Primary Ciliary Dyskinesia: Longitudinal Study of Lung Disease by Ultrastructure Defect and Genotype
Bibliographic record
Abstract
Abstract Rationale In primary ciliary dyskinesia, factors leading to disease heterogeneity are poorly understood. Objectives To describe early lung disease progression in primary ciliary dyskinesia and identify associations between ultrastructural defects and genotypes with clinical phenotype. Methods This was a prospective, longitudinal (5 yr), multicenter, observational study. Inclusion criteria were less than 19 years at enrollment and greater than or equal to two annual study visits. Linear mixed effects models including random slope and random intercept were used to evaluate longitudinal associations between the ciliary defect group (or genotype group) and clinical features (percent predicted FEV1 and weight and height z-scores). Measurements and Main Results A total of 137 participants completed 732 visits. The group with absent inner dynein arm, central apparatus defects, and microtubular disorganization (IDA/CA/MTD) (n = 41) were significantly younger at diagnosis and in mixed effects models had significantly lower percent predicted FEV1 and weight and height z-scores than the isolated outer dynein arm defect (n = 55) group. Participants with CCDC39 or CCDC40 mutations (n = 34) had lower percent predicted FEV1 and weight and height z-scores than those with DNAH5 mutations (n = 36). For the entire cohort, percent predicted FEV1 decline was heterogeneous with a mean (SE) decline of 0.57 (0.25) percent predicted/yr. Rate of decline was different from zero only in the IDA/MTD/CA group (mean [SE], −1.11 [0.48] percent predicted/yr; P = 0.02). Conclusions Participants with IDA/MTD/CA defects, which included individuals with CCDC39 or CCDC40 mutations, had worse lung function and growth indices compared with those with outer dynein arm defects and DNAH5 mutations, respectively. The only group with a significant lung function decline over time were participants with IDA/MTD/CA 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".