Investigation of Abdominoplasty Without General Anesthesia: A Scoping Review
Bibliographic record
Abstract
Introduction: Abdominoplasty is a common aesthetic surgical procedure primarily performed under general anesthesia (GA). However, GA is aerosol-generating and involves extended immobilization associated with systemic complications like venous thromboembolisms (VTEs). There is increasing interest in performing abdominoplasties without GA because of potential lower complication rates and shorter postoperative recovery time. This review sought to summarize all available literature on the safety and outcomes of abdominoplasty performed without GA. Methods: A scoping review was conducted with no date limits in October 2023 encompassing Medline, Embase, Web of Science, and CINAHL. The type of anesthesia was separated into 3 categories: conscious or intravenous (IV) sedation, regional anesthetic blocks (RAB: spinal and epidural), and local anesthesia (direct local infiltration and field blocks). Results: A total of 28 studies were included. Safety data was reported for abdominoplasty alone ( n = 6), with liposuction ( n = 14), or both ( n = 1). The employed anesthesia methods were IV and local ( n = 13), RAB and local ( n = 3), IV and RAB ( n = 2), IV and RAB and local ( n = 2), and IV only ( n = 1). A total of 48 379 patients were identified, with 30 cases of VTEs reported. Two studies reported GA conversion rates between 4.8% and 6.0%. A total of 11 studies assessed abdominoplasty outcomes, highlighting high patient satisfaction and low postoperative pain. The majority of analyzed studies had a “high” or “critical” risk of bias. Conclusion: Our review provides preliminary evidence that performing abdominoplasty without GA is safe and feasible. Additional high-quality studies are necessary to further validate our findings and to develop a standardized approach.
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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 | 0.008 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.016 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".