Stronger control of eating 3 months after sleeve gastrectomy predicts successful weight loss outcomes at one year
Bibliographic record
Abstract
Background: Weight loss response to sleeve gastrectomy (SG) is variable and predicting the effectiveness of surgery is challenging and elusive. The aim of our study was to assess and quantify the association between eating control and weight loss outcomes and identify the control of eating (CoE) attributes during the early postoperative period that might predict good vs. poor response to SG at one year. Methods: A prospective longitudinal cohort study using the Control of Eating Questionnaire (CoEQ) was designed as a series before and at 3-, 6-, and 12-months post-SG. Primary outcomes were changes in CoE attributes and percent of total weight loss (%TWL) 12-months post-surgery. Subjects were categorized based on %TWL as good (GR, ≥25 %) or poor responders (PR, <25 %). A receiver operating characteristic and logistic regression analyses were performed. Results: [range 35.2-66.3]) who completed the CoEQ at all four timepoints. The "Difficulty to control eating" score at 3 months revealed the highest area under the curve (AUC) (AUC 0.711; 95%CI 0.524-0.898; p=0.032). In a trade-off between a high Youden index and high sensitivity, the "Difficulty to control eating" score of 7 at 3 months was identified as the optimal cut-off for distinguishing between GRs and PRs. Score ≤7 at 3 months was strongly independently associated with a successful weight loss target of 25%TWL at one-year post-SG (Relative Risk 4.43; 95%CI 1.06-18.54; p=0.042). Conclusion: "Difficulty to control eating" score at 3 months post-SG is an independent early predictor of optimal response (achieving a successful TWL target of ≥25 % at one-year post-SG). Our results support the utility of this easy-to-administer validated tool for predicting the effectiveness of SG and may assist in identifying individuals with suboptimal response early and helping them with interventions to attain optimal weight loss targets.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 teacher head, 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".