Development and pilot evaluation of a quality grading system for paediatric spirometry
Bibliographic record
Abstract
Introduction: The American Thoracic and European Respiratory Societies (ATS/ERS) recommend the use of a quality grading system for spirometry (Culver BH et al. AJRCCM. 2017;196:1463-72), but while different systems have been reported there is no established paediatric standard. Aims: To develop and evaluate a pediatric quality grading index for FVC and FEV1 in paediatric pulmonary function laboratories. Methods: Criteria for a paediatric specific scale were generated by systematic literature review and content expert input (paediatric pulmonologists (n=6), respiratory scientist and pulmonary function technicians (n=4)). An iterative process was used to optimize items in the scale. FEV1 and FVC were graded separately (Figure 1). The grading index was applied to 89 randomly selected tests (subjects aged 5 to 17 years), independently scored by 4 technicians. Agreement was calculated using the most senior technician as the “gold standard”. Results: The majority of tests met or exceeded ATS/ERS acceptability and repeatability criteria by obtaining a Grade A or B for FEV1 (75%) and FVC (61%). Exact agreement for FEV1 and FVC was 91% and 81%, respectively. Interrater agreement (kappa) for FEV1 and FVC was 0.8 and 0.7, respectively. Conclusion: We report pilot data evaluating a novel quality grading system for paediatric spirometry which will need to be validated in a larger sample including longitudinal data in both health and 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 | 0.159 | 0.146 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".