Minimal important difference in weight loss following bariatric surgery: Enhancing <scp>BODY‐Q</scp> interpretability
Bibliographic record
Abstract
BODY-Q is a patient-reported outcome measure for comprehensive assessment of outcomes specific to patients undergoing bariatric surgery. The clinical utility of BODY-Q is hampered by the lack of guidance on score interpretation. This study aimed to determine minimal important difference (MID) for assessment of BODY-Q. Prospective BODY-Q data from Denmark and the Netherlands pre- and post-bariatric surgery were collected. Two distribution-based methods were used to estimate MID by 0.2 standard deviations of baseline scores and the mean standardized response change of scores from baseline to 3-years postoperatively. In total, 5476 assessments from 2253 participants were included of which 1628 (72.3%) underwent Roux-en-Y gastric bypass, 586 (26.0%) sleeve gastrectomy, 33 (1.5%) gastric banding, and 6 (0.03%) other surgeries. The mean age was 45.1 ± 10.9 with a mean BMI of 46.6 ± 9.6. Baseline MID ranged from 1 to 4 in health-related quality of life (HRQL) and from 2 to 8 in appearance scales. The mean change of scores ranged from 4 to 5 in HRQL and from 4 to 7 in the appearance scales. The estimated MID for the change in BODY-Q HRQL and appearance scales ranged from 3 to 8 and is recommended for use to interpret BODY-Q scores and assess treatment effects in bariatric surgery.
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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 | 0.019 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".