Investigative Ophthalmology & Visual Science Cover Image for Volume 61, Issue 7
June 2020
Volume 61, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2020
The ability to predict Visual Field damage using patient reported symptoms
Author Affiliations & Notes
  • Yesha Shah
    Wilmer Eye Institute, Johns Hopkins SOM, Maryland, United States
  • Michael Cheng
    Wilmer Eye Institute, Johns Hopkins SOM, Maryland, United States
  • Aleksandra Mihailovic
    Wilmer Eye Institute, Johns Hopkins SOM, Maryland, United States
  • Pradeep Y Ramulu
    Wilmer Eye Institute, Johns Hopkins SOM, Maryland, United States
  • Footnotes
    Commercial Relationships   Yesha Shah, None; Michael Cheng, None; Aleksandra Mihailovic, None; Pradeep Ramulu, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 1974. doi:
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      Yesha Shah, Michael Cheng, Aleksandra Mihailovic, Pradeep Y Ramulu; The ability to predict Visual Field damage using patient reported symptoms. Invest. Ophthalmol. Vis. Sci. 2020;61(7):1974.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Currently, glaucoma severity is characterized through testing, i.e. optic nerve findings, Optical Coherence Tomography (OCT), or Visual Field (VF) assessment. In practice, a useful adjunct to these tests is discussion of patient symptoms, though the ability of symptom-related questions to predict severity is unknown. Here, we evaluate which questions best capture glaucoma severity, and determine, using VF damage as the gold standard, to what extent symptoms can capture disease severity.

Methods : Patients in two groups (diagnosed glaucoma with VF mean deviation [MD] worse than -5 dB in both eyes and suspected glaucoma with VF MD better than -4 dB in both eyes) graded the presence and severity of 30 visual symptoms. Univariate and multiple linear regression models evaluated the amount of variance (adjusted R2) in VF MD explained by patient reported symptoms or, for comparison purposes, OCT total retinal nerve fiber layer (RNFL) thickness. Multiple models controlled for age, sex, race, and education.

Results : A total of 177 patients were recruited (81 with glaucoma and 96 with suspected glaucoma). Mean age was 65 years and 58% were female. Among glaucoma patients, the most commonly reported symptoms were having better vision in one eye (n=72), blurry vision (n=62), and glare (n=54). In univariate analysis, severity of two symptoms, better vision in one eye and peripheral loss, explained 33% and 34% of variance in VF damage, respectively, while the frequency of the following five symptoms: objects looking different sizes with each eye, missing patches, cloudy vision, weekly vision variance, and glare explained 33%, 32%, 26%, 19%, and 6% of the variance in VF damage respectively. A multiple linear regression model including the above seven symptoms explained 52% of the variance in VF damage, while a multiple linear regression model including total RNFL thickness explained only 37% of the variance in VF damage.

Conclusions : Patient reported symptoms explained a significant amount of variance in VF damage, outperforming RNFL thickness, a commonly used glaucoma tool. In glaucoma, patient communication with specific terms may be useful in staging disease and can complement clinical testing. Communication may be particularly useful in judging disease severity in patients where traditional testing is difficult to obtain.

This is a 2020 ARVO Annual Meeting abstract.

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