Purpose

To determine which patient-reported symptoms best distinguish patients with and without glaucoma and explain the most variance in visual field (VF) damage and to compare the amount of variance that can be explained by symptoms versus retinal nerve fiber layer (RNFL) thickness.

Design

Cross-sectional study.

Participants

Adults diagnosed with glaucoma or suspicion of glaucoma (controls).

Methods

Worse-eye VF damage was defined on the basis of perimetric testing. Thickness of RNFL was defined by OCT imaging. Patients rated their visual symptoms on questions collated from several published questionnaires, rating the frequency and severity of 28 symptoms on a scale of 1 (never/not at all) to 4 (very often/severe). Multivariable regression models identified patient-reported symptoms that contributed the highest variance in VF damage.

Main Outcome Measures

Patient-reported symptoms that explained the most variance in VF damage and amount of variance in VF damage explained by patient-reported symptoms and RNFL.

Results

A total of 170 patients (mean age: 64 years; 58% female; 47% employed) completed testing, including 95 glaucoma suspects and 75 glaucoma patients. In glaucoma patients, median mean deviation of VF damage in the worse eye was −19.3 and ranged from −5.3 to −34.7 decibels. Symptoms more common among glaucoma patients compared with glaucoma suspects included better vision in 1 eye, blurry vision, glare, sensitivity to light, cloudy vision, missing patches of vision, and little peripheral vision. Worse severity ratings for the symptom “little peripheral vision” explained the most variance in VF damage (43%). A multivariable model including the frequency of cloudy vision, severity of having little peripheral vision, missing patches, 1 eye having better vision, and vision worsening, plus sociodemographic features, explained 62% of the variance in VF damage. Comparatively, a multivariable model of worse-eye RNFL thickness and sociodemographic features explained 42% of the variance in VF damage, whereas a model including only sociodemographic features explained 8% of the variance in VF damage.

Conclusions

Five patient-reported symptoms explain a significant amount of the variance in VF damage. Asking patients about their symptoms may optimize patient-physician communication and be a useful adjunct to clinical testing in some patients to estimate disease severity.

中文翻译：

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患者报告的症状表明与青光眼视野损伤的严重程度相关

目的

确定哪些患者报告的症状最能区分青光眼患者和非青光眼患者，并解释视野 (VF) 损伤的最大差异，并比较症状与视网膜神经纤维层 (RNFL) 厚度可以解释的差异量。

设计

横断面研究。

参加者

被诊断患有青光眼或疑似青光眼的成年人（对照）。

方法

更严重的眼睛 VF 损伤是在视野测试的基础上定义的。RNFL 的厚度由 OCT 成像定义。患者根据从几份已发表的问卷中收集的问题对他们的视觉症状进行评分，对 28 种症状的频率和严重程度进行评分，评分范围为 1（从不/根本没有）到 4（非常频繁/严重）。多变量回归模型确定了患者报告的症状，这些症状对 VF 损伤的影响最大。

主要观察指标

患者报告的症状解释了 VF 损伤的最大差异，以及患者报告的症状和 RNFL 解释的 VF 损伤的差异量。

结果

共有 170 名患者（平均年龄：64 岁；58% 为女性；47% 已就业）完成了测试，其中包括 95 名青光眼疑似患者和 75 名青光眼患者。在青光眼患者中，较差眼睛的 VF 损伤的中位数平均偏差为 -19.3，范围为 -5.3 至 -34.7 分贝。与疑似青光眼患者相比，青光眼患者更常见的症状包括一只眼睛的视力更好、视力模糊、眩光、对光敏感、视力混浊、视力缺失和周边视力差。症状“周边视力小”的较差严重程度评级解释了 VF 损伤的最大差异 (43%)。一个多变量模型，包括视力模糊的频率、几乎没有周边视力的严重程度、缺失的斑块、一只眼睛有更好的视力和视力恶化，加上社会人口学特征，解释了 62% 的 VF 损伤差异。相比之下，较差眼睛 RNFL 厚度和社会人口学特征的多变量模型解释了 42% 的 VF 损伤方差，而仅包括社会人口学特征的模型解释了 8% 的 VF 损伤方差。

结论

五种患者报告的症状解释了 VF 损伤的显着差异。向患者询问他们的症状可以优化医患沟通，并成为一些患者进行临床测试以评估疾病严重程度的有用辅助手段。