Changes in Quality of Alimentation, Anthropometric Measurements, Emotional and Appetite Status of Bariatric Surgery Patients: A Retrospective Cohort Study
Bibliographic record
Abstract
Introduction: Laparoscopic adjustable gastric band (LAGB) operation is one of the bariatric surgery methods used to treat extreme obesity. Objective: This study aimed to evaluate the changes in food tolerance, quality of alimentation, anthropometric measurements, and emotional and appetite status following LAGB. Materials and methods: A retrospective cohort study was conducted with 98 patients, 1 year had passed since LAGB. In this study, no sample selection method was used; all patients who met the inclusion criteria and volunteered participated. The questionnaire form included questions to determine the patients’ demographic information, anthropometric measurements, changing food consumption, pre- and post-operative meal consumption, appetite and emotional status. Quality of Alimentation (QA) reflects patients’ post-operative dietary satisfaction and tolerance. The QA Form was used to evaluate post-operative food tolerance. Results: The average age was 38.61±9.82 years, and the mean QA score was 15.59±4.81. The patients lost an average of 30.80±17.76 kg of body weight from pre-operative to post-operative 1st year, and the percentage of patients’ excessive body weight loss was found to be 54.37±26.42. It was determined that the foods that were most difficult to consume after the operation were red meat, white meat, bread, rice, pasta, and salad, respectively. Conclusions: This study uniquely evaluates food tolerance using the QA Form, offering insights into post-operative dietary challenges. LAGB effectively reduces appetite, promotes weight loss, and has a positive impact on patients’ emotional health.
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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 | 0.001 |
| 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 | 0.000 |
| 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 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".