Spirometric pulmonary function in 3‐ to 5‐year‐old children
Bibliographic record
Abstract
Forced expiratory maneuvers are routinely used in children, 6 years of age and older for the diagnosis and follow-up of respiratory diseases. Our objective was to establish normative data for an extensive number of parameters measured during forced spirometry in healthy 3- to 5-year-old children. Children aged between 3 and 5 years were tested in 11 daycare centers. Usual parameters, including FEV1, FVC, PEF, FEF(25-75), FEF25, FEF50, FEF75, and Aex were measured and analyzed in relation to sex, age, height, and weight. In addition, the same analysis was performed for FEV0.5 and FEV0.75. One hundred sixty-four children were recruited for testing including 87 girls and 77 boys. Thirty-five were 3 years old, 63 were 4 years old, and 66 were 5 years old. Overall, 143 children (87%) accepted to perform the test and 128 children (78%) were able to perform at least two technically acceptable expiratory maneuvers. Analyses using different regression models showed that height was the best predictor for every parameter. In conclusion, the present study confirms that most healthy 3-5 years old children can perform valid forced expiratory maneuvers. In agreement with other studies, we found that height is the most important single predictor of various parameters measured on forced spirometry. The present study is the first to establish normative values for FEV0.75, as well as to demonstrate that Aex can be easily performed in the majority of children aged 3-5 years. These are likely important parameters of lung function in this age range.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".