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EquineCase series / Retrospective2 min read · distilled by Vetree AI

Horses without ocular disease maintain similar electroretinographic responses and peripapillary retinal thicknesses across age groups.

Gray AP, Ledbetter EC, Thirunagari N, Irias-Valvo K, Knickelbein KE · American Journal of Veterinary Research · 7 July 2026

Clinical bottom line

Abnormal ERG findings and retinal thinning in aged horses should be considered pathologic, not age-related.

Summary

This prospective study investigated the effects of age on electroretinography (ERG) parameters and peripapillary retinal thickness in horses with clinically healthy eyes. Fifteen horses were divided into three age groups (≤10, 11–20, and ≥21 years), each containing five animals. All horses underwent scotopic and photopic ERG testing using the RETevet device, high-resolution fundus photography, and spectral-domain optical coherence tomography (SD-OCT) to assess total retinal thickness (TRT) in nasal, dorsal, and temporal peripapillary regions. Statistical analysis revealed no significant differences in ERG a- or b-wave implicit times or amplitudes between any of the three age groups under either scotopic or photopic conditions. Similarly, no significant differences in peripapillary TRT were identified across regions or age groups. These findings refute the authors' hypothesis that older horses would demonstrate reduced ERG b-wave amplitudes while supporting the hypothesis that retinal thickness would remain stable with age. The study concludes that normal equine aging does not significantly alter retinal function or peripapillary thickness. Clinically, this is important because ERG abnormalities and retinal thinning detected in aged horses should not be attributed to physiologic aging but rather investigated as pathologic findings. Individual variation among horses is acknowledged, but the overall trend supports stable retinal health across the equine lifespan in the absence of ocular disease.

EquineLarge AnimalOphthalmology

This summary was distilled by AI and may occasionally misinterpret data. Confirm critical details with the primary literature before clinical application.