Treatment of hydrocephalus following posterior fossa tumor resection: a multicenter collaboration from the Hydrocephalus Clinical Research Network
Bibliographic record
Abstract
Abstract Objective Persistent hydrocephalus following posterior fossa brain tumor (PFBT) resection is a common cause of morbidity in pediatric brain tumor patients, for which the optimal treatment is debated. The purpose of this study was to compare treatment outcomes between VPS and ETV in patients with persistent hydrocephalus following surgical resection of a PFBT. Methods A post-hoc analysis was performed of the Hydrocephalus Clinical Research Network (HCRN) prospective observational study evaluating VPS and ETV for pediatric patients. Children who experienced hydrocephalus secondary to PFBT from 2008 to 2021 were included. Primary outcomes were VPS/ETV treatment failure and time-to-failure (TTF). Results: Among 241 patients, the VPS (183) and ETV (58) groups were similar in age, extent of tumor resection, and preoperative ETV Success Score. There was no difference in overall treatment failure between VPS and ETV (33.9% vs 31.0%, p=0.751). However, mean TTF was shorter for ETV than VPS (0.45 years vs 1.30 years, p=0.001). While major complication profiles were similar, compared to VPS, ETV patients had relatively higher incidence of minor CSF leak (10.3% vs. 1.1%, p=0.003) and pseudomeningocele (12.1% vs 3.3%, p=0.02). No ETV failures were identified beyond 3 years, while shunt failures occurred beyond 5 years. Shunt infections occurred in 5.5% of the VPS cohort. Conclusions ETV and VPS offer similar overall success rates for PFBT-related postoperative hydrocephalus. ETV failure occurs earlier, while susceptibility to VPS failure persists beyond 5 years. Tumor histology and grade may be considered when selecting the optimal means of CSF diversion.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".