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Related Concept Videos

Open Angle Glaucoma: Treatment01:27

Open Angle Glaucoma: Treatment

In open-angle glaucoma, the iridocorneal angle remains open, but the trabecular meshwork becomes stiff, slowing down the outflow of aqueous humor. This causes a buildup of aqueous humor in the anterior chamber, leading to a sudden increase in intraocular pressure. The treatment for open-angle glaucoma focuses on reducing the elevated intraocular pressure by either decreasing the secretion of aqueous humor or increasing its outflow.
Drugs such as carbonic anhydrase inhibitors, α2- and...
Glaucoma: Overview01:25

Glaucoma: Overview

Glaucoma is an eye condition characterized by increased intraocular pressure that damages the retina and optic nerve, leading to irreversible blindness if left untreated. The human eye has various components, including the cornea, iris, pupil, lens, and optic nerve. Aqueous humor is secreted by the epithelium of the ciliary body in the posterior chamber and flows through the trabecular meshwork and canal of Schlemm, maintaining normal intraocular pressure. The trabecular meshwork and the canal...
Angle Closure Glaucoma: Treatment01:28

Angle Closure Glaucoma: Treatment

Angle-closure glaucoma, or closed-angle glaucoma, is an eye condition where the iris bulges out and blocks the iridocorneal angle, resulting in a buildup of aqueous humor and increased intraocular pressure. Immediate medical attention is necessary due to the sudden onset of symptoms. The treatment for angle-closure glaucoma includes short-term and long-term approaches. Short-term treatment involves using eye drops like pilocarpine to lower intraocular pressure by increasing aqueous humor...

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Related Experiment Video

Updated: Jun 25, 2026

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential
07:11

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential

Published on: May 25, 2020

Machine Learning-Based Prediction of Long-Term Intraocular Pressure Fluctuations in Open-Angle Glaucoma.

Colya N Englisch1,2, André M Trouvain1, Philip Wakili1

  • 1Eye Clinic Sulzbach, Knappschaft Hospitals Saar, Sulzbach/Saar, Germany.

Ophthalmology Science
|June 24, 2026
PubMed
Summary
This summary is machine-generated.

Long-term intraocular pressure (IOP) fluctuations in glaucoma can be predicted using telemetric data and machine learning. This approach offers a path toward personalized patient care and reduced healthcare costs.

Keywords:
Artificial intelligenceFluctuationGlaucomaIntraocular pressureMachine learning

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Translaminar Autonomous System Model for the Modulation of Intraocular and Intracranial Pressure in Human Donor Posterior Segments
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Translaminar Autonomous System Model for the Modulation of Intraocular and Intracranial Pressure in Human Donor Posterior Segments

Published on: April 24, 2020

Related Experiment Videos

Last Updated: Jun 25, 2026

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential
07:11

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential

Published on: May 25, 2020

Translaminar Autonomous System Model for the Modulation of Intraocular and Intracranial Pressure in Human Donor Posterior Segments
08:55

Translaminar Autonomous System Model for the Modulation of Intraocular and Intracranial Pressure in Human Donor Posterior Segments

Published on: April 24, 2020

Area of Science:

  • Ophthalmology
  • Medical Technology
  • Data Science

Background:

  • Glaucoma management requires consistent monitoring of intraocular pressure (IOP).
  • Predicting long-term IOP fluctuations is crucial for effective treatment strategies.
  • Telemetric IOP sensors offer continuous monitoring capabilities.

Purpose of the Study:

  • To assess the predictability of long-term intraocular pressure (IOP) fluctuations in open-angle glaucoma patients.
  • To evaluate the efficacy of telemetric IOP sensor data in predicting future IOP changes.
  • To explore the use of machine learning models for IOP fluctuation prediction.

Main Methods:

  • A prospective, single-arm, multicenter study involving 24 glaucoma patients with telemetric IOP sensors.
  • Analysis of nyctohemeral mean IOP data, excluding the initial 90 postoperative days.
  • Application of Pearson correlation, multivariate regression, and Random Forest Classifier models to predict long-term IOP fluctuations from short-term data and clinical features.

Main Results:

  • Short-term IOP fluctuations showed weak correlation with long-term variability (Pearson r ≤ 0.33).
  • Random Forest models achieved high performance (AUROC 0.81-0.86), predicting long-term IOP fluctuations with good accuracy, sensitivity, and specificity.
  • Key predictors included short-term IOP fluctuations, mean nyctohemeral IOP, ocular pulse amplitude, age, BMI, and central corneal thickness.

Conclusions:

  • Long-term IOP fluctuations in glaucoma patients are predictable using a combination of baseline clinical/demographic data and IOP-derived features.
  • Telemetric monitoring and predictive modeling can enhance individualized glaucoma care.
  • This approach may reduce healthcare costs and the burden of frequent clinical visits.