Risk Profile of Young Adults with Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
RATIONALE: Chronic obstructive pulmonary disease (COPD) risk profiles have been described in populations consisting of or including older adults, leaving factors associated with COPD in younger adults overlooked. OBJECTIVES: To determine patient profiles of younger adults with COPD. METHODS: A cohort study was conducted using population-based survey data linked to health administrative data from Ontario, Canada, from 2007 to 2018. Younger adults (age 35-55 yr) newly diagnosed with COPD were matched to controls without COPD. Multivariable conditional logistic regression models were used to identify statistically significant predictors of COPD. To contextualize results, the analysis was repeated in older adults. RESULTS: There were 1,094 younger adults newly diagnosed with COPD. In adjusted analysis, previous influenza or pneumonia, higher level of comorbidity, a mental health condition, and a history of asthma independently predicted COPD diagnosis in younger adults. With the exception of mental health conditions, these same variables predicted COPD diagnosis in older adults. However, male sex, lower income, a history of respiratory disease other than asthma, and being overweight or underweight predicted COPD diagnosis in older but not in younger adults. CONCLUSIONS: Having a mental health condition was associated with COPD in younger adults, whereas male sex, lower income, a history of respiratory disease other than asthma, and being overweight or underweight did not. This new knowledge can be used to dispel stereotypes about COPD. They also suggest that different screening criteria should be considered for younger adults.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".