Predictors of atypical birefringence pattern in scanning laser polarimetry.
OBJECTIVE
To evaluate predictors of atypical birefringence patterns (ABP) observed in scanning laser polarimetry.


METHODS
A total of 179 eyes from 82 normal subjects and 97 glaucoma patients were included. The retinal nerve fibre layer in each eye was imaged sequentially with GDx variable corneal compensation (VCC) and GDx enhanced corneal compensation (ECC) (Carl Zeiss Meditec, Dublin, California). The associations between the typical scan score (TSS) and age, axial length, spherical error, parapapillary atrophy (PPA) and visual-field mean deviation (MD) were evaluated with univariate and multivariate regression analyses.


RESULTS
23.5% (42/179) and 5.0% (9/179) of subjects had ABP (TSS<80) with GDx VCC and GDx ECC, respectively. For both GDx VCC and ECC, the TSS was significantly correlated with age, axial length, spherical error and PPA, but not with visual-field MD. After adjusting the effect of covariates, the axial length/spherical error and PPA were significantly associated with GDx VCC TSS, whereas the axial length/spherical error was the only predictor for GDx ECC TSS. Myopic eyes were more likely to develop ABP in both GDx VCC and ECC.


CONCLUSIONS
Axial length or spherical error is a significant predictor for ABP with both GDx VCC and GDx ECC. Caution should be exercised in interpreting the results of scanning laser polarimetry in eyes with a long axial length or myopia.
Qiu
K
K
Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, PR China.
Leung
C K S
CK
Weinreb
R N
RN
Liu
S
S
Chueng
C Y L
CY
Li
H
H
Zhang
M-Z
MZ
Pang
C-P
CP
Lam
D S C
DS
D000328:Adult; D000367:Age Factors; D001718:Birefringence; D003315:Cornea / Q000033:anatomy & histology* / Q000502:physiology; D003941:Diagnostic Techniques, Ophthalmological; D005260:Female; D005901:Glaucoma / Q000473:pathology*; D006801:Humans; D007834:Lasers; D008297:Male; D009412:Nerve Fibers / Q000473:pathology*; D011237:Predictive Value of Tests; D012044:Regression Analysis