Locally Administered Ketorolac and Bupivacaine for Control of Postoperative Pain in Breast Augmentation Patients
Bibliographic record
Abstract
With recent developments in the field of analgesia, the question arises whether there is a role for placing local anesthetics, nonsteroidal anti-inflammatory drugs, or both into the breast implant pocket. The objective of this study was to test the effectiveness of locally administered intraoperative ketorolac and bupivacaine with epinephrine at reducing pain in the postoperative period. The study was a prospective, randomized, double-blind clinical trial. One hundred consecutive retropectoral breast augmentation patients were enrolled, and informed consent was obtained. A standard anesthetic protocol and surgical procedure were followed. Normal saline, ketorolac alone (30 mg), bupivacaine alone (150 mg), or ketorolac and bupivacaine (30 mg and 150 mg respectively) were placed into the implant pocket before implant insertion. All patients completed the study. The power of this study to detect a 20 percent difference with respect to the primary outcome was 0.90 and confidence intervals of 95 percent were used to determine significance. The primary outcome was pain as measured by the visual analogue pain scale. The secondary outcome was time spent in the recovery room. Intraoperative placement of ketorolac combined with bupivacaine reduced pain in the postoperative period. It did not appear that anesthesiologist, anesthesia time, surgeon, operating room time, difficulty of dissection, breast incision, or implant size had a significant effect on postoperative pain. There was a trend that the ketorolac and bupivacaine patients spent less time in the recovery room and used fewer analgesics postoperatively than the other patients. There were no hematomas requiring reoperation and no complications. Locally administered intraoperative ketorolac and bupivacaine with epinephrine significantly reduced pain in the postoperative period.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".