Abstract
To evaluate the effects of stimulus intensity, aging, sex, smoking and eye symmetry on pupillary light reflex (PLR) parameters. We evaluated 2812 eyes from 1406subjects in a single-centre, cross-sectional study. PLR data were collected using four different stimulus intensities. We prepared two models for each of the eight PLR parameters, and defined the model with the lowest values of Akaike's information criterion (AIC) as being the best-fit. Model A was a linear regression model without adjustment for among-individual variability, while the Model B linear mixed-effects models (LMMs) were adjusted for among-individual variability. The regression coefficients of the two models were compared. Model B showed the lowest AIC values for all parameters and the best fit. For light stimulus intensity, age and eye symmetry, the two models yielded similar results for all PLR parameters. For sex and smoking index, some PLR parameters showed the opposite results, i.e., Model A showed significant effects while Model B did not. These results indicate that light stimulus intensity, aging, sex, smoking and eye symmetry are factors that affect PLR parameters. These should be adjusted when evaluating the clinical potential of PLR as a diagnostic tool. In addition, adjusting for among-individual variability due to LMMs can improve the model fit and reduce false positives. This can reveal the association between clinical factors and PLR parameters with increased accuracy.
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