Purpose
To develop and validate an associative model using pupillography that
best discriminates those with and without glaucoma.
Design
A prospective case-control study.
Methods
148 patients with glaucoma (mean age 67±11) and 71 controls
(mean age 60±10) were enrolled in a clinical setting. This prototype
pupillometer is designed to record and analyze pupillary responses at
multiple, controlled stimulus intensities, while using varied stimulus
patterns and colors. We evaluated three approaches: 1) comparing the
responses between the two eyes, 2) comparing responses to stimuli between
the superonasal and inferonasal fields within each eye, and 3) calculating
the absolute pupil response of each individual eye. Associative models were
developed using stepwise regression or forward selection with Akaike
information criterion and validated with 5-fold cross validation. We
assessed the associative model using sensitivity, specificity and the area
under the receiver operating characteristic curve (AUROC).
Results
Persons with glaucoma had a more asymmetric pupil response between
the two eyes (p<0.001), between superonasal and
inferonasal visual field within the same eye
(p=0.014), and also had a smaller amplitude, slower
velocity and longer latency of pupil response compared to controls (all
p<0.001). A model including age and these three
components resulted in an AUROC of 0.87 (95% CI 0.83 to 0.92) with
80% sensitivity and specificity in detecting glaucoma. This result
remained robust after cross-validation.
Conclusions
Using pupillography, we were able to discriminate persons with
glaucoma from those with normal eye exams. With refinement, pupil testing
may provide a simple approach for glaucoma screening.