Clinical and Metabolic Improvement after Bariatric Surgery in Older Adults: A 6-Year Follow-Up
Bibliographic record
Abstract
AIM: Our aim in this study was to assess the clinical and metabolic impact of bariatric surgery in older adults. METHODS: This analytical, observational, longitudinal study was carried out with individuals aged 60 years and older who underwent bariatric surgery after 55 years of age at a specialist center for obesity management located in the Federal District of Brazil. Post-surgery changes in the following parameters from baseline: total body weight, excess weight lost, body mass index (BMI), number of medications, number of comorbidities, and weight regain. Mean values of the variables of interest before and after surgery were compared using the nonparametric Wilcoxon test, Poisson regression and multiple linear regression to test the effect of different variables. RESULTS: Overall, 74 subjects were assessed (78.3% female, mean age 65.8 ± 3.9 years). The mean time from bariatric surgery to assessment was 75.7 months. The mean weight and BMI in the overall sample at baseline was 101.9 ± 17.1 kg and 39.8 ± 4.9 kg/m², respectively. After the procedure, mean weight and BMI were reduced to 75.9 ± 12.9 kg and 29.4 ± 4.1 kg/m², respectively. Reductions were also achieved in mean number of medications used (P<0.001), number of comorbidities (P<0.001), triglyceride levels (P=0.007), and glycated hemoglobin (P=0.02). The mean HDL level increased significantly (P=0.008). CONCLUSION: In this sample, bariatric surgery was not only useful to manage obesity, but also reduced the number of comorbidities and medications used, and was associated with improvement in clinical and laboratory parameters.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".