Neuronavigation and Laparoscopy Guided Ventriculoperitoneal Shunt Insertion for the Treatment of Hydrocephalus
Bibliographic record
Abstract
Hydrocephalus is a common adult neurosurgical condition typically requiring treatment with a cerebrospinal fluid (CSF) shunt, of which the ventriculoperitoneal (VP) shunt is the most common type. Unfortunately, the failure rates of VP shunts are alarmingly high, with up to 50% of patients requiring revision surgery within 2 years. VP shunt failure may occur due to infection, or catheter mispositioning, migration, and occlusion. We undertook a joint neurosurgery and general surgery collaboration in a 7-year prospective non-randomized consecutive quality improvement cohort study to reduce the rates of ventriculoperitoneal (VP) shunt failures in 224 adult patients at a tertiary care institution. The initiative combined the use of electromagnetic stereotactic neuronavigation to guide the placement of the proximal catheter and laparoscopy to place the distal catheter under direct visualization. With laparoscopic assistance, the distal catheter was anchored through a small hole created in the falciform ligament and placed into the right retrohepatic space, free from the omentum, adhesions, or bowel that might obstruct the catheter tip. The surgeries were performed using a shunt infection prevention protocol to reduce the risk of shunt infections. Here, we present an intraoperative video of the surgical procedure. Compliance with shunt infection reduction strategies and the combined utilization of neuronavigation and laparoscopy techniques in adult VP shunt surgery resulted in a 44% reduction in the risk of overall shunt failure. The significant positive impact with regard to shunt-failure-free patient outcomes among patients who underwent VP shunt surgery using this strategy underscores the value associated with the use of these modern intraoperative techniques and cross-specialty collaboration during VP shunt surgery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".