Patient satisfaction following nipple reconstruction incorporating autologous costal cartilage
Bibliographic record
Abstract
BACKGROUND: Nipple-areolar reconstruction completes postmastectomy breast reconstruction.Many techniques for nipple reconstruction have been described, and each has their advocates and critics.One of the frequent failings of most designs is loss of nipple projection with time.OBJECTIVES: To determine the effect of including autologous costal cartilage on patient satisfaction with their nipple reconstruction.METHODS: Sixty-eight patients were identified who had undergone fishtail flap nipple reconstruction following autologous free flap breast reconstruction between 1990 and 2004.Qualitative questionnaires, using Likert scales, were sent to each patient to specifically assess their satisfaction with their nipple reconstruction.RESULTS: Of 26 respondents (mean ± SEM follow-up period 3.7±3.6years), 13 had undergone nipple reconstruction incorporating costal cartilage banked at the time of initial breast reconstruction, and the other 13 had no cartilage in their nipple reconstructions.While both groups would opt for nipple reconstruction again, patients with cartilage grafts incorporated into their reconstructions had overall satisfaction ratings 1.92 grades higher on average (not significant, P=0.12) than those without.This difference increased to 3.2 grades when the satisfaction of the patient's partner was taken into account (P<0.05).Improved satisfaction corresponded to higher scores for volume, consistency, texture, and particularly for projection and contour of the nipple (P<0.05).Although nipple morphology changed over time, there was a trend toward improved stability in the cartilage group.CONCLUSIONS: Patient satisfaction with nipple reconstruction can be improved by incorporating costal cartilage beneath the skin flaps.Superior contour and projection are sustained over time.
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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 | 0.001 | 0.005 |
| 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) | 0.003 | 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".