Body Contouring Surgery After Bariatric Surgery Improves Long-Term Health-Related Quality of Life and Satisfaction With Appearance
Bibliographic record
Abstract
OBJECTIVE: To examine health-related quality of life (HRQL) and satisfaction with appearance in patients who have undergone bariatric surgery (BS) with or without subsequent body contouring surgery (BCS) in relation to the general population normative for the BODY-Q. BACKGROUND: The long-term impact of BS with or without BCS has not been established using rigorously developed and validated patient-reported outcome measures. The BODY-Q is a patient-reported outcome measure developed to measure changes in HRQL and satisfaction with appearance in patients with BS and BCS. METHODS: Prospective BODY-Q data were collected from 6 European countries (Denmark, the Netherlands, Finland, Germany, Italy, and Poland) from June 2015 to February 2022 in a cohort of patients who underwent BS. Mixed-effects regression models were used to analyze changes in HRQL and appearance over time between patients who did and did not receive BCS and to examine the impact of patient-level covariates on outcomes. RESULTS: This study included 24,604 assessments from 5620 patients. BS initially led to improved HRQL and appearance scores throughout the first postbariatric year, followed by a gradual decrease. Patients who underwent subsequent BCS after BS experienced a sustained improvement in HRQL and appearance or remained relatively stable for up to 10 years postoperatively. CONCLUSIONS: Patients who underwent BCS maintained an improvement in HRQL and satisfaction with appearance in contrast to patients who only underwent BS, who reported a decline in scores 1 to 2 years postoperatively. Our results emphasize the pivotal role that BCS plays in the completion of the weight loss trajectory.
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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 | 0.001 |
| 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) | 0.002 | 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".