Prospective Study of Outcomes after Reduction Mammaplasty: Long-Term Follow-Up
Bibliographic record
Abstract
BACKGROUND: The purpose of this prospective study was to determine whether the beneficial effects of reduction mammaplasty are maintained over the long term in a Canadian population and to determine whether reduction mammaplasty facilitates weight loss in the overweight patient. METHODS: The Short Form-36, Rosenberg Self-Esteem Scale, and Symptom Inventory Questionnaire were used to assess 57 patients preoperatively and postoperatively at 6 months and 21.5 months. Surgeons completed preoperative, operative, and postoperative patient assessment forms to collect anthropometric, procedural, and postoperative complication data. RESULTS: Stable and significant improvements were found in all three outcomes questionnaires when compared preoperatively and 6 and 21.5 months postoperatively. The Short Form-36 indicated significant improvements (p < 0.05) in seven of the eight health status domains and the physical summary score, suggesting that the procedure primarily benefits physical aspects of health. Scores also improved on the Rosenberg Self-Esteem Scale (p < 0.0001) and symptoms improved on the Symptom Inventory Questionnaire (p < 0.0001) in patients 6 and 21.5 months after reduction mammaplasty. The patients had significant health deficits preoperatively compared with the normal population. Preoperative mean Short Form-36 scores were significantly lower in several areas (p < 0.005). The health deficits were eliminated at 6 months and showed a normalization effect at 21.5 months. Patients with a body mass index greater than 27 kg/m (n = 26; 1 kg = 2.2 lbs.) showed a significant decrease in weight and body mass index at long-term follow-up at 21.5 months postoperatively (p < 0.003). CONCLUSIONS: The long-term results of reduction mammaplasty indicate that this procedure is an effective method to reduce or alleviate both physical and psychological symptoms associated with macromastia. This study shows that this procedure should be covered under Canadian medical insurance plans.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".