Prospective multicenter studies in pediatric hydrocephalus
Bibliographic record
Abstract
Prospective multicenter clinical research studies in pediatric hydrocephalus are relatively rare. They cover a broad spectrum of hydrocephalus topics, including management of intraventricular hemorrhage in premature infants, shunt techniques and equipment, shunt outcomes, endoscopic treatment of hydrocephalus, and prevention and treatment of infection. The research methodologies include randomized trials, cohort studies, and registry-based studies. This review describes prospective multicenter studies in pediatric hydrocephalus since 1990. Many studies have included all forms of hydrocephalus and used device or procedure failure as the primary outcome. Although such studies have yielded useful findings, they might miss important treatment effects in specific subgroups. As multicenter study networks grow, larger patient numbers will allow studies with more focused entry criteria based on known and evolving prognostic factors. In addition, increased use of patient-centered outcomes such as neurodevelopmental assessment and quality of life should be measured and emphasized in study results. Well-planned multicenter clinical studies can significantly affect the care of children with hydrocephalus and will continue to have an important role in improving care for these children and their families.
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 | 0.019 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".