Serum adiponectin levels are associated with worse cognitive function in postmenopausal women
Bibliographic record
Abstract
INTRODUCTION: Adiponectin may be a biomarker of cognitive impairment stage, and its clinical progression. In this study we aimed to evaluate the relationship between serum adiponectin levels and cognitive performances in menopausal women, and whether serum adiponectin levels may be differently associated with cognitive performances as compared to overweight/obese subjects. METHODS: We enrolled 188 post-menopausal women, divided into two groups: obese/overweight group (n = 96) and normal weight group (n = 92). After a clinical examination, and laboratory measurements, we assessed cognitive functions by Montreal Cognitive Assessment test (MoCA). RESULTS: A significant and greater decrease in executive/visuo-spatial and in attention functions occurred in obese/overweight group as compared to normal weight group (p< 0.001). A significant positive relationship between serum adiponectin levels, and MoCA Global cognitive function was found. MoCA executive, and MoCA attention functions significantly and positively correlated with serum adiponectin levels. BMI, WHR, and serum adiponectin levels were independently associated with MoCA Global cognitive function, but only serum adiponectin levels were independently associated with MoCA attention. CONCLUSION: A significant positive association may exist between serum adiponectin levels, and better cognitive function in postmenopausal status. The major determinant of attentional capacity was just serum adiponectin levels, and dosage of serum adiponectin levels may be early serum marker of cognitive decline. Therefore, serum adiponectin level has to be used, as early biomarker, to detect cognitive decline, and to support an early prevention.
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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 | 0.001 |
| 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) | 0.001 | 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".