<p>Exploring the Association Between Emphysema Phenotypes and Low Bone Mineral Density in Smokers with and without COPD</p>
Bibliographic record
Abstract
Rationale: Emphysema and osteoporosis are tobacco-related diseases. Many studies have shown that emphysema is a strong and independent predictor of low bone mineral density (BMD) in smokers; however, none of them explored its association with different emphysema subtypes. Objective: To explore the association between the different emphysema subtypes and the presence of low bone mineral density in a population of active or former smokers with and without chronic obstructive pulmonary disease (COPD). Methods: One hundred and fifty-three active and former smokers from a pulmonary clinic completed clinical questionnaires, pulmonary function tests, a low-dose chest computed tomography (LDCT) and a dual-energy absorptiometry (DXA) scans. Subjects were classified as having normal BMD or low BMD (osteopenia or osteoporosis). Emphysema was classified visually for its subtype and severity. Logistic regression analysis explored the relationship between the different emphysema subtypes and the presence of low BMD adjusting for other important factors. Results: Seventy-five percent of the patients had low BMD (78 had osteopenia and 37 had osteoporosis). Emphysema was more frequent (66.1 vs 26.3%, p =< 0.001) and severe in those with low BMD. Multivariable analysis adjusting for other significant cofactors (age, sex, FEV 1 , and severity of emphysema) showed that BMI (OR=0.91, 95% CI: 0.76– 0.92) and centrilobular emphysema (OR=26.19, 95% CI: 1.71 to 399.44) were associated with low BMD. Conclusion: Low BMD is highly prevalent in current and former smokers. BMI and centrilobular emphysema are strong and independent predictors of its presence, which suggests that they should be considered when evaluating smokers at risk for low BMD. Keywords: emphysema, COPD, low bone mineral density, osteopenia, osteoporosis; smokers
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".