Effect of bariatric surgery on nutritional and metabolic parameters: does the type of antidepressant medication matter?
Bibliographic record
Abstract
Abstract Purpose Depression is prevalent in patients undergoing bariatric surgery (BSx). Long-term use of antidepressant is associated with weight gain, particularly the use of selective serotonin reuptake inhibitors (SSRIs). Little is known about whether different types of antidepressants affect the response to BSx. The purpose of this study was to determine the relationship between SSRI use and nutritional and biochemical measurements in those with obesity pre-/post-BSx. Methods This is a cross-sectional and prospective cohort study. Patients were enrolled pre-BSx and divided into 3 groups: SSRI, non-SSRI and no antidepressant. Nutritional, biochemical and pharmacological data were collected pre- and 6 months post-BSx. Results Pre-BSx, 77 patients were enrolled: 89.6% female, median age 45 years and body mass index (BMI) of 45.3 kg/m2. 14.3% were taking SSRIs and had a significantly higher BMI (52.1 kg/m2) compared to 62.3% in no antidepressant (46.0 kg/m2) and 23.4% in non-SSRI antidepressants (43.1 kg/m2). At 6 months post-BSx (n = 58), the SSRI group still had significantly higher BMI in comparison to the other two groups. No other significant differences found between groups. Conclusion Despite higher BMI, patients taking SSRI and undergoing BSx had similar responses, based on nutritional and biochemical parameters, to those on non-SSRI or no antidepressants. Level of evidence Level III: Evidence obtained from well-designed cohort or case–control analytic studies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".