Variation in C-reactive Protein Following Weight Loss in Obese Insulin Resistant Postmenopausal Women: is there an Independent Contribution of Lean Body Mass?
Bibliographic record
Abstract
BACKGROUND: We showed that obese insulin resistant postmenopausal women are characterized by higher lean body mass and elevated C-reactive protein. Although counterintuitive, we hypothesized that losses in muscle mass following caloric restriction and increase in muscle quality will be associated with improvements in glucose homeostasis through decreases in C-reactive protein. OBJECTIVES: To determine 1) if improvements in C-reactive protein concentrations occurs through losses in lean body mass; and 2) if decreases in C-reactive protein levels contribute to improvements in insulin sensitivity. METHODS: 50 postmenopausal women (body mass index>26 kg/m(²)) with impaired glucose disposal (<7.5 mg/kg/min) completed a 6-month caloric restriction program. Outcome measures were: Glucose disposal rate: M value (by hyperinsulinemic-euglycemic clamp), body composition (total, trunk, and appendicluar). LBM and FM by DXA), LBM index (LBM (kg)/height (m(2)), body fat distribution (VAT and SAT by CT scan) and plasma high-sensitive C-reactive protein (hsCRP) and interleukin-6 (Il-6). RESULTS: Significant correlations were observed between Δ hsCRP levels with Δ Il-6 (r=0.33, p≤0.05), Δ total LBM index (r=0.44, p≤0.01), Δ trunk LBM (r=0.38, p≤0.01) Δ SAT (r=0.35, p≤0.05) and ∆ glucose disposal rate (r=- 0.44, p≤0.01). After including all the correlated variables in Stepwise linear regression model, Δ LBM index was the only independent predictor of the reduction in hsCRP levels (R(2)=0.20, p≤0.01). CONCLUSION: Losses in total lean body mass are independently associated with improvements in inflammatory state (CRP levels) in obese postmenopausal women with impaired glucose disposal.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".