Abstract P2064: Changes in Inflammatory Markers Monitored Across Time After Bariatric Surgery in Severely Obese Patients
Bibliographic record
Abstract
Adipose tissue is a higly active endocrine tissue and produce adipokines, peptides produced by adipose tissue and exerting autocrine, paracrine and endocrine function. Objective: to analyze changes (Δ) in serum levels of several adipokines and inflammatory markers in morbidly obese patients (MO) after bariatric surgery (BS) at several follow-up time points. Methods: Fifty-two MO (81% women, 40% hypertensives, age 43.9±8.9 yr, BMI 42.2±5.4 Kg/m 2 , waist circumference 131.6±12.1 cm) were evaluated prospectively before and 1,3,6 and 12 months (m) after BS, with assessment of anthropometric data and serum concentrations of several adipokines and inflammatory markers. BS technique: laparoscopic gastric by-pass (28 of 52) and sleeve gastrectomy (24 of 52). Results: at 12m body weight (-35.7±10.2 Kg) and waist circumference (-27.2±9.4 cm) decreased (p<0.001). Two inflammatory markers, leptin and hsCRP, decreased at 1,3,6 and 12m (p<0,005 for all). Adiponectin and angiopoetin-2 increased from month 3 on. (Table). These Δ were statistically significant when examined by an ANOVA with repeated measures, excepte for adiponectin (p=0.065). After adjusting for age, sex, and BS technique, the BS technique was statistically significant only for ΔhsCRP (p=0.035). Pearson correlations were explored. There were no statistically significant correlation between Δ body weight or Δ waist circumference with changes of any of these markers at any follow-up time point. Conclusions: there is a decrease in inflammatory markers 1 m after BS in MO patients with progressive decrease throughout 12 m. These changes are independent of the BS technique and of Δ in body weight and waist circumference.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".