Direct-to-Implant Prepectoral Breast Reconstruction: Patient-Reported Outcomes
Bibliographic record
Abstract
BACKGROUND: Direct-to-implant prepectoral breast reconstruction has recently experienced a resurgence in popularity because of its lower levels of postoperative pain and animation deformity. BREAST-Q, a well-validated patient-reported outcomes tool, was used to assess patient satisfaction and quality of life. The goal of this study was to assess patient-reported outcomes at 6-month and 1-year follow-up after direct-to-implant prepectoral breast reconstruction. METHODS: Sixty-nine consented adult patients undergoing a total of 110 direct-to-implant, prepectoral, postmastectomy breast reconstructions completed BREAST-Q questionnaires immediately preoperatively, and at 6 and 12 months thereafter. RESULTS: Mean breast satisfaction decreased nonsignificantly from 61.3 preoperatively to 58.6 at 12 months after reconstruction (p = 0.32). Psychosocial well-being improved nonsignificantly from 67.1 preoperatively to 71.1 at 12-month follow-up (p = 0.26). Physical well-being of the chest was insignificantly different, from 74.4 to 73.3 at 12-month follow-up (p = 0.62). Finally, sexual well-being similarly remained nonsignificantly changed from 60.2 preoperatively, to 59.1 at 12 months (p = 0.80). The use of acellular dermal matrix and postmastectomy radiotherapy did not have any significant effects on patient-reported outcomes. Through regression analysis, neoadjuvant chemotherapy, increased age, and incidence of rippling were found to negatively influence BREAST-Q results. CONCLUSIONS: Patients who underwent direct-to-implant prepectoral breast reconstruction demonstrated an overall satisfaction with their outcomes. As prepectoral breast reconstruction continues to advance and grow in popularity, patient-reported outcomes such as those presented in this study become of paramount importance in practice. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, IV.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".