Neurofibromatosis Type 1 in a Pediatric Population: Ste-Justine's Experience
Bibliographic record
Abstract
BACKGROUND: To date, few pediatric series of neurofibromatosis type 1 (NF-1) have been described in the literature even though it is the most frequently encountered phakomatosis. METHODS: We reviewed 987 charts of pediatric patients with a presumptive diagnosis of NF-1 who were evaluated at Ste-Justine hospital from January 1, 1991 to July 31, 2002. Patients who presented with two or more cardinal criteria were diagnosed with NF-1. Clinical and laboratory data were retrospectively collected, including: demographics, neuroimaging and presence or absence of associated symptoms or signs of NF-1. RESULTS: A total of 279 patients were diagnosed with NF-1. The mean age at diagnosis was 3.4 years. Ninety-nine percent of the patients had café au lait spots and 47% had a first degree relative with NF-1. Almost 60 percent (59.6%) of those seen by an ophthalmologist had Lisch nodules. Optic glioma was found in in 14.7%, cutaneous neurofibromas in 38.4%, plexiform neurofibromas in 24.7%, neurofibrosarcoma in 1.8%, learning disabilities in 39%, attention deficit disorder in 40.5%, osseous dysplasias in 7.2%, pseudoarthrosis in 3.6%, precocious puberty in 3.2% and short stature in 17.9%. Magnetic resonance, when performed, showed hyperintense T2 lesions in 87.1% of cases. The mean period of follow-up was 7.4 years. CONCLUSION: Neurofibromatosis type 1 is a multisystemic disorder associated with increased risk of malignancy. It can be diagnosed at a very young age and clinical follow-up is advised. To our knowledge, this is the largest single center study of NF-1 in a pediatric population.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".