LINC-10. SIOP PODC ADAPTED TREATMENT GUIDELINES FOR CRANIOPHARYNGIOMA IN LOW- AND MIDDLE-INCOME SETTINGS
Bibliographic record
Abstract
Abstract Pediatric craniopharyngioma is a rare tumor with excellent survival but significant long-term morbidities due to the loco-regional tumor growth or secondary to its treatment. Visual impairment, panhypopituitarism, hypothalamic damage and behavioral changes are amongst the main challenges. This tumor should be managed under the care of a multidisciplinary team to determine the optimum treatment within the available resources. This is particularly important for low middle-income countries (LMICs) where resources are variable. We provide a risk-stratified management guideline for children diagnosed with craniopharyngioma in a resource limited setting based on the service levels describing the facilities and personnel required for management as previously specified by the Pediatric Oncology in Developing Countries (PODC) committee of The International Society of Pediatric Oncology (SIOP). A multi-disciplinary group of neurosurgeons, radiation and pediatric oncologists, radiologists, pediatric endocrinologists and an ophthalmologist with experience in managing children with craniopharyngioma in LMIC setting was formed and carried online meetings to form a consensus guideline. The clinical characteristics (including the visual and endocrine presentations), suggestive radiological features as well as potential treatment options including surgery, radiotherapy and intra-cystic therapies were discussed in depth and in relation to available resources. In addition, hormonal management, pre- and post-operative PICU care and expected future complications related to craniopharyngioma and to follow up these children were discussed and documented in the guideline. We believe this guideline is a useful reference for health care providers in LMIC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.032 | 0.016 |
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".