Prevalence and prognosis of CT lung pathology among adults meeting lung function reference population eligibility criteria: a CanCOLD study
Bibliographic record
Abstract
Background: Global Lung Function Initiative (GLI) reference equations are widely used to define lung impairment. The GLI inclusion criteria for ‘healthy’ individuals are limited to non-smokers, without respiratory symptoms or diagnosed respiratory disease. This definition ignores multiple factors which affect lung health. Aim: To describe the likelihood of misclassification in a ‘healthy’ reference population. Methods: Individuals meeting GLI inclusion criteria were identified in the Canadian Cohort of Obstructive Lung Disease (CanCOLD) study. CT scans were graded by radiologists for the presence of emphysema. Demographic and clinical characteristics were compared between misclassified (CT emphysema) and correctly classified (no emphysema) individuals. Results: Of 1,561 CanCOLD participants, 17.7% (n=276, mean age ± SD 66.6 ± 10 years; 38.8% female) met the GLI ‘healthy’ inclusion criteria. Of these, 10.5% (n=29) had CT signs of emphysema. Females, those with higher education, and higher FEV1/FVC z-scores were less likely to be misclassified (Table). The misclassified group had higher risk of death within 6 years (HR 1.37 (95% CI 0.84-2.26)). Results were similar with higher thresholds of emphysema (>0% vs >5%). Conclusion: Although, the small sample size led to wide confidence intervals and non-statistically significant differences between groups, 1 in 10 of those who are considered 'healthy' exhibit some evidence of CT lung pathology, which may lead to underestimation of lung function impairment. erj;66/suppl_69/PA5186/TB1 T1 TB1 Odds Ratio (95% CI) Sex (F) 0.56 (0.22-1.27) FEV1/FVC z-score 0.80 (0.52-1.25) Age 1.01 (0.98-1.06) <=High School 1.0 > High School 0.66 (0.25-2.08)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".