Cigarette Smoking Is Associated with Subclinical Parenchymal Lung Disease
Bibliographic record
Abstract
RATIONALE: Cigarette smoking is a risk factor for diffuse parenchymal lung disease. Risk factors for subclinical parenchymal lung disease have not been described. OBJECTIVES: To determine if cigarette smoking is associated with subclinical parenchymal lung disease, as measured by spirometric restriction and regions of high attenuation on computed tomography (CT) imaging. METHODS: We examined 2,563 adults without airflow obstruction or clinical cardiovascular disease in the Multi-Ethnic Study of Atherosclerosis, a population-based cohort sampled from six communities in the United States. Cumulative and current cigarette smoking were assessed by pack-years and urine cotinine, respectively. Spirometric restriction was defined as a forced vital capacity less than the lower limit of normal. High attenuation areas on the lung fields of cardiac CT scans were defined as regions having an attenuation between -600 and -250 Hounsfield units, reflecting ground-glass and reticular abnormalities. Generalized additive models were used to adjust for age, gender, race/ethnicity, smoking status, anthropometrics, center, and CT scan parameters. MEASUREMENTS AND MAIN RESULTS: The prevalence of spirometric restriction was 10.0% (95% confidence interval [CI], 8.9-11.2%) and increased relatively by 8% (95% CI, 3-12%) for each 10 cigarette pack-years in multivariate analysis. The median volume of high attenuation areas was 119 cm(3) (interquartile range, 100-143 cm(3)). The volume of high attenuation areas increased by 1.6 cm(3) (95% CI, 0.9-2.4 cm(3)) for each 10 cigarette pack-years in multivariate analysis. CONCLUSIONS: Smoking may cause subclinical parenchymal lung disease detectable by spirometry and CT imaging, even among a generally healthy cohort.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".