Intraosseous infusion into the skull: potential application for the management of hydrocephalus
Bibliographic record
Abstract
OBJECT: Hydrocephalus results from abnormal cerebrospinal fluid (CSF) volumes or flow patterns. The absorption of CSF is determined largely by pressures within veins and venous sinuses in the head and adjacent to the spine. Most surgical solutions for hydrocephalus involve diversion of excess CSF into alternative absorption sites, and most of these solutions are still suboptimal. The focus of this work has been to recreate more normal CSF absorption into the dural venous sinuses without having to directly access the superior sagittal sinus (SSS). METHODS: Intraosseous skull infusion for the purpose of accessing the SSS and the systemic venous system was tested by experimental skull infusions of tracer fluids into living large animals (14 adult pigs). Compared with control injections into an ear vein, infusions into the skull through specially designed infusion devices had similar systemic absorption characteristics. This suggested that intraosseous skull infusion in a living large animal was successful in gaining access to the SSS and systemic venous system. CONCLUSIONS: This study constitutes the first demonstration of the success of intraosseous skull infusion in gaining rapid access to the systemic venous system and it thus opens the possibility of using this strategy for diversion of CSF back into the intracranial venous system for the treatment of hydrocephalus.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".