Reduced pattern electroretinogram signal in affected patients with Leber Hereditary Optic Neuropathy
Bibliographic record
Abstract
Abstract Purpose The pattern electroretinogram (PERG) signal has been reported to be a sensitive tool for the detection of retinal ganglion cell (RGC) dysfunction in both animal models and patients suffering from optic neuropathies. This study investigated whether functional PERG can detect different levels of RGC dysfunction in both carriers and affected patients with Leber Hereditary Optic Neuropathy (LHON). Methods PERG signals were recorded using both checkerboard (0.8° check size, 2 reversals/sec) and bars (0.5 cycles/deg) stimuli with mean luminance of 300 cd/m2 and 100% contrast. PERG signals were measured against functional full field Photopic Negative Response (PhNR) recordings (red flashes at 5 cd s/m 2 stimulus intensity on blue rod saturating background) and subjective measures of retinal sensitivity (mean deviation [MD] via 30‐2 automated visual fields) and structural metrics (both ganglion cell complex [GCC] and retinal nerve fiber layer [RNFL] thickness from optical coherence tomography [OCT] scans). Results PERG P50 amplitudes were similar across controls, carriers, and LHON affected patients. P50 implicit times were significantly reduced in LHON affected patients (CHECKS: 45.8 ± 1.1 ms; BARS: 43.5 ± 0.8 ms; n = 32) compared to controls (CHECKS: 49.3 ± 0.5 ms; BARS: 48.1 ± 0.4 ms; n = 72). N95 amplitudes elicited by the checkerboard stimulus were significantly reduced and implicit times significantly increased in LHON affected patients (−3.4 ± 0.4 µV; 93.6 ± 2.2 ms; n = 32) compared to controls (−5.9 ± 0.5 µV; 85.3 ± 0.8 ms; n = 72). No differences were seen in PERG signals between control or LHON affected patients and carriers. Although PERG parameters were significantly different in LHON affected patients, the measurements were not correlated with PhNR signals, MD and RNFL thickness in all four quadrants around the optic disc. On the other hand, PhNR amplitudes, which were significantly reduced in LHON affected (−16.3 ± 3.4 µV; n = 32) and in carriers (−21.8 ± 3.0 µV; n = 30) compared to controls (−34.2 ± 2.5 µV; n = 28), were correlated with MD (r = −0.611, p < 0.0005; n = 28), average GCC (r = −0.618, p < 0.0001; n = 32) and average RNFL thickness (r = −0.553, p < 0.001; n = 31) in affected patients. Conclusions Significant differences in PERG recordings were measured between control and LHON affected patients. However, no significant differences were seen in carriers and PERG metrics were not correlated with functional PhNR parameters and other subjective and objective measurements tested. Our results suggest that PERG may not be as sensitive as PhNR to discriminate different levels of RGC dysfunction between LHON affected patients and carriers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".