Serum Leptin Levels and the Risk of Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Leptin is a major adipokine that regulates weight balance and energy homeostasis. There is inconsistent evidence linking circulating leptin levels to risk of stroke. We tested the hypothesis that leptin levels are associated with risk of incident stroke in an elderly community based sample. METHODS: Serum leptin levels were assayed in 757 stroke free individuals (mean age, 79 years; 62% women) from the Framingham Original Cohort at the 22nd examination cycle (1990-1994). Incidence of all -stroke and ischemic stroke were prospectively ascertained. RESULTS: During a mean follow up of 10 years, 119 individuals developed stroke (99 ischemic strokes). In multivariable Cox regression models, log leptin levels were not associated with incidence of all -stroke or ischemic stroke (hazard ratios per SD increment in log leptin 0.90 [0.73-1.09] and 0.89 [0.72-1.11], respectively). The results were suggestive for potential effect modification by waist/hip ratio for the association between leptin and stroke (P=0.03). Adjusting for age, sex, and established stroke risk factors, analysis stratified by waist/hip ratio quartiles revealed a lower incidence of first-ever all-stroke and ischemic stroke associated with higher leptin levels among only subjects in the top waist/hip ratio quartile (hazard ratio, 0.64 [0.43, 0.95] versus 0.98 [0.77, 1.25] for incident all-stroke and 0.61 [0.39, 0.95] versus 0.96 [0.74, 1.26] for ischemic stroke). CONCLUSIONS: Leptin levels were not directly related to the risk of incident stroke overall but there was an inverse association with stroke in the top waist/hip ratio quartile. Further investigations are required to confirm these findings and explore possible mechanisms for the observed association.
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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 | 0.002 |
| 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 | 0.001 | 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".