Langerhans cell histiocytosis: A complex recurrent disease
Bibliographic record
Abstract
A six-year-old boy was referred to a paediatric hematologist/oncologist with recurrent, painful skull masses. Skeletal survey and computed tomography revealed lytic lesions in his calvarium (Figure 1) and a silent lesion in his right humerus. Positron emission tomography-computed tomography scan confirmed involvement of these sites. A biopsy of the skull mass showed infiltrates of pathogenic Langerhans cells, staining positive for CD1a, Langerin and S100, and containing Birbeck granules on electron microscopy. Of note, 14 months earlier, the boy had a soft tissue mass removed by surgical curettage from the lateral wall of his left orbit but no adjuvant therapy. The pathology of both lesions was consistent with Langerhans cell histiocytosis (LCH). ... The boy's treatment at this time included vinblastine and prednisone for a year, with regression of all lesions. Three years later, another skull mass appeared and surgical curettage again showed pathogenic Langerhans cells. Meanwhile, he had developed excessive thirst and polyuria. A water deprivation test confirmed diabetes insipidus. A brain magnetic resonance imaging scan showed enhancement and thickening of his infundibular pituitary stalk, suggestive of LCH involvement. In view of this new development, a paediatric endocrinologist became involved in managing the diabetes insipidus and is closely observing any further pituitary complications. Because LCH has the potential to recur despite successful therapies, sometimes with significant sequelae, close supervision by a multidisciplinary care team is essential (1).
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".