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Observational Study
. 2017 May;42(5):743-747.
doi: 10.1080/02713683.2016.1238944. Epub 2016 Nov 29.

Diagnostic Ability of Automated Pupillography in Glaucoma

Affiliations
Observational Study

Diagnostic Ability of Automated Pupillography in Glaucoma

Harsha L Rao et al. Curr Eye Res. 2017 May.

Abstract

Purpose: To evaluate the diagnostic ability of automated pupillography measurements in glaucoma and study the effect of inter-eye asymmetry in glaucomatous damage on the diagnostic ability.

Methods: In an observational, cross-sectional study, 47 glaucoma patients and 42 control subjects underwent automated pupillography using a commercially available device. Diagnostic abilities of the pupillary response measurements were evaluated using area under receiver operating characteristic (ROC) curves (AUC) and sensitivities at fixed specificities. Influence of inter-eye asymmetry in glaucoma [inter-eye mean deviation (MD) difference on visual fields (VF)] on the diagnostic ability of pupillography parameters was evaluated by ROC regression approach.

Results: The AUCs of automated pupillography parameters ranged from 0.60 (amplitude score with peripheral blue stimulus) to 0.82 (amplitude score with full field white stimulus, Amp-FF-W). Sensitivity at 95% specificity ranged between 5% (amplitude score with full field blue stimulus) and 45% (amplitude score with full field green stimulus). Inter-eye MD difference significantly affected the diagnostic performance of automated pupillography parameters (p < 0.05). AUCs of Amp-FF-W at inter-eye MD difference of 0 dB, 5 dB, 10 dB and 15 dB were 0.71, 0.80, 0.87 and 0.93, respectively, according to the regression model. The corresponding sensitivities at 95% specificity were 20%, 34%, 50% and 66%, respectively.

Conclusions: The diagnostic abilities of even the best automated pupillography parameters were only moderate in glaucoma. The performance of these pupillography measurements in detecting glaucoma significantly increased with greater inter-eye asymmetry in the glaucomatous damage.

Keywords: Automated pupillography; diagnostic ability; glaucoma.

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