Outcomes in Subfascial Versus Subglandular Planes in Breast Augmentation: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Breast augmentation is the most commonly performed aesthetic surgery procedure in women worldwide. The use of the subfascial plane has been suggested to decrease the incidence of capsular contracture compared with the subglandular plane, while simultaneously avoiding the complication of animation deformity in the subpectoral plane. The aim of this systematic review and meta-analysis was to compare the adverse outcomes of subfascial vs subglandular planes in breast augmentation. This review was registered a priori on OSF (https://osf.io/pm92e/). A search from inception to June 2023 was performed on MEDLINE, Embase, and CENTRAL. A hand search was also performed. All randomized and comparative cohort studies that assessed the use of the subfascial plane for breast augmentation were included. Outcomes evaluated included the incidences of seroma, hematoma, infection, rippling, capsular contracture, and revision surgery. Ten studies were included in this systematic review. Three randomized controlled trials and 7 comparative cohort studies were used for quantitative synthesis. There was a significant difference favoring subfascial compared with subglandular planes in the incidence of hematoma, rippling, and capsular contracture. All included studies had a high risk of bias. The current evidence suggests that the subfascial plane for breast augmentation decreases the risk of capsular contracture, hematoma, and rippling compared with the subglandular plane. Further randomized evidence with high methodological rigor is still required to validate these findings.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.030 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".