A Prospective Study of Patients Undergoing Breast Reduction Surgery: Health-Related Quality of Life and Clinical Outcomes
Bibliographic record
Abstract
BACKGROUND: This study assessed the health-related quality of life experienced by breast reduction patients using four reliable and validated health-related quality-of-life measures. METHODS: Consecutive patients with breast hypertrophy completed the Health Utilities Index Mark 2, the Health Utilities Index Mark 3, and the Breast Reduction Assessment Value and Outcomes instruments (the Short Form 36, the Multidimensional Body-Self Rating Questionnaire Appearance Assessment, and the Breast-Related Symptom Questionnaire) at 1 week and 1 day before surgery and at 1, 6, and 12 months after surgery. RESULTS: For the 52 patients in the study, mean scores for all quality-of-life instruments increased from the preoperative assessments to the postoperative assessments. The mean quality-adjusted life years gained per patient because of the surgery was 0.12 during the 1-year follow-up period. There was a positive relationship (p < 0.001) between breast resection weight and body mass index. However, body mass index and tissue resection weight were not significantly associated with Health Utilities Index Mark 3 change scores (p > 0.05). CONCLUSIONS: Patients who undergo breast reduction experience an important improvement in health-related quality of life according to four established measures. The improvement is most noticeable between 1 day before surgery and 1 month after surgery, after which it stabilizes for up to 1 year. The health-related quality-of-life effect of the surgery translates into an expected lifetime gain of 5.32 quality-adjusted life years, which is equivalent to each patient living an additional 5.32 years in perfect health. The authors conclude that there is no justification for the ongoing restriction or denials of third-party payments based on body mass index.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".