A Systematic Review and Meta-analysis of Clinical Outcomes in Autologous Breast Reconstruction Using Internal Mammary Artery Perforators as Recipient Vessels
Bibliographic record
Abstract
Recipient vessel selection is vital for successful autologous free-flap breast reconstruction. Internal mammary artery perforators have gained interest as a recipient vessel option. However, previous studies on their microsurgical safety and efficacy are limited and inconsistent. Thus, we conducted a systematic review and meta-analysis to assess the safety and effectiveness of using internal mammary artery perforators as recipient vessels in breast reconstruction. Methods: The protocol has been previously published in PROSPERO (CRD42020190020). The PubMed, Scopus, Web of Science, and PROSPERO databases were searched. Two independent reviewers evaluated the articles for inclusion in the study. Study quality was assessed using the Newcastle-Ottawa Scale and the MINORS instrument (Methodological Index for Non-Randomized Studies). Results: Of the 361 articles screened, 13 studies were included (313 patients with 318 flaps; 223 unilateral, 31 bilateral, mean average age 51.2 and mean BMI 27.8 ± 1.9). The mean overall success rate was 99.8%, the pooled surgical success rate was 100% [95% confidence interval (CI): 97%-100%], and the overall rate of complications was 11% (95% CI: 7%-18%). The most common complication was vascular-related to microanastomoses, with an incidence of 5% (95% CI: 2%-10%). The fat necrosis rate was 3% (95% CI: 2%-6%). Conclusions: This study verified that internal mammary artery perforator vessels are reliable in breast reconstruction, with a high success rate and a relatively low complication rate. Moreover, in selected microsurgical breast reconstruction patients, internal mammary artery perforators may be the primary recipient vessel choice over the internal mammary artery or thoracodorsal vessels.
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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 | 0.017 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.041 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".