Alternatives to the Gold Standard: A Systematic Review of Profunda Artery Perforator and Lumbar Artery Perforator Flaps for Breast Reconstruction
Bibliographic record
Abstract
INTRODUCTION: Breast reconstruction with the deep inferior epigastric perforator (DIEP) flap is the current gold-standard autologous option. The profunda artery perforator (PAP) and lumbar artery perforator (LAP) flaps have more recently been described as alternatives for patients who are not candidates for a DIEP flap. The aim of this study was to review the survival and complication rates of PAP and LAP flaps, using the DIEP flap as a benchmark. METHODS: A literature search was conducted using PubMed, MEDLINE, Embase, BIOSIS, Web of Science, and Cochrane databases. Papers were screened by title and abstract, and full texts reviewed by three independent blinded reviewers. Quality was assessed using MINORS criteria. RESULTS: Sixty-three studies were included, for a total of 745 PAP, 62 stacked PAP, 187 LAP, and 23,748 DIEP flap breast reconstructions. The PAP (98.3%) had comparable success rate to DIEP (98.4%), and the stacked PAP (88.7%) and LAP (92.5%) success rate was significantly lower (P < 0.0001). The PAP and LAP groups both had a low incidence of fat necrosis. However, the revision rate for the LAP group was 16.1% whereas the PAP group was 3.3%. Donor site wound dehiscence rate was 2.9 in the LAP group and 9.1% in the PAP group. CONCLUSIONS: Profunda artery perforator and DIEP flaps demonstrate very high rates of overall survival. The LAP flap has a lower survival rate. This review highlights the survival and complication rates of these alternative flaps, which may help clinicians in guiding autologous reconstruction technique when a DIEP flap is unavailable.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".