Fat Grafting Versus Implants: Who's Happier? A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Background: Breast implants were first introduced in the 1960s and have long been used for augmentation and reconstructive breast surgery. More recently, fat grafting for breast augmentation has gained popularity due to the ‘natural’ outcome and lack of implant-related complications. The aim of this study was to conduct a systematic review and meta-analysis comparing patient-related outcome measures between fat grafting and implant-based primary augmentation using the validated BREAST-Q questionnaire. Methods: A systematic review of the literature according to the PRISMA guidelines was conducted in PubMed®, Cochrane Library®, EMBASE®, MEDLINE®, and Scopus® databases. Papers were screened by two independent blinded reviewers. Quality was assessed using MINORS criteria. Results: Fourteen studies were included in the meta-analysis representing a total of 81 fat grafting augmentations and 1535 implant augmentations. The average overall patient satisfaction mean post-operative scores were 13.0 points higher in the implant group based on meta-regression (95% CI: 2.4-23.5; P = .016). There was no statistical difference in reported post-operative sexual well-being, psychosocial well-being, or physical well-being BREAST-Q scores. Conclusion: Although implant-based augmentation resulted in higher post-operative overall satisfaction scores, fat grafting remains a highly desirable alternative for augmentation in the right patient. This meta-analysis strongly highlights that careful patient selection and evaluation of patient goals must be assessed when selecting an augmentation method.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.016 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| 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".