EP236 Effectiveness of regional anesthesia in the perioperative management of gender-affirming surgeries: A systematic review
Bibliographic record
Abstract
Background and Aims Transition-related surgery (TRS) is an effective treatment for gender dysphoria, but the perioperative analgesic management of transgender patients may be complicated by higher rates of mood and substance use disorders. Regional anesthesia techniques reduce pain severity and opioid requirements, thereby improving postoperative recovery. However, little is known regarding the effectiveness of regional anesthesia techniques for transgender patients undergoing TRS. Methods A literature search was performed using Medline, Embase, Cochrane, and CINAHL databases. Original studies describing regional anesthesia approaches for patients undergoing TRS were included. The primary outcomes were pain scores and opioid requirements on the first postoperative day (POD1). Due to the heterogeneity of interventions and outcomes, findings underwent qualitative synthesis without meta-analysis. Results Of 1652 studies identified, eight met criteria for inclusion. Three studies described chest surgery, comprising 201 patients of whom 84% were transgender men undergoing mastectomy with pectoralis blocks or local instillation anesthesia devices. The remaining five studies described genital surgery, comprising 50 patients of whom 56% were transgender women undergoing vaginoplasty with lumbosacral erector spinae plane blocks or epidural anesthetics. Overall, the eight studies broadly ascribed benefits to nerve blocks. Few studies directly compared regional and non-regional anesthesia; however, these studies unanimously reported lower pain scores and opioid requirements on POD1 with nerve blocks compared to none. Furthermore, anesthetic complications were rare among included studies. Conclusions Regional anesthesia for TRS is understudied, which may be attributable to pervasive marginalization of transgender individuals. However, the limited existing literature does support regional anesthesia techniques as an effective option for TRS.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".