Activity-related dyspnea in older adults participating in the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
BACKGROUND: Dyspnea is associated with functional impairment and impaired quality of life. There is limited information on the potential risk factors for dyspnea in an older adult population. OBJECTIVES: Among older adults aged 45 to 85 years of age, what sociodemographic, environmental, and disease related factors are correlated with dyspnea? DESIGN: We used cross-sectional questionnaire data collected on 28,854 participants of the Canadian Longitudinal Study of Aging (CLSA). Multinomial regression was used to assess the independent effect of individual variables adjusting for the other variables of interest. KEY RESULTS: The adjusted odds ratios for dyspnea "walking on flat surfaces" were highest for obesity (OR, 5.71; 95%CI, 4.71-6.93), lung disease (OR, 3.91; 95%CI, 3.41-4.49), and depression (OR, 3.68; 95%CI, 3.15-4.29), and were greater than 2 for lower income, and heart disease. The effect of diabetes remained significant after adjusting for sociodemographics, heart disease and BMI (OR, 1.61; 95%CI, 1.39-1.86). Those with both respiratory disease and depression had a 12.78-fold (95%CI, 10.09-16.19) increased odds of exertional dyspnea, while the corresponding OR for the combination of heart disease and depression was 18.31 (95%CI, 13.4-25.01). CONCLUSIONS: In a community sample of older adults, many correlates of dyspnea exist which have significant independent and combined effects. These factors should be considered in the clinical context where dyspnea is out of proportion to the degree of heart and lung disease. Whether or not diabetes may possibly be a risk factor for dyspnea merits further investigation.
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".