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Deep Learning in the Detection and Prediction of Hydroxychloroquine Maculopathy

NCT06839443 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 100

Last updated 2025-02-21

No results posted yet for this study

Summary

Hydroxychloroquine retinal toxicity affects a significant number of patients using this medication. Detection of toxicity is difficult in the early stages of the disease and depends on the subjectivity of the clinician who reads the tests (optical coherence tomography, autofluorescence and visual fields). Automating the reading of these diagnostic exams could lead to earlier detection of this pathology and reduce the burden associated with interpreting these exams in the ophthalmology service. The images that are usually taken in the screening and monitoring of hydroxychloroquine toxicity by will be collected - photography of the ocular fundus and optical coherence tomography with autofluorescence.

Conditions

  • Hidroxicloroquine Intake

Interventions

DIAGNOSTIC_TEST

Retinopathy group

OCT scans and Retinai algorithm will be performed

DIAGNOSTIC_TEST

Control group

OCT scans and Retinai algorithm will be performed

Sponsors & Collaborators

  • Centro Hospitalar de Lisboa Central

    lead OTHER

Principal Investigators

  • Rita Anjos, MD · ULS São José

Eligibility

Min Age
18 Years
Max Age
100 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2024-08-01
Primary Completion
2025-04-20
Completion
2025-06-20

Countries

  • Portugal

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06839443 on ClinicalTrials.gov