Assessment of laparoscopic working space in guinea pigs (Cavia porcellus) undergoing carbon dioxide insufflation at different intra-abdominal pressures
Bibliographic record
Abstract
OBJECTIVE: To evaluate pneumoperitoneal volumes (laparoscopic working space) in guinea pigs (Cavia porcellus) undergoing pneumoperitoneum via carbon dioxide insufflation at different intra-abdominal pressures (IAPs) (4, 6, and 8 mm Hg) and recumbencies (dorsal, right lateral, and left lateral). ANIMALS: Six 3- to 4-month-old sexually intact female Hartley guinea pigs. PROCEDURES: Guinea pigs were anesthetized, intubated, and had an abdominal insufflation catheter placed. A baseline abdominal CT scan was performed. Guinea pigs underwent insufflation, with each IAP given in a random order for 10 to 15 minutes with a washout period of 5 minutes between pressures. Abdominal CT scans were acquired at each IAP and at each recumbency. Pneumoperitoneal volumes were calculated using software. RESULTS: Increases in IAP increased working space significantly (P < .001). The 6- and 8-mm Hg pressures increased working space from 4 mm Hg by 7.3% and 19.8%, respectively. Recumbent positioning (P = .60) and body weight (P = .73) did not affect working space. Order of IAP had a significant (P = .006) effect on working space. One of the guinea pigs experienced oxygen desaturation and bradycardia at 6- and 8-mm Hg IAP. CLINICAL RELEVANCE: Although an increased working space occurred at 6 and 8 mm Hg compared to 4 mm Hg, further research is needed concerning the cardiovascular effects of pneumoperitoneum in guinea pigs to determine whether those higher IAPs are safe in this species. An IAP of 6 mm Hg can be considered for laparoscopic cannula placement, followed by a lower IAP for laparoscopic procedures.
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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".