Increasing incidence of optic nerve hypoplasia/septo-optic dysplasia spectrum: Geographic clustering in Northern Canada
Bibliographic record
Abstract
INTRODUCTION: Owing to the shared embryonic origin, defects in development of optic nerves are often seen in conjunction with defects affecting the surrounding brain and pituitary gland. Optic nerve hypoplasia (ONH) and septo-optic dysplasia (SOD) represent a clinical spectrum associated with visual, pituitary and severe central nervous system structural abnormalities (SODplus). Based on changing clinical patterns, our primary objective was to examine trends in annual incidence of ONH/SOD and geographical clustering in Manitoba. METHODS: This was a retrospective 1996 to 2015 chart review with extraction of anthropometric measures, radiologic findings, parental characteristics, endocrinopathies and neurologic symptoms from all involved in care. Postal codes were used to assign map co-ordinates and identify relevant census-based deprivation indices. RESULTS: Ninety-three children were identified in our catchment area; Poisson regression confirmed a striking 1.11-fold annual increase (95% confidence interval 1.07 to 1.16) or ~800% over two decades. The annual incidence (averaged 2010 to 2014 chart data) reached 53.3 per 100,000, affecting 1 in 1875 live births. Most (~55%) had SODplus. Common presenting features were hypoglycemia, nystagmus, seizures and developmental delay; 40% had hormone deficiencies; 80% had reduced visual acuity, typically bilateral. Many were premature with young, primiparous mothers. Unhealthy maternal lifestyles and severe material deprivation were noted. There was disproportionate clustering in individuals from Northern Manitoba at three times the average provincial rate. CONCLUSION: We noted a dramatic rise in the annual incidence of ONH/SOD, which was strongly associated with poverty and northern communities. The pattern was consistent with environmental or nutritional etiologies. Many children were severely affected with increased morbidity and health care burdens.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".