A placebo-controlled randomized clinical trial of perioperative administration of gabapentin, rofecoxib and their combination for spontaneous and movement-evoked pain after abdominal hysterectomy
Why this work is in the frame
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Bibliographic record
Abstract
Current treatments for post-injury movement-evoked pain are inadequate. Non-opioids may complement opioids, which preferentially reduce spontaneous pain, but most have incomplete efficacy as single agents. This trial evaluates efficacy of a gabapentin-rofecoxib combination following hysterectomy. In addition to IV-PCA morphine, 110 patients received either placebo, gabapentin (1800 mg/day), rofecoxib (50 mg/day) or a gabapentin-rofecoxib combination (1800/50 mg/day) starting 1 h pre-operatively for 72 h. Outcomes included pain at rest, evoked by sitting, peak expiration and cough, morphine consumption and peak expiratory flow (PEF). For placebo, gabapentin, rofecoxib and combination, 24 h pain (100 mm VAS) was: at rest-23.6 (P<0.05 vs. all treatments), 13.8, 14.4 and 12.1; during cough-50.7 (P<0.05 vs. all treatments), 41.5, 44.8 and 30.8; 48 h morphine consumption (mg) was: 130.4 (P<0.05 vs. all treatments), 81.7, 75.6 and 57.2 (P<0.05 vs. gabapentin and rofecoxib) and 48 h PEF (% baseline) was: 63.9 (P<0.05 vs. all treatments), 77.2, 76.7 and 87.5 (P<0.05 vs. gabapentin and rofecoxib). Adverse effects were similar in all groups except sedation which was more frequent with gabapentin. Combination and rofecoxib reduced pain interference with movement, mood and sleep (P<0.05) and combination was superior to gabapentin for all these three (P<0.05). These data suggest that a gabapentin-rofecoxib combination is superior to either single agent for postoperative pain. Other benefits include opioid sparing, reduced interference with movement, mood and sleep and increased PEF suggesting accelerated pulmonary recovery. Future research should identify optimal dose-ratios for this and other analgesic combinations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.003 |
| 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) | 0.000 | 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 it