Maximal and Partial Expiratory Flow Rates in a Population Sample of 10- to 11-yr-old Schoolchildren
Bibliographic record
Abstract
The effect of volume history on forced expiratory flow rates has been reported to differ between patients with asthma and healthy persons, and it has been hypothesized that the peripheral airway inflammation of patients with asthma may underlie this difference. There are no published data, however, on the distribution of such volume history effects or the relation of these effects to airways disease in children. We obtained combined partial and maximal forced expiratory flow-volume curves on 1,834 children, age 10-11 yr, in eight communities in the United States and Canada. The effect of a deep inhalation on forced expiratory flow rates at low lung volumes was quantitated by the ratio of V (30) during a maximal expiratory maneuver (V (30M)) to V (30) during a partial expiratory maneuver (V (30P)). The V (30M)/V (30P) ratio was slightly higher among girls than boys (1.26 versus 1.18, p = 0.0001) indicating that a deep inhalation increased V (30) slightly more among girls than among boys. The V (30M)/V (30P) ratio was related to neither history of asthma nor to maternal smoking. In contrast, most spirometric indices from either the maximal or the partial expiratory flow-volume curve were lower in association with a history of asthma or a report of maternal smoking. The ratio of FEF(25-75)/FVC was particularly consistent as a measurement that discriminated both of these effects in boys and girls. These results suggest that the measurement of volume history effects offers no benefits for epidemiological studies of childhood respiratory disease whereas spirometric indices such as the FEF(25-75)/FVC ratio are quite sensitive to the effects of asthma and environmental tobacco smoke exposure on the airways.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".