A Randomized Controlled Trial Examining the Effect of Naproxen on Analgesia During the Second Day After Cesarean Delivery
Bibliographic record
Abstract
UNLABELLED: Whereas nonsteroidal antiinflammatory drugs augment spinal morphine on Day l, the analgesia gained by simply combining these drugs with conventional "on request" oral regimens on Day 2 is less clear. In this trial, we randomized 80 women undergoing elective cesarean delivery with spinal morphine (0.2 mg) to receive naproxen (500 mg) or placebo every 12 h after surgery. Both groups received conventional therapy with acetaminophen with codeine (on request) and rescue IM opioids. Incision pain on sitting (IPS), incision pain at rest, uterine cramping, and gas pain were evaluated with visual analog scales (0-100). Worst interval pain (0-10), analgesic use, and side effects were measured over 72 h. At 36 h (primary outcome), naproxen use was associated with reductions in IPS (38.2 +/- 26.0 versus 51.4 +/- 25.7; P = 0.05), incision pain at rest, uterine cramping, and worst interval pain scores. Clinically modest, statistically significant reductions in IPS (P = 0.0001) and opioid use were found over time (P < 0.0l). Reductions in the incidence of inadequate analgesia and improvements in overall pain relief (P = 0.0006) on Day l did not persist on Day 2 (overall pain relief, P = 0.057; inadequate analgesia, 24% naproxen versus 27% controls; P = 1.00). The addition of regular doses of naproxen to conventional oral pain therapy after cesarean delivery leads to reductions in IPS at 36 h and pain over Day 2 but does not reduce the incidence of inadequate analgesia. IMPLICATIONS: This randomized trial suggests that adding regular doses of naproxen to conventional "on request" acetaminophen and codeine therapy provides small reductions in pain on the second day after cesarean delivery. The greatest effects occur at 36 h, when pain peaks.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".