Battle of the Blocks: Which Pain Management Technique Triumphs in Gender-Affirming Bilateral Mastectomies?
Bibliographic record
Abstract
Background: Gender-affirming mastectomy, performed on transgender men and non-binary individuals, frequently leads to considerable postoperative pain. This pain can significantly affect both patient satisfaction and the overall recovery process. The study examines the efficacy of four analgesic techniques pectoral nerve (PECS) 2 block, erector spinae plane (ESP) block, thoracic wall local anesthesia infiltration (TWI), and systemic multimodal analgesia (SMA) in managing perioperative pain, with special consideration for the effects of chronic testosterone therapy on pain thresholds. Methods: A retrospective analysis was conducted on patients aged 18 - 45 who underwent gender-affirming bilateral mastectomies at a New York City community hospital. The study compared intraoperative and post-anesthesia care unit (PACU) opioid consumption, postoperative pain scores, the interval to first rescue analgesia, and total PACU duration among the four analgesic techniques. Results: The study found significant differences in intraoperative and PACU opioid consumption across the groups, with the PECS 2 block group showing the least opioid requirement. The PACU morphine milligram equivalent (MME) consumption was highest in the SMA group. Postoperative pain scores were significantly lower in the PECS and ESP groups at earlier time points post-surgery. However, by postoperative day 2, pain scores did not significantly differ among the groups. Chronic testosterone therapy did not significantly impact intraoperative opioid requirements. Conclusion: The PECS 2 block is superior in reducing overall opioid consumption and providing effective postoperative pain control in gender-affirming mastectomies. The study underscores the importance of tailoring pain management strategies to the unique physiological responses of the transgender and non-binary community. Future research should focus on prospective designs, standardized block techniques, and the complex relationship between hormonal therapy and pain perception.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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".