Airway Disease in Children with Primary Ciliary Dyskinesia: Impact of Ciliary Ultrastructure Defect and Genotype
Bibliographic record
Abstract
Abstract Rationale Primary ciliary dyskinesia (PCD) is characterized by impaired mucociliary clearance, recurrent respiratory infections, progressive airway damage, and obstructive lung disease. Although the association of ciliary ultrastructure defect/genotype with the severity of airflow obstruction has been well characterized, their association with airway abnormalities on chest computed tomography (CT) has been minimally evaluated. Objectives We sought to delineate the association of ciliary defect class/genotype with chest CT scores in children with PCD. Methods Cross-sectional analysis of children with PCD (N = 146) enrolled in a prospective multicenter observational study, stratified by defect type: outer dynein arm (ODA), ODA/inner dynein arm (IDA), IDA/microtubular disorganization (MTD), and normal/near normal ultrastructure with associated genotypes. CTs were scored using the MERAGMA-PCD (Melbourne-Rotterdam Annotated Grid Morphometric Analysis for PCD), evaluating airway abnormalities in a hierarchical order: atelectasis, bronchiectasis, bronchial wall thickening, and mucus plugging/tree-in-bud opacities. The volume fraction of each component was expressed as the percentage of total lung volume. The percentage of disease was computed as the sum of all components. Regression analyses were used to describe the association between clinical predictors and CT scores. Results Acceptable chest CTs were obtained in 141 children (71 male): 57 ODA, 20 ODA/IDA, 40 IDA/MTD, and 24 normal/near normal. The mean (standard deviation) age was 8.5 (4.6) years, forced expiratory volume in 1 second (FEV1) percent predicted was 82.4 (19.5), and %Disease was 4.6 (3.5). Children with IDA/MTD defects had a higher %Disease compared with children with ODA defects (2.71% higher [95% confidence interval (CI), 1.37–4.06; P < 0.001]), driven by higher %Mucus plugging (2.35% higher [1.43–3.26; P < 0.001]). Increasing age, lower body mass index, and lower FEV1 were associated with a higher %Disease (0.23%; 95% CI, 0.11–0.35; P < 0.001 and 0.03%; 95% CI, 0.01–0.04; P = 0.008 and 0.05%; 95% CI, 0.01–0.08; P = 0.011, respectively). Conclusions Children with IDA/MTD defects had significantly greater airway disease on CT, primarily mucus plugging, compared with children with ODA defects.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".