PATHOGNOMONIC (DIAGNOSTIC) ERGs A Review and Update
Why this work is in the frame
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Bibliographic record
Abstract
In Brief Purpose: To review three inherited retinal disorders associated with diagnostic or pathognomonic electroretinogram (ERG) abnormalities: cone dystrophy with supernormal rod ERG (KCNV2), enhanced S-cone syndrome (NR2E3), and bradyopsia (RGS9/R9AP). Methods: A review of clinical details, genetic basis, and electrophysiological features in these disorders and a brief summary of the standard and nonstandard ERG techniques required to identify the disorders. Results: The electrophysiological features in each of these three disorders are pathognomonic such that the responsible gene can be specified. The results from nonstandard electrophysiological testing in excess of international standards are necessary to describe the pathognomonic changes in cone dystrophy with supernormal rod ERG and bradyopsia. The clinical phenotype in the disorders can be variable. Mutations in NR2E3 may additionally be associated with phenotypes other than enhanced S-cone syndrome. Conclusion: Characteristic ERG changes enable the diagnosis of cone dystrophy with supernormal rod ERG, enhanced S-cone syndrome, and bradyopsia and accurate genetic screening. This review highlights the need for additional nonstandard ERGs to make the diagnosis in two of these disorders. Pathognomonic electroretinogram abnormalities, that is, changes that are specific for both a diagnosis and the responsible genetic defect, are found in only three inherited retinal disorders: “cone dystrophy with supernormal rod electroretinogram” (KCNV2), “enhanced S-cone syndrome” (NR2E3), and “bradyopsia” (RGS9/R9AP). Those disorders are reviewed.
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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) | 0.001 | 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 it