Oncoplastic Breast Reconstruction Complications and Patient-Reported Outcomes
Bibliographic record
Abstract
Introduction: Oncoplastic breast reconstruction (OBR) combines breast conservation treatment with breast reduction/reconstruction and is appropriate for breast cancer patients with macromastia and/or ptosis, who want to avoid mastectomy, and who include breast reduction in their goals. This study's purpose was to evaluate complications and patient-reported outcomes associated with OBR at our institution. Methods: A retrospective chart review was conducted for all consecutive OBR cases from April 2009 to April 2020. Data was extracted from a prospectively maintained database and surgeons’ EMRs. Risk factors for any complication were evaluated by a univariate logistic regression analysis with significance level set at P < 0.05. Postoperative patient satisfaction was evaluated with the validated BREAST-Q 2.0 questionnaire for which raw scores were obtained. Rasch-transformed scores from 0 (worst) to 100 (best) were calculated from the BREAST-Q conversion tables. Results: 81 patients had OBR of whom 22 experienced 25 post-surgical complications. Increasing ipsilateral and contralateral specimen weight and American Society of Anesthesiologists Physical Status Classification System Score (ASA) were significantly correlated with increased odds for any complication. The BREAST-Q questionnaire was completed post-OBR by 37 patients who reported a high degree of satisfaction with physicians, medical, and office staff. Conclusions: OBR is rated well by patients. All complications were Clavien-Dindo 1 and managed with local office-based wound care.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".