Visual acuity of children treated with chemotherapy for optic pathway gliomas
Bibliographic record
Abstract
BACKGROUND: Chemotherapy is the most common primary treatment modality for pediatric optic pathway gliomas (OPGs). Due to the risk of severe visual impairment, visual acuity (VA) has become a clinical parameter of fundamental importance for children with OPGs. Despite this reality, most studies omit crucial information necessary for analysis of the effect of chemotherapy on VA in patients with cerebral gliomas. The principal goal of this study was to determine the immediate and long-term visual outcome of children treated first with chemotherapy for OPGs. PROCEDURE: Retrospective, non-comparative, case series of children with OPGs treated initially with chemotherapy. VA was measured prior to chemotherapy, directly following chemotherapy, as well as at last follow-up. RESULTS: Seven children (14 eyes) were positive for the neurofibromatosis type-1 (NF1) mutation and 10 children (20 eyes) were without the NF1 mutation (sporadic). Three deaths, all in the sporadic cohort, occurred as a result of their OPG. Median follow-up time of survivors was 10.54 ± 4.36 (SD) years. Both NF1 mutation positive and sporadic cohorts had deterioration in VA over time; however, deterioration was only statistically significant in the sporadic population. The percentage of eyes with vision weaker than 20/200 prior to chemotherapy, directly following chemotherapy and at last follow-up grew from 18% to 24% to 38%, respectively. CONCLUSIONS: In both NF1 mutant and sporadic OPGs, VA deteriorated directly following chemotherapy as well as at long-term follow-up. Despite chemotherapy, eyes with severe functional impairment gradually increased over time.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".