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Giacinto Triolo, William J Feuer, Pedro F Monsalve, Luis E Vazquez, John Joseph McSoley, Lori Ventura, Vittorio Porciatti; Ocular neurovascular changes during head-down posture predict future retinal nerve fiber layer loss in glaucoma suspects.. Invest. Ophthalmol. Vis. Sci. 2016;57(12):2993.
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© ARVO (1962-2015); The Authors (2016-present)
To investigate posture-induced neuro-vascular changes predictive of optic nerve tissue loss in glaucoma suspects (GS).
Mean peripapillary retinal fiber layer thickness (RNFLT) was measured with OCT two times/year in 29 GS aged 58 ± 8.9 years over 5.0 ± 0.73 years. GS, together with 11 age-matched controls aged 54.2 ± 10 years, also had a baseline pattern electroretinogram (PERG), IOP and brachial blood pressure measurements in the seated and - 10 degrees head-down-body-tilt position (HDT). An additional group of 17 young, healthy subjects aged 20.4 ± 10 years was used to investigate age-dependent changes in hemodynamic parameters during HDT.
While all GS had baseline RNFLT in the normal range, 10/29 (34%) of them developed significant (P<0.05) thinning over the follow-up period. There was no correlation between initial RNFLT and corresponding change (R2 = 0.008). RNFL-thinners, RNFL-non-thinners, and controls tended to differ in a number of measurements such as HDT-PERG amplitude, seated PERG phase, seated systolic blood pressure (SBP), HDT-diastolic blood pressure (DBP), and calculated HDT-ocular perfusion pressure (OPP). Backward stepwise logistic regression including seated and HDT-induced changes of all variables determined a prediction equation discriminating (P=0.007) thinners from non-thinners with 90% sensitivity and 79% specificity (AUROC=0.91) with 2 false negatives and 1 false positive.
HDT is a non-invasive provocative procedure that can disclose neuro-vascular deficits in glaucoma suspects predictive of future loss of optic nerve tissue. This study provides a proof of concept that the HDT-PERG provocative test may have a role in the clinical management of glaucoma.
This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.
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