Lung function and plasma fibrinogen concentrations in the <scp>N</scp>ewcastle <scp>T</scp>housand <scp>F</scp>amilies birth cohort between age 49 and 51 years
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: A number of studies have suggested inverse associations between lung function and inflammatory markers, including fibrinogen. In this study, we used data from the Newcastle Thousand Families birth cohort to assess the association between contemporaneous markers of lung function and fibrinogen while adjusting for potential confounding factors throughout life. METHODS: At age 49-51 years, complete data on lung function and plasma fibrinogen were available for 380 study members. These data were analysed in relation to each other, adjusted for sex and height, with further adjustment for potential confounders within linear regression models using robust estimates. RESULTS: Forced expiratory volume in 1 s was significantly inversely associated with plasma fibrinogen concentration after initial adjustments for sex and height (beta = -0.12, P = 0.011) and remained so after further adjustments for pack-years of cigarettes smoked and current smoking status. On further adjustment for standardized birthweight and duration breast-fed, the association approached statistical significance (P = 0.051). Adjusting for body mass index (BMI) resulted in a loss of significance (P = 0.09), but an unchanged regression coefficient, while, after adjustment for percent body fat, rather than BMI, the association was no longer significant (P = 0.20) and the coefficient reduced. CONCLUSIONS: The association between lung function and fibrinogen remains after adjustment for potential early-life confounders and smoking. However, it is not independent of contemporaneous measures of adiposity, with evidence of confounding by percent body fat. Further studies, with measures of adiposity, are required to confirm whether associations between markers of inflammation and lung function are due to residual confounding by adiposity.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".