Impact of chronic airflow obstruction in a working population
Bibliographic record
Abstract
Data on the individual and collective impact of chronic airflow obstruction at a population level are scarce. In a nationwide survey, dyspnoea, quality of life and missed working days were compared between subjects with and without spirometrically diagnosed chronic airflow obstruction. Subjects aged > or =45 yrs were recruited in French health prevention centres (n = 5,008). Results of pre-bronchodilator spirometry and questionnaires (European Community Respiratory Health Survey-derived questionnaire and European quality of life five-dimension questionnaire) were collected. Adequate datasets were available for 4,764 subjects aged 60+/-10 yrs (only 2% were aged > or =80 yrs). The prevalence of airflow obstruction (forced expiratory volume in one second/forced vital capacity of <0.70) was 7.5%. The vast majority (93.9%) of cases had not been diagnosed previously. Health status was significantly influenced by dyspnoea. Both were associated with the number of missed working days. Despite mild-to-moderate severity, subjects with chronic airflow obstruction exhibited more dyspnoea, poorer quality of life and higher numbers of missed working days (mean 6.71 versus 1.45 days.patient(-1).yr(-1) in patients without airflow obstruction, for the population with no known heart or lung disease). In conclusion, even mild-to-moderate airflow obstruction is associated with an impaired health status, which represents an additional argument in favour of early detection in chronic obstructive pulmonary disease.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".