Neuro-Ophthalmological Findings in Children and Adolescents with Chronic Ataxia
Bibliographic record
Abstract
Chronic ataxia is a challenging problem in paediatric neurology. It is caused by a multitude of disorders that at least initially have similar or non-specific phenotype. Some of these disorders have associated neuro-ophthalmological signs (N-OS). The aims of this study are to describe the N-OS and their frequencies in general and by disease aetiology in paediatric patients with chronic ataxia. The authors identified 184 patients under age 17 years with chronic ataxia (>2 months duration or recurrent) during 1991-2008 from multiple sources. Diagnoses and N-OS were ascertained following charts review. Mean age (SD) was 15 (7.7) years. Median duration of follow-up was 6.4 years. There were 214 N-OS in 115 patients (median = 2, range = 1-5 N-OS/patient). Strabismus was present in 29.3% of patients, nystagmus 27.7%, impaired smooth pursuit 23.4%, hypometric saccades 10.3%, decreased visual acuity 9.2%, abnormal optic discs 8.7%, abnormal pupillary examination 2.7%, hypermetric saccades 2.2%, impaired ductions 1.6%, and abnormal visual fields in 1.1% of patients. N-OS were reported most commonly among patients with the following disorders (commonest N-OS): hypoxic-ischaemic encephalopathy following birth (strabismus), episodic ataxia (nystagmus), neuronal ceroid lipofuscinosis (abnormal optic discs), neuronal migration disorder (strabismus), ischaemic stroke (nystagmus), Joubert syndrome-related disorders (strabismus), leukodystrophy (nystagmus), Friedreich ataxia (hypometric saccades, impaired smooth pursuit, nystagmus), mitochondrial disease (strabismus, nystagmus), ataxia telangiectasia (impaired smooth pursuit), and Angelman syndrome (strabismus). N-OS occur commonly in children with chronic ataxia. Although non-specific, they vary with disease aetiology, potentially aiding in the assessment of these patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".