ArticleDocumenta ophthalmologica. Advances in ophthalmology2020
A novel method for electroretinogram assessment in patients with central retinal vein occlusion.
Article in Documenta ophthalmologica. Advances in ophthalmology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 9 citations in OpenAlex.
- The oscillatory response of the electroretinogram and neuronal adaptation.Acta ophthalmologica · 2026Review
- Oscillatory potential findings in patients with acute ischaemic central retinal vein occlusion.BMJ open ophthalmology · 2024Article
- New criteria for evaluation of electroretinogram in patients with retinitis pigmentosa.Documenta ophthalmologica. Advances in ophthalmology · 2021Article
- Continuous wavelet transform analysis of ERG in patients with diabetic retinopathy.Documenta ophthalmologica. Advances in ophthalmology · 2021Article
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3 authors at 3 institutions in 1 country.
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Abstract
purposeCentral retinal vein occlusion (CRVO) is the second most common retinal vascular disorder after diabetic retinopathy that affects the eyes. We propose a method for distinction of normal and central CRVO eyes based on electroretinogram (ERG).
methodsSeventeen patients with CRVO in one eye were analyzed. Their ERG signals were collected in six different stimuli, including four records in the darkness (dark-adapted 0.01, dark-adapted 3.0, dark-adapted oscillatory potentials, and dark-adapted 10) and two records in brightness (light-adapted 3.0 and light-adapted 30 Hz flicker). Nonlinear features such as Hurst exponent (HE) and approximate entropy (ApEn) were extracted from healthy and CRVO eyes. Finally, a parabolic mapping and two criteria (theta angle and the density of points) were proposed to distinguish the groups.
resultsFor ApEn, the P values of dark-adapted 3.0 oscillatory (P = 0.0433) and flicker (P = 0.0425) confirmed significant differences between the groups. For HE, the P values of dark-adapted 3.0 oscillatory (P = 0.0421) and flicker 30 Hz (P = 0.0402) confirmed differences between the healthy and CRVO groups. The P values of theta angle for dark-adapted 3.0 (P = 0.0199), dark-adapted oscillatory (P = 0.0265), dark-adapted 10.0 (P = 0.0166), light-adapted 3.0 (P = 0.0411), and flicker (P = 0.0361) showed significant differences. Using the density criterion, the statistical test demonstrated a significant difference between the groups in dark-adapted 3 (P = 0.0038), dark-adapted oscillatory (P = 0.0102), dark-adapted 10.0 (P = 0.0071), light-adapted 3.0 (P = 0.0319), and flicker 30 Hz (P = 0.0076).
conclusionThe proposed features have made it possible to distinguish between healthy and CRVO eyes. This method could be helpful in some cases with no definite diagnosis or to estimate the severity of CRVO.
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