An evaluation of the analgesic effects of meloxicam in addition to epidural morphine/mepivacaine in dogs undergoing cranial cruciate ligament repair.
Bibliographic record
Abstract
The analgesic efficacy of an epidural morphine/mepivacaine combination alone versus epidural morphine/mepivacaine in combination with meloxicam administered prior to the onset of anesthesia was assessed in 20 dogs undergoing cranial cruciate ligament repair. Numerical and visual analog pain scores were performed prior to anesthesia and at 6, 8, 12, 16, and 24 hours after epidural administration by a trained observer, blinded to treatment. An analgesiometer was used to determine the amount of pressure required to produce an avoidance response at the incision site. Animals that received meloxicam demonstrated a trend toward decreased pain scores over all time periods. Visual analog pain scores tended to be lower in dogs receiving meloxicam across all time periods, with a significant interaction between time and visual analog score at 6 and 8 hours (P < 0.05). No dogs receiving meloxicam required rescue analgesia, while 3 of 10 dogs in the epidural only group required rescue analgesia. Administration of meloxicam in addition to epidural morphine plus mepivacaine conveys improved analgesia as compared with epidural alone. Postoperative analgesia is reliably maintained for 24 hours following administration.
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) | 0.001 | 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".