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Editors Selection IGR 8-1

Glaucoma and Systemic Diseases: POAG and Poor Sleep Quality

James Morgan

Comment by James Morgan on:

61823 Intrinsically photosensitive retinal ganglion cell activity is associated with decreased sleep quality in patients with glaucoma, Gracitelli CP; Duque-Chica GL; Roizenblatt M et al., Ophthalmology, 2015; 122: 1139-1148


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Graticelli et al. report on the changes in the sleep patterns of patients with glaucoma. The background to the potential effect of glaucoma on circadian rhythms has been reported by others. The study adds to the debate by quantifying the changes in pupillometry as a function of disease. The pupillometry was tuned to be selective for intrinsically responsive retinal ganglion cells which are thought to be important in entraining the circadian clock.

The principle findings are that sleep disturbances are significant in patients with treated glaucoma compared with age-matched controls. The time to onset of REM sleep as identified a useful benchmark for sleep disturbance. Overall the study contributes to the literature that sleep disturbance is common in patients with glaucoma. The link to any possible change in photosensitive RGCs is, however, associative and not causative. The investigators admit to the small size of the study which precludes any robust (multivariate) analysis of the factors that could contribute to sleep disturbance- in particular age, medication, and other concurrent diseases. The thorough assessment of the patient's sleep pattern is commendable but it seems unlikely that this methodology could be applied to large patient cohorts.

Glaucoma can affect patient quality of life in ways that are not captured by conventional measurements of visual performance

The study should remind us that glaucoma can affect patient quality of life in ways that are not captured by conventional measurements of visual performance. It highlights the need for larger studies to dissect the complex interactions of medications/concurrent disease/environment on circadian processes. Knowledge of these factors is important since it could be used to optimize times for the measurement and treatment of those factors by which we gauge disease severity. We also need less demanding surrogate measurements of sleep quality that would fit with a 'big data' approach to this problem.



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