Pneumoperitoneum in Veterinary Laparoscopy: A Review
Bibliographic record
Abstract
Objective: To review the effects of carbon dioxide pneumoperitoneum during laparoscopy, evaluate alternative techniques to establishing a working space and compare this to current recommendations in veterinary surgery. Study Design: Literature review. Sample Population: 92 peer-reviewed articles. Methods: An electronic database search identified human and veterinary literature on the effects of pneumoperitoneum (carbon dioxide insufflation for laparoscopy) and alternatives with a focus on adaptation to the veterinary field. Results: Laparoscopy is the preferred surgical approach for many human and several veterinary procedures due to the lower morbidity associated with minimally invasive surgery, compared to laparotomy. The establishment of a pneumoperitoneum with a gas most commonly facilitates a working space. Carbon dioxide is the preferred gas for insufflation as it is inert, inexpensive, noncombustible, colorless, excreted by the lungs and highly soluble in water. Detrimental side effects such as acidosis, hypercapnia, reduction in cardiac output, decreased pulmonary compliance, hypothermia and post-operative pain have been associated with a pneumoperitoneum established with CO2 insufflation. As such alternatives have been suggested such as helium, nitrous oxide, warmed and humidified carbon dioxide and gasless laparoscopy. None of these alternatives have found a consistent benefit over standard carbon dioxide insufflation. Conclusions: The physiologic alterations seen with CO2 insufflation at the current recommended intra-abdominal pressures are mild and of transient duration. Clinical Significance: The current recommendations in veterinary laparoscopy for a pneumoperitoneum using carbon dioxide appear to be safe and effective.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".