Long-Term Lung Function and <i>Pseudomonas aeruginosa</i> Infection in Genotyped Primary Ciliary Dyskinesia
Bibliographic record
Abstract
Abstract Rationale Primary ciliary dyskinesia (PCD) is a rare genetic disorder characterized by progressive lung disease. Pseudomonas aeruginosa is a major pathogen in this disease and is known to impact lung function. Previous genotype–phenotype studies have been limited by cross-sectional designs, isolated adult or pediatric populations, small numbers, or short follow-up durations. Objectives We aimed to explore long-term lung function in PCD grouped by genotypes and ultrastructural defects, considering the influence of P. aeruginosa. Methods In this retrospective observational study, we analyzed 43 years of spirometry and 20 years of microbiology data. Using linear mixed-effects models, we estimated forced expiratory volume in 1 second z-score trends and compared them at ages 10, 25, and 50 years, whereas generalized estimating equations were used to assess P. aeruginosa prevalence between groups. In a secondary analysis, we matched spirometry and microbiology samples to evaluate the influence of P. aeruginosa on lung function. Results We included 127 genotyped patients, 6,691 spirometry measurements, and 10,082 microbiology samples. CCDC39 and CCDC40 variants showed early-onset and sustained decline in lung function, whereas DNAH11 and HYDIN variants demonstrated relative stability. Lung function in the proximity of positive P. aeruginosa cultures was on average 0.06 z-score lower. Despite this, differences between groups remained largely unaffected by P. aeruginosa. Conclusions Long-term lung function in PCD follows discrete genotype-specific profiles and appears independent of P. aeruginosa infection. We confirm and extend previous findings of CCDC39 and CCDC40 as variants associated with early-onset severe lung function impairment persisting in the long term.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".