Visual sensitivity is comprehensively described by the contrast sensitivity function (CSF), but current routine clinical care does not include its assessment because of the time-consuming need to estimate thresholds for a large number of spatial frequencies. The quick CSF method, however, dramatically reduces testing times by using a Bayesian information maximization rule. We evaluate the test-retest variability of a tablet-based quick CSF implementation in a study with 100 subjects who repeatedly assessed their vision with and without optical correction. We first discuss two commonly used measures of repeatability, intraclass correlation and the Bland-Altman Coefficient of Repeatability, and show that they are vulnerable to artifacts. Instead, we propose to formulate precision as an information retrieval task: from all repeat test scores, can we retrieve a certain individual based on their first test score? We then use rank-based analyses such as mean average precision as a better measure to compare different test metrics, and show that the highest test-retest precision is achieved using a summary statistic, the area under the log CSF (AULCSF). This demonstrates the benefit of assessment of the whole CSF compared to sensitivity at individual spatial frequencies only. AULCSF also yields best discrimination performance (99.2%) between measurements that were taken with and without glasses, respectively, even better than CSF Acuity. The tablet-based quick CSF thus enables the rapid and reliable home monitoring of visual function, which has the potential to improve early diagnosis and treatment of ophthalmic pathologies such as diabetic retinopathy or age-related macular degeneration.

译文

:视觉敏感度由对比敏感度功能(CSF)进行了全面描述,但是当前的常规临床护理不包括其评估,因为需要花费大量时间来估计大量空间频率的阈值。但是,快速的CSF方法通过使用贝叶斯信息最大化规则大大减少了测试时间。我们在一项包含100名受试者的研究中评估了基于平板电脑的快速CSF实施的重测变异性,这些受试者在有无光学矫正的情况下反复评估其视力。我们首先讨论两种可重复性的常用度量,类内相关性和可重复性的Bland-Altman系数,并表明它们易受伪影的影响。相反,我们建议将精确度公式化为信息检索任务:从所有重复的测试成绩中,我们是否可以根据他们的第一个测试成绩来检索某个人?然后,我们使用基于等级的分析(例如平均平均精度)作为比较不同测试指标的更好方法,并显示使用汇总统计量(对数CSF下的面积(AULCSF))可以实现最高的重测精度。与仅在单个空间频率下的灵敏度相比,这证明了评估整个CSF的益处。在分别戴有眼镜和不戴眼镜的情况下,AULCSF还可产生最佳的辨别性能(99.2%),甚至优于CSF Acuity。因此,基于平板电脑的快速CSF可以实现对视觉功能的快速可靠的家庭监控,具有改善早期诊断和治疗眼科疾病(如糖尿病性视网膜病或年龄相关性黄斑变性)的潜力。

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