Impaired lung function and serum leptin in men and women with normal body weight: a population based study
Bibliographic record
Abstract
BACKGROUND: Impaired lung function is a risk factor for cardiovascular morbidity. Whether circulating factors are responsible for this association is unknown. A study was undertaken to determine whether leptin, a hormone that can promote atherothrombosis, is raised in individuals with impaired lung function. METHODS: Data from non-obese participants in the Third National Health, Nutrition, and Examination Survey (n=2808) were analysed to determine the relationship between circulating leptin levels and forced expiratory volume in 1 second (FEV(1)) values divided into quintiles (quintile 1, FEV(1) predicted < or =85.2%; quintile 2, 85.3-94.3%; quintile 3, 94.4-101.4%; quintile 4, 101.5-110.0%; and quintile 5, > or =110.1%). RESULTS: Serum leptin levels changed along the FEV(1) gradient. The highest leptin levels were found in quintile 1 (geometric mean (GM) 5.42; interquartile range (IQR) 3.00-9.60 fg/l) and the lowest in quintile 5 (GM 4.94; IQR 2.80-9.10 fg/l). Adjustments for age, body mass index, and other confounders strengthened this relationship. Compared with quintile 5, the odds of having an increased serum leptin level in quintiles 1, 2, 3, and 4 were 2.26 (95% confidence interval (CI) 1.54 to 3.31), 2.20 (95% CI 1.52 to 3.17), 1.46 (95% CI 1.01 to 2.09), and 1.28 (95% CI 0.90 to 1.83), respectively. CONCLUSION: Individuals with impaired lung function have raised serum leptin levels. Leptin may play a role in the pathogenesis of cardiovascular morbidity and mortality related to impaired lung function.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".