The Versatility of Lateral Chest Wall Perforator Flaps in Immediate and Delayed Breast Reconstruction: Retrospective Study of Clinical Experience with 26 Patients
Bibliographic record
Abstract
Rationale: Lateral chest flaps represent versatile reconstructive options, especially valuable in times of global healthcare resource restriction. In this series, we present our experience with the use of lateral chest wall flaps in both immediate and delayed reconstruction from both breast conserving and mastectomy surgery. Methods: A retrospective cohort study of patients who had undergone a lateral chest wall flap for immediate or delayed breast reconstruction of a lumpectomy or mastectomy defect was performed. Data collected consisted of patient demographics, procedure type, tumor/oncological characteristics, as well as postoperative complications. Findings: Between September 2015 and April 2021, 26 patients underwent breast reconstruction using a lateral chest wall flap. Fifteen patients (58%) underwent immediate reconstruction (9 lumpectomy; 6 mastectomy) and 11 (42%) underwent delayed breast reconstruction. All flaps survived, though 1 patient required partial flap debridement following venous compromise hours after surgery. There were no incidences of hematoma, seroma, infection, or wound healing delay at either the donor site or breast. There was one positive margin which occurred in a mastectomy patient. Significance: This study describes the use of lateral chest wall flaps in a wide variety of reconstructive breast surgery scenarios. This technique can be safely performed in an outpatient setting and does not require microvascular techniques. Review of our outcomes and complications demonstrate that this is a safe and effective option. Our experience is that this is an easy to learn, versatile flap that could be a valuable addition to the surgeon's arsenal in breast reconstruction.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".