损害的患者，采用汉弗莱30 - 2全阈值程序获取单眼和双眼视野。评估了四种双眼敏感度预测模型：最佳眼，基于最敏感眼的个体值（由平均偏差[MD]定义）进行预测；平均眼，基于每个视野位置两眼之间的平均敏感度进行预测；最佳位置，基于每个视野位置两眼之间的最高敏感度进行预测；以及双眼总和，基于每个位置两眼之间敏感度的双眼总和进行预测。计算每个模型预测的双眼敏感度与实际双眼敏感度之间的差异。
双眼总和模型和最佳位置模型预测的与实际双眼敏感度之间的平均差异接近零，所有预测中有95%在实际双眼敏感度的±3 dB范围内。最佳眼（MD）预测的平均误差为1.5 dB（95%置信限[CL]，±3.7 dB）。平均眼预测最差，平均误差为3.7 dB（95% CL，±4.6 dB）。
双眼总和模型和最佳位置模型比其他两个模型能更好地预测双眼视野敏感度，在性能上有统计学显著差异。双眼总和模型和最佳位置模型在性能上的微小差异无统计学意义。对于评估功能性视野对任务表现、日常活动及相关生活质量问题的影响，双眼总和模型或最佳位置模型均可对双眼视野敏感度提供良好估计。
