Nutrition Care for Patients with Weight Regain after Bariatric Surgery
Bibliographic record
Abstract
Achieving optimal weight outcomes for patients with obesity is important to the management of their chronic disease. All interventions present risks for weight regain. Bariatric surgery is the most efficacious treatment, producing greater weight losses that are sustained over more time compared to lifestyle interventions. However, approximately 20-30% of patients do not achieve successful weight outcomes, and patients may experience a regain of 20-25% of their lost weight. This paper reviews several factors that influence weight regain after bariatric surgery, including type of surgery, food tolerance, energy requirements, drivers to eat, errors in estimating intake, adherence, food and beverage choices, and patient knowledge. A comprehensive multidisciplinary approach can provide the best care for patients with weight regain. Nutrition care by a registered dietitian is recommended for all bariatric surgery patients. Nutrition diagnoses and interventions are discussed. Regular monitoring of weight status and early intervention may help prevent significant weight regain.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".