ArticleTranslational vision science & technology2026
Wavelet-Based Pattern ERG Biomarkers Outperform Temporal Amplitude Measures for Functional Stratification in Optic Nerve Disease.
Article in Translational vision science & technology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Technical note: a functional data analysis approach to analyze the light-adapted electroretinogram in children and adolescents.Documenta ophthalmologica. Advances in ophthalmology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Purpose: To extend wavelet analysis of pattern electroretinography (PERG) from macular cone to retinal ganglion cell (RGC) dysfunction in optic nerve disease (OND) by validating Symlet-2 (sym2) discrete wavelet transform (DWT) features. Methods: From the open access PERG-Institute of Applied Ophthalmobiology (IOBA) dataset, 58 recordings from OND subjects and 262 recordings from healthy volunteers (HVs) were analyzed. Five pre-selected sym2 coefficients (D5-2, D6-2, D6-3, A6-3, A6-4) were quantified. Their correlations with canonical amplitudes (|P50-N35|, |N95-P50|) and group separation (rank-biserial effect size, |rrb|) were analyzed. We also assessed a previously defined DWT energy index based on the Daubechies 8 mother wavelet (7N), capturing RGC activity. Results: The macular cone-specific sym2-D6-2 correlated tightly with |P50-N35| in HVs (rcorr = 0.95) and OND subjects (rcorr = 0.97). In contrast, sym2-A6-4 (112-150 ms, 0-13 Hz) was best suited to capture differences between the HV and OND groups (|rrb| = 0.549), compared to |N95-P50| (|rrb| = 0.358). Bootstrap benchmarking confirmed that sym2-A6-4 outperformed |P50-N35| and |N95-P50| (Δ|rrb| = 0.362 and 0.187; Pboot = 0.005 and 0.036, respectively). The 7N feature failed to yield effective results on all measures (|rrb| = 0.084). Conclusions: Sym2 DWT features provide compartment-specific, multidimensional biomarkers that outperform traditional canonical peaks for both macular cone (sym2-D6-2) and RGC (sym2-A6-4) assessment. Future work should validate these biomarkers in a large, diverse, genetically and phenotypically characterized external cohort to confirm generalizability and clinical utility. Translational Relevance: Sym2 wavelet indices provide robust and sensitive PERG biomarkers that could serve as quantitative endpoints in clinical trials.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.