Bradley Chris

Predicting Visual Field Worsening with Longitudinal OCT Data Using a Gated Transformer Network.

Gated transformer network models trained with OCT data may be used to identify VF worsening.

Comparing the Accuracy of Peripapillary OCT Scans and Visual Fields to Detect Glaucoma Worsening.

More frequent OCT scans and VF tests are needed to improve the accuracy of diagnosing glaucoma worsening.

Evidence-Based Guidelines for the Number of Peripapillary OCT Scans Needed to Detect Glaucoma Worsening.

To diagnose RNFL worsening more accurately, the number of OCT scans must be increased compared with current clinical practice. A clustered measurement strategy reduces the number of scans required compared with evenly spacing measurements.

Forecasting Risk of Future Rapid Glaucoma Worsening Using Early Visual Field, OCT, and Clinical Data.

Deep learning models can forecast future rapid glaucoma worsening with modest to high performance when trained using data from early in the disease course.

The Effect of Achieving Target Intraocular Pressure on Visual Field Worsening.

In treated patients, failing to achieve target IOP was associated with more rapid VF worsening. Eyes with moderate glaucoma experienced the greatest VF worsening from failing to achieve target IOP.

Validation of a Wearable Virtual Reality Perimeter for Glaucoma Staging, The NOVA Trial: Novel Virtual Reality Field Assessment.

Estimated sensitivities of RATA-Standard are comparable to SITA-Standard between 23 to 40 dB with high concordance in glaucoma staging.

The Impact of Social Vulnerability on Structural and Functional Glaucoma Severity, Worsening, and Variability.

Increased SVI score is associated with worse functional (VF) loss at baseline, higher rates of structural (OCT) worsening over time, higher VF variability, and a greater effect of IOP on RNFL loss.

Development and Evaluation of an Artificial Intelligence Model to Set Target IOP for Glaucoma.

AI models can set target IOP with comparable performance to glaucoma specialists and are superior to utilizing mean IOP or society-based guidelines to set targets.

The Impact of Achieving Target Intraocular Pressure on Glaucomatous Retinal Nerve Fiber Layer Thinning in a Treated Clinical Population.

Being above the clinician-set target pressure is associated with more rapid RNFL thinning in suspect, mild, and moderate glaucoma.

Improving Visual Field Forecasting by Correcting for the Effects of Poor Visual Field Reliability.

Including all VFs in the trend estimation has more predictive power for future reliable VFs than excluding unreliable VFs. Correcting for VF reliability further improves model accuracy.

Opportunities for Improving Glaucoma Clinical Trials via Deep Learning-Based Identification of Patients with Low Visual Field Variability.

Deep learning models can forecast eyes with low VF variability using data from a single baseline clinical visit.

The Effect of Medication Adherence on Intraocular Pressure and Glaucoma Progression.

Lower adherence was associated with higher IOP, with a stronger effect seen at PDC values below the median, and accelerated glaucomatous damage, including faster rates of MD deterioration and increased RNFLT loss.

Detecting Visual Field Worsening From Optic Nerve Head and Macular Optical Coherence Tomography Thickness Measurements.

cp-RNFL and GC-IPL similarly predicted VF worsening overall, but cp-RNFL performed best in early glaucoma stages and GC-IPL in later stages. Combining both did not enhance detection significantly.

The association between a pharmacy-based estimate of medication adherence and surgical and laser treatment in glaucoma patients.

Lower PDC was associated with an increased likelihood of undergoing any non-medical intervention.

Rapidly Progressing Glaucoma: Clinical, Structural, and Socioeconomic Drivers of Treatment Escalation.

Although rapid progression was a strong predictor of aggressive procedures, fewer than 1 in 4 patients underwent aggressive IOP-lowering interventions in the first 7 years.

Comparing the Utility of Retinal Nerve Fiber Layer and Ganglion Cell Inner Plexiform Layer OCT Changes to Detect Glaucoma Progression.

The cpRNFL and mGCIPL changes serve complementary roles in monitoring glaucoma progression depending on the stage of disease severity.

Predicting the Structure-Function Relationship in Glaucoma Using a Physiological Model.

A physiological model can account for much of the observed variance in structure-function data for glaucoma by simulating different patterns of RGC loss-this is currently not possible with curve-fitting models.