F.07 Reducing ventricular shunt malfunction in the adult patient
Bibliographic record
Abstract
Background: Treatment of adult patients with hydrocephalus is often undertaken with a ventriculoperitoneal shunt (VPS). Failure rates have been reported as high as 50% in the first year. Methods: A Quality Improvement (QI) model was used to evaluate and modify VPS-insertion techniques to improve outcome. Malfunction was defined as a change in neurological shunt-related function with correlated diagnostic imaging studies. Prospectively collected data from 2012-2015 was reviewed. Results: 146 patients underwent a new VPS insertion. Diagnoses were: normal pressure hydrocephalus 101 patients, acquired hydrocephalus 28 patients and chronic-congenital hydrocephalus 17 patients. 103 patients had traditional insertion of a ventricular catheter using surface landmarks with 2 catheter misplacements requiring surgery. Image guidance with electromagnetic tracking was instituted with 0 catheter misplacements in 43 consecutive patients. 121 patients had traditional minilaparotomy/trocar placement of the peritoneal catheter with 59/121 (49%) experiencing shunt malfunction and 35/59 (59%) experiencing a second malfunction requiring surgery. Laparoscopic insertion of the peritoneal catheter was instituted in 25 consecutive patients with 3 (12%) distal obstructions. Laparoscopy was also used in 13 patients undergoing VPS revision with 2 (15%) experiencing subsequent malfunction. Conclusions: Changes to standard VPS surgical treatment including the addition of image-guidance and laparoscopic surgical techniques were associated with a significant decrease in shunt malfunction requiring surgery.
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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 | 0.000 | 0.000 |
| 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) | 0.003 | 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".