Effect of a Preoperative Gabapentin on Postoperative Analgesia in Patients with Inflammatory Bowel Disease Following Major Bowel Surgery: A Randomized, Placebo‐Controlled Trial
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Postoperative pain management for patients with inflammatory bowel disease (IBD) can be challenging. These patients have a high tolerance to pain medication, and relative contraindications to the use of epidural analgesia, limiting the pain management options. We evaluated the effect of a single preoperative gabapentin dose on opioid consumption for patients with IBD undergoing abdominal surgery. Secondary outcomes were postoperative pain scores, opioid-related side effects, and patient's length of hospital stay. METHODS: Following Research Ethics Board approval and informed written consent, patients were randomly allocated into 2 groups receiving either 600 mg of oral gabapentin or placebo 1 hour before the surgery. A blinded anesthesiologist recorded pain scores at rest and movement twice daily for 2 postoperative days. Also recorded were opioid consumption, time of return of bowel function, time to discharge, and opioid-related side effects on the opioid-related symptom distress scale (ORSDS). RESULTS: Seventy-two patients completed the study. The difference in opioid consumption (P = 0.4169) and pain scores measured at rest and movement on all 4 postoperative visits was not statistically significant. There was no significant difference between gabapentin and placebo on all the 11 symptoms reported on the ORSDS. There was a slight increase in length of hospital stay in the placebo group, but the return of bowel function was similar between the groups. CONCLUSIONS: This study examined the effect of a single preoperative administration of gabapentin in patients with IBD undergoing major bowel surgery. Our results suggest a single preoperative oral dose of gabapentin 600 mg does not reduce postoperative pain scores, opioid consumption, or opioid-related side effects.
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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 | 0.006 | 0.022 |
| 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