Perioperative characteristics and long-term outcomes following prophylactic total laparoscopic gastropexy using a novel knotless tissue control device in 44 dogs.
Bibliographic record
Abstract
Objective: To report on operative technique and outcomes following prophylactic total laparoscopic gastropexy (PTLG) using a novel knotless tissue control device (KTCD) in dogs. Animals: This study included 44 dogs. Procedure: Medical records were reviewed, and perioperative data were collected. Right-sided incisional gastropexy was performed using 2 strands of KTCD introduced through a 12-millimeter cannula in a single-incision multi-channeled port. Dog owners were contacted to obtain outcome data. Results: Median age and weight of dogs were 17 mo (6 to 60 mo) and 48.5 kg (14 to 73.3 kg). Median surgical and anesthesia times were 90 min (60 to 150 min) and 195 min (135 to 270 min). Major intraoperative complications were not reported. Follow-up data were available for 40/44 (91%) dogs. Median follow-up time was 522 d (43 to 983 d). Gastric dilatation volvulus (GDV) was not reported in any dog. One dog developed suspected colonic entrapment around the gastropexy that required surgical revision. All owners were satisfied with the procedure and indicated they would repeat the procedure with future pets. Conclusion: The PTLG procedure using novel KTCD in this cohort of dogs was effective at preventing GDV for the duration of follow-up and was associated with low perioperative complication rate and high owner satisfaction. Clinical relevance: This retrospective study reports on operative technique and outcomes associated with KTCD use in PTLG. Our findings warrant prospective evaluation of KTCD use in PTLG.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".