Langerhans' Cell Histiocytosis in the Paediatric Population: Presentation and Treatment of Head and Neck Manifestationsy
Bibliographic record
Abstract
Langerhans' cell histiocytosis (LCH) is a rare paediatric disease of unknown etiology affecting 1 to 5 children per 1 million each year. It is characterized by the idiopathic proliferation of Langerhans' cells. The clinical spectrum of disease is quite varied, ranging from a solitary eosinophilic granuloma to diffuse multisystem involvement. The head and neck is the most common site of involvement, occurring in approximately 60% of LCH patients. Head and neck manifestations are diverse and include skull and temporal bone lesions, cervical lymphadenopathy, and skin rash. Diagnosis can be difficult as these lesions mimic other common conditions seen by the otolaryngologist, including otitis externa, acute mastoiditis, and gingivitis. A retrospective study was carried out to study our centre's experience with LCH over the last 10 years. Twenty-one patients were diagnosed between January 1990 and December 1999. Patient's age at time of diagnosis ranged from 6 days to 14 years. Fifty-seven percent of patients had localized bony lesions; the remaining 43% had diffuse multisystem disease. The head and neck was also the most commonly involved site in our study, affecting 67% of our patients. Presentation and diagnosis of these lesions are discussed in detail. Treatment, complications, and patient outcomes will also be discussed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".