Management of primary ciliary dyskinesia in European children: recommendations and clinical practice
Bibliographic record
Abstract
The European Respiratory Society Task Force on primary ciliary dyskinesia (PCD) in children recently published recommendations for diagnosis and management. This paper compares these recommendations with current clinical practice in Europe. Questionnaires were returned by 194 paediatric respiratory centres caring for PCD patients in 26 countries. In most countries, PCD care was not centralised, with a median (interquartile range) of 4 (2-9) patients treated per centre. Overall, 90% of centres had access to nasal or bronchial mucosal biopsy. Samples were analysed by electron microscopy (77%) and ciliary function tests (57%). Nasal nitric oxide was used for screening in 46% of centres and saccharine tests in 36%. Treatment approaches varied widely, both within and between countries. European region, size of centre and the country's general government expenditure on health partly defined availability of advanced diagnostic tests and choice of treatments. In conclusion, we found substantial heterogeneity in management of PCD within and between countries, and poor concordance with current recommendations. This demonstrates how essential it is to standardise management and decrease inequality between countries. Our results also demonstrate the urgent need for research: to simplify PCD diagnosis, to understand the natural history and to test the effectiveness of interventions.
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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 | 0.018 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".