Analgesic efficacy of intraperitoneal administration of bupivacaine in cats
Bibliographic record
Abstract
Objectives The aim of this study was to evaluate the analgesic efficacy of intraperitoneal (IP) bupivacaine in cats undergoing ovariohysterectomy (OVH). Methods Forty-five cats were included in a randomized, prospective, blinded study after owners' written consent was obtained. The anesthetic protocol included acepromazine-buprenorphine-propofol-isoflurane. A ventral midline incision was made and cats (n = 15/group) were administered either IP saline 0.9% (negative and positive control groups; NG and PG, respectively) or IP bupivacaine (2 mg/kg; bupivacaine group; BG). Cats in the PG received meloxicam (0.2 mg/kg SC). An OVH was performed and postoperative pain was evaluated using a dynamic interactive visual analog scale (DIVAS), the UNESP-Botucatu multidimensional composite pain scale (MCPS) and mechanical nociceptive thresholds (MNT) for up to 8 h after the end of surgery. Postoperative sedation was evaluated using DIVAS. Rescue analgesia was provided with buprenorphine and/or meloxicam. Repeated measures linear models and a Cochran-Mantel-Haenszel test were used for statistical analysis ( P <0.05). Results There was a significant effect of treatment on the number of times rescue analgesia was administered ( P = 0.002) (PG, n = 2, 13%; NG, n = 12, 80%; BG, n = 4, 27%) with the number of rescues being higher in the NG group than in the PG ( P = 0.0004) and BG ( P = 0.02) groups. The DIVAS, MCPS and MNT were significantly different when compared with baseline values at different time points; however, data were not significantly different among groups. Conclusions and relevance Treatments PG and BG produced similar analgesia in terms of pain scores, number of times rescue analgesia was administered and MNT. Based on rescue analgesia, IP administration of bupivacaine provides analgesia in cats after OVH.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".