Septo‐optic dysplasia in childhood: the neurological, cognitive and neuro‐ophthalmological perspective
Bibliographic record
Abstract
AIM: We set out to describe 17 patients with septo-optic dysplasia (SOD), focusing on the little-explored neurological, cognitive, and neuro-ophthalmological components. A further aim was to identify possible clinical correlations and phenotypic characteristics within the diagnostic spectrum. METHOD: We collected clinical-instrumental data (from the history, general and neurological examination, developmental assessment, and neuro-ophthalmological, neuroradiological, neurophysiological, and endocrinological evaluations) on nine males and eight females (mean age 34.4mo, SD 31.6; range 4mo-9y 6mo) diagnosed with SOD who were referred to our Centre of Child Neuro-ophthalmology between 1999 and 2010. RESULTS: We observed a heterogeneous clinical spectrum characterized by nervous system, visual, and endocrine dysfunctions; optic nerve involvement was present in all 17 children, midline brain defects in 14, and cortical developmental malformations in seven. Developmental/cognitive delay and relational and communication difficulties were observed in eight and seven children, respectively, and reduced visual acuity and oculomotor dysfunction were observed in all. Pituitary hormone deficiencies were present in nine children. INTERPRETATION: Nervous system involvement emerged as a key feature of SOD. As part of a holistic approach to the disease, particular attention should be paid to this aspect. The emergence of new clinical correlations and correlations between clinical features and three SOD subtypes opens the way for better clarification of this disease and, therefore, more targeted diagnosis, follow-up, and care of affected children.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".