Deep Learning in the Detection and Prediction of Hydroxychloroquine Maculopathy

Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18-100
SponsorCentro Hospitalar de Lisboa Central

About this trial

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.

Eligibility criteria

Qualifiers

Patients with > 10 years of HCQ intake

Disqualifiers

Patients with ocular diseases that might mimic HCQ maculopathy or interfer with HCQ maculopathy screening

Trial design

Treatments tested in this trial

  • Retinopathy group
  • Control group

Treatment groups

100 Participants
are divided into 2 treatment groups