Clinical Features of Childhood Primary Ciliary Dyskinesia By Genotype and Ultrastructural Phenotype
Bibliographic record
Abstract
RATIONALE: The relationship between clinical phenotype of childhood primary ciliary dyskinesia (PCD) and ultrastructural defects and genotype is poorly defined. OBJECTIVES: To delineate clinical features of childhood PCD and their associations with ultrastructural defects and genotype. METHODS: A total of 118 participants younger than 19 years old with PCD were evaluated prospectively at six centers in North America using standardized procedures for diagnostic testing, spirometry, chest computed tomography, respiratory cultures, and clinical phenotyping. MEASUREMENTS AND MAIN RESULTS: Clinical features included neonatal respiratory distress (82%), chronic cough (99%), and chronic nasal congestion (97%). There were no differences in clinical features or respiratory pathogens in subjects with outer dynein arm (ODA) defects (ODA alone; n = 54) and ODA plus inner dynein arm (IDA) defects (ODA + IDA; n = 18) versus subjects with IDA and central apparatus defects with microtubular disorganization (IDA/CA/MTD; n = 40). Median FEV1 was worse in the IDA/CA/MTD group (72% predicted) versus the combined ODA groups (92% predicted; P = 0.003). Median body mass index was lower in the IDA/CA/MTD group (46th percentile) versus the ODA groups (70th percentile; P = 0.003). For all 118 subjects, median number of lobes with bronchiectasis was three and alveolar consolidation was two. However, the 5- to 11-year-old IDA/CA/MTD group had more lobes of bronchiectasis (median, 5; P = 0.0008) and consolidation (median, 3; P = 0.0001) compared with the ODA groups (median, 3 and 2, respectively). Similar findings were observed when limited to participants with biallelic mutations. CONCLUSIONS: Lung disease was heterogeneous across all ultrastructural and genotype groups, but worse in those with IDA/CA/MTD ultrastructural defects, most of whom had biallelic mutations in CCDC39 or CCDC40.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".