Nipple-areolar Complex Reconstruction following Postmastectomy Breast Reconstruction
Bibliographic record
Abstract
BACKGROUND: Nipple-areola complex (NAC) reconstruction occurs toward the final stage of breast reconstruction; however, not all women follow through with these procedures. The goal of this study was to determine the impact of the health state burden of living with a reconstructed breast before NAC reconstruction. METHODS: A sample of the population and medical students at McGill University were recruited to establish the utility scores [visual analog scale (VAS), time trade-off (TTO), and standard gamble (SG)] of living with an NAC deformity. Utility scores for monocular and binocular blindness were determined for validation and comparison. Linear regression and Student's t test were used for statistical analysis, and significance was set at P < 0.05. RESULTS: There were 103 prospective volunteers included. Utility scores (VAS, TTO, and SG) for NAC deformity were 0.84 ± 0.18, 0.92 ± 0.11, and 0.92 ± 0.11, respectively. Age, gender, and ethnicity were not statistically significant independent predictors of utility scores. Income thresholds of <$10,000 and >$10,000 revealed a statistically significant difference for VAS (P = 0.049) and SG (P = 0.015). Linear regression analysis showed that medical education was directly proportional to the SG and TTO scores (P < 0.05). CONCLUSIONS: The absence of NAC in a reconstructed breast can be objectively assessed using utility scores (VAS, 0.84 ± 0.18; TTO, 0.92 ± 0.11; SG, 0.92 ± 0.11). In comparison to prior reported conditions, the quality of life in patients choosing to undergo NAC reconstruction is similar to that of persons living with a nasal deformity or an aging neck requiring rejuvenation.
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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 | 0.003 |
| 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".