SWK-08. DELAYED DIAGNOSIS OF CENTRAL NERVOUS SYSTEM (CNS) TUMORS IN CHILDREN: PERSPECTIVE FROM THE FRONTLINE
Bibliographic record
Abstract
Abstract Delayed diagnosis of CNS tumors in children is well documented, partially due to challenges in recognizing rare diagnoses. Our objective was to describe Canadian family physicians’ attitudes and confidence in diagnosing and managing pediatric CNS tumors. A standardized questionnaire was administered at a Canadian national family physicians’ conference. Items were based on observations from our institutional study of prediagnostic symptomatic interval in pediatric CNS tumors. 449 surveys were completed. 302/443 (68%) physicians practice in cities. 153/447 (34%) report encountering parents that inquire about their children having brain tumors. 261/449 (58%) have not managed a pediatric brain tumor. 153/447 (34%) report they are not confident, 255/447 (57%) somewhat confident and 39/447 (9%) confident in managing a suspected brain tumor in a stable child. 259/447 (58%) would refer directly to a hospital/specialist. The reported median time for suspicion of a brain tumor was 8–14 days for children with vomiting and/or headache and 1 day for children with seizure and/or ataxia. 410/447 (97%) report not knowing any guidelines to help with management. 235/447 (53%) suggested barriers they experience to include 52/235 (22%) wait times for imaging/specialists, 37/235 (16%) geographical location of the child, 27/235 (12%) knowledge, 25/235 (11%) access to imaging/specialist, and 15/235 (6%) patient-related factors or system barriers, and 8/235 (3%) specialist attitudes. 68/235 (29%) identified no barriers in their practice. This study provides insight into family physicians’ perceived challenges and barriers in diagnosing and managing new suspected pediatric CNS tumors. Educational effort and overcoming systemic perceived barriers may increase physicians’ confidence.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".