青光眼诊所患者中通过计算得出的视野缺损原型的临床关联
Clinical Correlates of Computationally Derived Visual Field Defect Archetypes in Patients from a Glaucoma Clinic.
作者信息
Cai Sophie, Elze Tobias, Bex Peter J, Wiggs Janey L, Pasquale Louis R, Shen Lucy Q
机构信息
a Department of Ophthalmology , Harvard Medical School, Massachusetts Eye and Ear , Boston , MA , USA.
b Department of Ophthalmology, Harvard Medical School , Schepens Eye Research Institute , Boston , MA , USA.
出版信息
Curr Eye Res. 2017 Apr;42(4):568-574. doi: 10.1080/02713683.2016.1205630. Epub 2016 Aug 5.
PURPOSE
To assess the clinical validity of visual field (VF) archetypal analysis, a previously developed machine learning method for decomposing any Humphrey VF (24-2) into a weighted sum of clinically recognizable VF loss patterns.
MATERIALS AND METHODS
For each of 16 previously identified VF loss patterns ("archetypes," denoted AT1 through AT16), we screened 30,995 reliable VFs to select 10-20 representative patients whose VFs had the highest decomposition coefficients for each archetype. VF global indices and patient ocular and demographic features were extracted retrospectively. Based on resemblances between VF archetypes and clinically observed VF patterns, hypotheses were generated for associations between certain VF archetypes and clinical features, such as an association between AT6 (central island, representing severe VF loss) and large cup-to-disk ratio (CDR). Distributions of the selected clinical features were compared between representative eyes of certain archetypes and all other eyes using the two-tailed t-test or Fisher exact test.
RESULTS
243 eyes from 243 patients were included, representative of AT1 through AT16. CDR was more often ≥ 0.7 among eyes representative of AT6 (central island; p = 0.002), AT10 (inferior arcuate defect; p = 0.048), AT14 (superior paracentral defect; p = 0.016), and AT16 (inferior paracentral defect; p = 0.016) than other eyes. CDR was more often < 0.7 among eyes representative of AT1 (no focal defect; p < 0.001) and AT2 (superior defect; p = 0.027), which was also associated with ptosis (p < 0.001). AT12 (temporal hemianopia) was associated with history of stroke (p = 0.022). AT11 (concentric peripheral defect) trended toward association with trial lens correction > 6D (p = 0.069).
CONCLUSIONS
Shared clinical features between computationally derived VF archetypes and clinically observed VF patterns support the clinical validity of VF archetypal analysis.
目的
评估视野（VF）原型分析的临床有效性，这是一种先前开发的机器学习方法，可将任何汉弗莱视野（24-2）分解为临床可识别的视野损失模式的加权和。
材料与方法
对于之前确定的16种视野损失模式（“原型”，表示为AT1至AT16）中的每一种，我们筛选了30995个可靠的视野，以选择10-20名代表性患者，其视野对于每种原型具有最高的分解系数。回顾性提取视野全局指数以及患者的眼部和人口统计学特征。基于视野原型与临床观察到的视野模式之间的相似性，提出了某些视野原型与临床特征之间关联的假设，例如AT6（中央岛，代表严重视野损失）与大杯盘比（CDR）之间的关联。使用双尾t检验或Fisher精确检验比较某些原型的代表性眼睛与所有其他眼睛之间所选临床特征的分布。
结果
纳入了243例患者的243只眼睛，代表AT1至AT16。在代表AT6（中央岛；p = 0.002）、AT10（下方弓形缺损；p = 0.048）、AT14（上方旁中心缺损；p = 0.016）和AT16（下方旁中心缺损；p = 0.016）的眼睛中，CDR≥0.7的情况比其他眼睛更常见。在代表AT1（无局灶性缺损；p < 0.001）和AT2（上方缺损；p = 0.027）的眼睛中，CDR<0.7的情况更常见，这也与上睑下垂相关（p < 0.001）。AT12（颞侧偏盲）与中风病史相关（p = 0.022）。AT11（同心周边缺损）倾向于与试验镜片矫正>6D相关（p = 0.069）。
结论
通过计算得出的视野原型与临床观察到的视野模式之间的共同临床特征支持视野原型分析的临床有效性。
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