Reference Equations for Spirometry in the Canadian Population
Bibliographic record
Abstract
RATIONALE: Spirometry plays a major role in the diagnosis and assessment of severity of lung disease. Determining which lung function values are normal and which are below the lower limit of normal depends on reference equations derived from an appropriate population. OBJECTIVES: The purpose of this study was to derive spirometric reference equations for the Canadian population. METHODS: The Canadian Health Measures Survey consisted of a respiratory questionnaire, urinary cotinine measurements, and spirometry performed in the sitting position with rigorous quality control standards. Of the 16,606 respondents between 6 and 79 years of age, 11,145 were eliminated for positive responses to the respiratory questionnaire, tobacco exposure, or inability to provide high-quality spirograms. Of the remaining 5,461, roughly half were less than 18 years of age. Quantile regression was used to derive predictive (median) and lower limit of normal equations for males and females for FEV1, FVC, and FEV1/FVC ratio for those with ages greater and less than 18 years. MEASUREMENTS AND MAIN RESULTS: The resulting equations were compared with those from the Global Lung Initiative (GLI) and National Health and Nutrition Examination Survey (NHANES) III by using an ideal subject on the 50th percentile for height and between the ages of 6 and 79 years; the comparison showed minor and inconsistent discrepancies among the predictive equations. A plot of residuals (predicted minus measured value for each subject) suggested a marginally better fit compared with the GLI and NHANES III equations, although differences among the equations were small and unlikely to have any clinical significance. CONCLUSIONS: This study provides spirometric reference equations for the Canadian population that were measured under the recommended clinical conditions and with rigorous quality control.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".