Jithin Yohannan

Evidence-based Criteria for Assessment of Visual Field Reliability.

FL have little impact on reliability in patients with established glaucoma.

Assessing Glaucoma Progression Using Machine Learning Trained on Longitudinal Visual Field and Clinical Data.

A convolutional LSTM architecture can capture local and global trends in VFs over time.

The Evolving Role of the Relationship between Optic Nerve Structure and Function in Glaucoma.

Second, those studies that use longitudinal data to improve detection of worsening are reviewed. Finally, areas of further research and steps needed to implement structure-function relationships clinically are explored.

The Effect of Transitioning from SITA Standard to SITA Faster on Visual Field Performance.

Converting to SITA Faster in eyes that were previously followed with SITA Standard led to similar VF performance in mild glaucoma but resulted in higher MD values in moderate and advanced glaucoma.

Comparison of Clinical Outcomes with Open Versus Closed Conjunctiva Implantation of the XEN45 Gel Stent.

Implantation of the XEN45 with opening of the conjunctiva is a safe and efficacious procedure to lower IOP with comparable success rate and lower needling rate compared with the closed conjunctiva technique.

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.

Evidence-Based Criteria for Determining Peripapillary OCT Reliability.

Signal strength decreases down to 3 have relatively mild impacts on OCT reliability.

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.

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.

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.

Factors Predicting a Greater Likelihood of Poor Visual Field Reliability in Glaucoma Patients and Suspects.

FPs, test duration, and FNs are the primary measures predicting if a VF is likely to be reliable, although tests with normal reliability measures may still be unreliable.

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.

Short-Term Outcomes of Hydrus Microstent With and Without Additional Canaloplasty During Cataract Surgery.

Microstent combined with canaloplasty resulted in a significantly higher rate of medication-free status compared with microstent alone through 6 months.

Reliability of Several Glaucoma Tests in Patients With Boston Type 1 Keratoprosthesis.

The 10-2 visual field and RNFL thickness seem sufficiently repeatable and might allow the detection of glaucoma progression in KPro eyes. Such testing is important, given limited inter-rater agreement regarding the palpation IOP estimate.

The Association Between Intraocular Pressure and Visual Field Worsening in Treated Glaucoma Patients.

IOP remained associated with VF worsening in eyes with more advanced glaucoma throughout the IOP range but was only associated with VF worsening in eyes with less severe glaucoma at higher IOP.

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.

Reduced Intraocular Pressure Variability after Gonioscopy-Assisted Transluminal Trabeculotomy Procedure.

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.

Reply to Commentary on ``Development and Evaluation of an Artificial Intelligence Model to Set Target IOP for Glaucoma''.

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.