The effect of laparoscopy on intracranial pressure as measured by optic nerve sheath diameter: A review.
Bibliographic record
Abstract
Laparoscopic surgery has many benefits over open surgery including lower complication rates, and shorter duration and lower cost of hospitalization. However, recent human literature suggests laparoscopy and carbon dioxide insufflation can result in intracranial hypertension. Invasive monitoring of intracranial pressure is not routinely performed in veterinary medicine, and ultrasonographic evaluation of the optic nerve sheath has been employed as an indirect measure of intracranial pressure in many species. The optic nerve sheath is continuous with the meninges of the brain and becomes distended with intracranial hypertension. Optic nerve sheath diameter is a reliable and consistent measure of intracranial pressure and has been utilized in humans to evaluate patients for intracranial hypertension secondary to laparoscopy and capnoperitoneum. No thorough evaluation of the effects of laparoscopy on intracranial pressure has been performed in dogs. Ultrasonographic evaluation of the optic nerve sheath is a safe, non-invasive, and inexpensive procedure that may allow for the evaluation of intracranial pressure without the need for invasive monitoring systems. As laparoscopic procedures are performed increasingly often, this review aims to inform the reader on the effects of capnoperitoneum and to facilitate appropriate patient selection, anesthetic considerations, and surgical planning.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".