Artificial Intelligence for Staging Glaucoma Severity: A Comparison With an Eye Specialist Using Visual Field Tests

NCT07820709 | Completed

• 1 other identifier: OftalmoUnisa2026_1
• Study Type: observational
• Target: 50
• Locations: 1 country
• Sites: 1

Brief Summary

The study titled "Reliability of Artificial Intelligence in Glaucoma Severity Staging Using the Brusini GSS2 System: A Longitudinal Comparative Study against Expert Assessment" aims to evaluate the diagnostic reliability and clinical utility of an Artificial Intelligence (AI) system in staging glaucoma severity using the Brusini Glaucoma Staging System 2 (GSS2) compared to expert ophthalmologist assessment. The study protocol involves the longitudinal analysis of visual fields (VFs) collected at baseline (T0) and at a 1-year follow-up (T1). Statistical methodology will utilize quadratic weighted Cohen's kappa to assess diagnostic agreement between the AI system and expert assessment, Wilcoxon signed-rank tests to evaluate potential systematic bias, and Spearman's rank correlation to investigate the relationship between longitudinal progression and changes in the clinical Visual Field Index.

Conditions

Glaucoma and Ocular Hypertension

Outcome Measures

Primary Outcomes (1)

• Quadratic weighted Cohen's kappa coefficient for diagnostic agreement in glaucoma severity staging between AI and expert assessment

  Glaucoma severity will be staged (from Stage 0 to Stage 5) using the Brusini Glaucoma Staging System 2 (GSS2) based on visual field parameters. Staging will be performed independently by the AI system and an expert ophthalmologist at each time point. Inter-rater agreement between the AI and expert staging will be quantified using the quadratic weighted Cohen's kappa ($\\kappa$), where values range from -1 (complete disagreement) to +1 (perfect agreement).

  Baseline (T0) and 1-year follow-up (T1)

Secondary Outcomes (1)

• Median difference in Brusini GSS2 staging scores between AI and expert assessment

  Baseline (T0) and 1-year follow-up (T1)

Study Arms (1)

Glaucoma Patients

Diagnostic Test: Artificial Intelligence GSS2 Staging

Interventions

Artificial Intelligence GSS2 Staging DIAGNOSTIC_TEST

An artificial intelligence system used to automatically stage glaucoma severity from standard automated visual field tests according to the Brusini Glaucoma Staging System 2 (GSS2). AI classifications were compared with those of an expert ophthalmologist at baseline and 1-year follow-up. The AI was used for assessment only and did not influence patient management or treatment.

Glaucoma Patients

Eligibility Criteria

• Sex: all
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Adult patients with glaucoma or suspected glaucoma attending the Ophthalmology Unit of University of Salerno for routine glaucoma follow-up. Eligible participants underwent standard automated visual field testing at baseline and approximately 1-year follow-up. Visual fields were independently staged by an artificial intelligence system and an expert ophthalmologist using the Brusini Glaucoma Staging System 2 (GSS2).

You may qualify if:

• Adults (≥18 years of age).
• Diagnosis of glaucoma or suspected glaucoma undergoing routine clinical follow-up.
• Availability of reliable standard automated visual field (VF) examinations at baseline and approximately 1-year follow-up.
• Visual field tests suitable for staging using the Brusini Glaucoma Staging System 2 (GSS2).
• Availability of all clinical data required for study analysis.

You may not qualify if:

• Unreliable visual field examinations (e.g., excessive fixation losses, false-positive or false-negative responses according to institutional reliability criteria).
• Visual field defects attributable to ocular or neurological diseases other than glaucoma.
• Missing baseline or follow-up visual field examinations.
• Incomplete clinical data preventing GSS2 staging or statistical analysis.
• Previous ocular conditions or interventions that could significantly affect visual field interpretation, if judged by the investigator.

Sponsors & Collaborators

• University of Salerno: lead

Study Sites (1)

University of Salerno

Salerno, 84084, Italy

Location

MeSH Terms

Conditions

Glaucoma; Ocular Hypertension

Condition Hierarchy (Ancestors)

Eye Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: July 14, 2026
• First Posted: September 15, 2026
• Study Start: April 15, 2011
• Primary Completion: July 24, 2025
• Study Completion: July 24, 2025
• Last Updated: September 15, 2026

Record last verified: 2026-07

Data Sharing

• IPD Sharing: Will not share

Locations

IT (1)