Predicting the Magnitude of Functional and Structural Damage in Glaucoma From Monocular Pupillary Light Responses Using Automated Pupillography.
Pradhan Zia S, Rao Harsha L, Puttaiah Narendra K, Kadambi Sujatha V, Dasari Srilakshmi, Reddy Hemanth B, Palakurthy Meena, Riyazuddin Mohammed, Rao Dhanaraj A S
AI Summary
Automated pupillography's constriction latency parameters (onset, maximal) best predicted the magnitude of functional and structural glaucoma damage, suggesting its potential as a non-invasive assessment tool.
Abstract
Purpose
To predict the magnitude of functional damage [mean deviation (MD) on visual field examination] and structural damage [retinal nerve fiber layer (RNFL) and ganglion cell complex (GCC) thickness on spectral domain optical coherence tomography] in glaucoma from monocular pupillary light response measurements using automated pupillography.
Methods
In total, 59 subjects (118 eyes) with either a confirmed or suspected diagnosis of glaucoma underwent automated pupillography, along with visual fields and spectral domain optical coherence tomography examinations. Association between pupillary light response measurements of each eye [amplitude of constriction, latency of onset of constriction (Loc), latency of maximal constriction (Lmaxc), velocity of constriction and velocity of redilation] and corresponding MD, average RNFL, and average GCC measurements were evaluated using univariate and multivariate regression analysis after accounting for the multicollinearity. Goodness of fit of the multivariate models was evaluated using coefficient of determination (R).
Results
Multivariate regression models that contained Loc and Lmaxc showed the best association with MD (R of 0.30), average RNFL thickness (R=0.18) and average GCC thickness (R=0.26). The formula that best predicts the MD could be described as: MD=-14.06-0.15×Loc+0.06×Lmaxc. The formula that best predicts the average RNFL thickness could be described as: Average RNFL thickness=67.18-0.22×Loc+0.09×Lmaxc.
Conclusions
Glaucomatous damage as estimated by MD, RNFL, and GCC thickness measurements were best predicted by the latency parameters (Loc and Lmaxc) of pupillography. Worsening of glaucomatous damage resulted in a delayed onset of pupillary constriction and a decreased Lmaxc.
MeSH Terms
Shields Classification
Key Concepts5
In glaucoma patients, multivariate regression models incorporating latency of onset of constriction (Loc) and latency of maximal constriction (Lmaxc) from monocular pupillary light responses showed the best association with mean deviation (MD) on visual field examination (R of 0.30), average retinal nerve fiber layer (RNFL) thickness (R=0.18), and average ganglion cell complex (GCC) thickness (R=0.26).
The formula that best predicts the mean deviation (MD) in glaucoma patients using monocular pupillary light responses is MD = -14.06 - 0.15 × Loc + 0.06 × Lmaxc, where Loc is latency of onset of constriction and Lmaxc is latency of maximal constriction.
The formula that best predicts the average retinal nerve fiber layer (RNFL) thickness in glaucoma patients using monocular pupillary light responses is Average RNFL thickness = 67.18 - 0.22 × Loc + 0.09 × Lmaxc, where Loc is latency of onset of constriction and Lmaxc is latency of maximal constriction.
Worsening of glaucomatous damage, as estimated by mean deviation (MD), retinal nerve fiber layer (RNFL), and ganglion cell complex (GCC) thickness measurements, is best predicted by the latency parameters (latency of onset of constriction and latency of maximal constriction) of automated pupillography.
Worsening of glaucomatous damage, as estimated by MD, RNFL, and GCC thickness measurements, resulted in a delayed onset of pupillary constriction and a decreased latency of maximal constriction (Lmaxc).
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