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Deep Learning in the Detection and Prediction of Hydroxychloroquine Maculopathy

Study acronym: PLAQUINAI
StatusCompleted
PhaseNot specified
Started
View on ClinicalTrials.gov ↗

Record History

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  1. Study completion date changed from estimate of Jun 20, 2025 to Sep 20, 2026 Show 6 more changesShow less
    • Trial completed
    • Secondary endpoints: 1 to 3
    • Study description expanded, about 14 words
    • Site details revised
    • Collaborators expanded, about 9 words
    • Eligibility criteria shortened, about 2 words
  2. Study First Submitted
  • Stopped: an ongoing trial was terminated, suspended or withdrawn.
  • Notable: the trial’s plan changed such as a big move in its timeline or size, a new primary endpoint, sponsor or phase, or recruiting opened or resumed.
  • Minor: routine progress and housekeeping, such as sites added or enrollment closed.
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.
Trial Details
NCT Number NCT06839443
Lead Sponsor Centro Hospitalar de Lisboa Central
Collaborators: Biomedical Imaging Lab, UTAD, led by Prof. António Cunha.
Conditions
(from sponsor)		 Hidroxicloroquine Intake
Enrollment 100 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov