Intraocular Pressure Monitoring Using an Implantable Sensor Detects Structural Glaucoma Progression in the EYEMATE-IO Trial.
Summary
Peak IOP and IOP fluctuations in glaucoma patients derived from measurements with the EYEMATE-IO sensor were associated with progression of the disease, whereas GAT measurements were not.
Abstract
PURPOSE
To evaluate the association between intraocular pressure (IOP) measurements and concurrent rates of retinal nerve fiber layer (RNFL) thinning in primary open-angle glaucoma (POAG) eyes previously implanted with a sulcus-based IOP sensor.
DESIGN
Prospective.
METHODS
In this case series, part of the prospective, open-label, multicenter interventional EYEMATE-IO trial, patients implanted with the EYEMATE-IO sensor system (Implandata) were enrolled in the 3-year ARGOS-03 follow-up study. All patients enrolled had at least 5 optical coherence tomography (OCT) examinations 6 months apart, with a minimum 2-year follow-up. A minimum of 4 IOP measurements daily at different times of the day were obtained with the EYEMATE-IO. Mean IOP, peak IOP, and fluctuation of IOP measured by EYEMATE-IO sensor during the period between 2 consecutive OCT examinations were calculated, and the relationship with OCT RNFL thinning was analyzed using mixed-effects models. The relationship of mean IOP measured by Goldmann applanation tonometry (GAT) on the day of the OCT examination with RNFL thinning was also analyzed.
RESULTS
Eight eyes of 8 patients with the EYEMATE-IO sensor were included in the analysis. The mean number of self-measurements of IOP per patient was 7283 ± 5562 (range 1478-17247), with a mean follow-up time of 2.88 ± 0.19 years (range 2.43-3.01). The mean number of OCT examinations per patient was 6.38 ± 0.74 (range 5-7). Overall, the mean rate of RNFL thinning during the follow-up was -0.62 ± 1.06 μm/y (P = .274). In the linear mixed-effects model analysis, both peak IOP and IOP fluctuations measured using the EYEMATE-IO sensor were significantly associated with RNFL thinning (coefficient [95% CI]: -0.11 [-0.19; -0.34], P = .005, and -0.76 [-1.31; -0.20], P = .007, respectively), whereas no association was found for in-office mean IOP measured by GAT (95%
CI
[-0.12; 0.20], P = .616).
CONCLUSIONS
Peak IOP and IOP fluctuations in glaucoma patients derived from measurements with the EYEMATE-IO sensor were associated with progression of the disease, whereas GAT measurements were not. These findings suggest that self-measurements of IOP throughout the day with an implantable IOP sensor can predict glaucoma progression.
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