Diagnostic accuracy of an iPad application for detection of visual field defects

Eye (Lond). 2023 Jun;37(8):1690-1695. doi: 10.1038/s41433-022-02223-y. Epub 2022 Sep 5.

Abstract

Background/objectives: Tablet-based perimetry could be used to test for glaucomatous visual field defects in settings without easy access to perimeters, although few studies have assessed diagnostic accuracy of tablet-based tests. The goal of this study was to determine the diagnostic accuracy of iPad perimetry using the visualFields Easy application.

Subjects/methods: This was a prospective, cross-sectional study of patients undergoing their first Humphrey Field Analyser (HFA) visual field test at a glaucoma clinic in India. Participants underwent 24-2 SITA Standard HFA testing and iPad-based perimetry with the visualFields Easy application. Reference standards for both visual field loss and suspected glaucoma were determined by ophthalmologist review of HFA results and optic disc photographs. Receiver operating characteristic curves were constructed to assess diagnostic accuracy at various test thresholds.

Results: 203 eyes from 115 participants were included, with 82 eyes classified as moderate or worse glaucoma. iPad perimetry had an area under the receiver operating characteristic (AUROC) curve of 0.64 (95% CI 0.57 to 0.71) for detection of any visual field defect relative to HFA and an AUROC of 0.68 (0.59 to 0.76) for detection of moderate or worse glaucoma relative to ophthalmologist examination. At a set specificity of 90%, the sensitivity of iPad perimetry for detection of moderate or worse glaucoma was 35% (22-48%).

Conclusions: iPad perimetry using the visualFields Easy application had inadequate diagnostic accuracy to be used as a screening tool for glaucoma in this South Indian population.

MeSH terms

  • Cross-Sectional Studies
  • Glaucoma* / diagnosis
  • Glaucoma* / epidemiology
  • Humans
  • Prospective Studies
  • ROC Curve
  • Sensitivity and Specificity
  • Vision Disorders / diagnosis
  • Visual Field Tests* / methods
  • Visual Fields