Effect of Sarcopenia on Cardiovascular Disease Risk Factors in Obese Postmenopausal Women
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To compare sarcopenic-obese and obese postmenopausal women for risk factors predisposing to cardiovascular disease (CVD) and determine whether there may be a relationship between muscle mass and metabolic risk in obese postmenopausal women. RESEARCH METHODS AND PROCEDURES: In this cross-sectional study, 22 healthy obese postmenopausal women (mean age, 66 +/- 5 years; mean BMI, 27 +/- 3 kg/m(2)) were divided into two groups matched for age (+/-2 years) and fat mass (FM) (+/-2%). Sarcopenia was defined as a muscle mass index of <14.30 kg fat-free mass (FFM)/m(2) (which corresponds to 1 standard deviation below the values of a young reference population), and obesity was defined as an FM of >35% (which corresponds to the World Health Organization guidelines). FM, FFM (measured by DXA), daily energy expenditure (accelerometry), dietary intake (3-day dietary record), and blood biochemical analyses (lipid profile, insulin, glucose, and C-reactive protein) were obtained. Visceral fat mass (VFM) was calculated by the equation of Bertin, which estimates VFM from DXA measurements. RESULTS: Obese women had more FFM (p = 0.006), abdominal FM (p = 0.047), and VFM (p = 0.041) and a worse lipid profile [p = 0.040 for triglycerides; p = 0.004 for high-density lipoprotein (HDL); p = 0.026 for total cholesterol/HDL] than sarcopenic-obese postmenopausal women. Obese women also ingested significantly more animal (p = 0.001) and less vegetal proteins (p = 0.013), although both groups had a similar total protein intake (p = 0.967). DISCUSSION: Sarcopenia seems to be associated with lower risk factors predisposing to CVD in obese postmenopausal women. With the increase in the number of aging people, the health implications of being sarcopenic-obese merit more attention.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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 it