Diagnostic sensitivity and specificity of dark adaptometry for detection of age-related macular degeneration

Gregory R. Jackson, Ingrid U. Scott, Ivana K. Kim, David A. Quillen, Alessandro Iannaccone, John G. Edwards

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Abstract

PURPOSE. Difficulty with night vision is a common complaint of patients with age-related macular degeneration (AMD). Consistent with this complaint, dark adaptation (DA) is substantially impaired in these patients. Because of the severity of the deficit, measurement of DA has been suggested as a means for the diagnosis of AMD. Previous methods for measurement of DA were time intensive (>30 minutes), which made them unsuitable for clinical use. This study evaluated a rapid DA test (≤ 6.5 minutes) for the detection of AMD. METHODS. Dark adaptation was measured by using the AdaptDx dark adaptometer in two groups: subjects with normal retinal health and subjects with AMD. Subjects were assigned to their group by clinical examination and grading of fundus photographs. Subjects were classified as having DA consistent with normal retinal health (rod intercept ≤ 6.5 minutes) or having dark adaptation consistent with AMD (rod intercept > 6.5 minutes). RESULTS. The eligible sample for analysis included 21 normal adults and 127 AMD patients. The rapid test was found to have a diagnostic sensitivity of 90.6% (P < 0.001) and specificity of 90.5% (P < 0.027). Thus, abnormal DA was detected in 115 of 127 AMD patients, and normal DA was found in 19 of 21 normal adults. CONCLUSIONS. The high diagnostic sensitivity and specificity compared favorably to longduration research methods for the measurement of DA, and slit lamp biomicroscopy performed by a retina specialist. These results suggest that a rapid DA test is useful for the detection of AMD.

Original languageEnglish (US)
Pages (from-to)1427-1431
Number of pages5
JournalInvestigative Ophthalmology and Visual Science
Volume55
Issue number3
DOIs
StatePublished - Jan 1 2014

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All Science Journal Classification (ASJC) codes

  • Ophthalmology
  • Sensory Systems
  • Cellular and Molecular Neuroscience

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