Primary Ciliary Dyskinesia and Neonatal Respiratory Distress
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Primary ciliary dyskinesia (PCD) is a rare inherited disease affecting motile cilia lining the respiratory tract. Despite neonatal respiratory distress as an early feature, diagnosis is typically delayed until late childhood. Our objective was to identify characteristics that differentiate PCD from common causes of term neonatal respiratory distress. METHODS: This was a case-control study. Patients with PCD born after 1994 attending a regional PCD clinic who had a history of neonatal respiratory distress (n = 46) were included. Controls (n = 46), term neonates with respiratory distress requiring a chest radiograph, were randomly selected from hospital birth records and matched on gender, birth month/year, and mode of delivery. Multiple logistic regression was used to determine the association between neonatal characteristics and PCD diagnosis. The diagnostic performance of the best predictive variables was estimated by calculating sensitivity and specificity. RESULTS: PCD cases required more oxygen therapy (39 cases, 29 controls, P = .01), longer duration of oxygen therapy (PCD mean = 15.2 days, control mean = 0.80 days, P < .01), had later onset of neonatal respiratory distress (PCD median = 12 hours, control median = 1 hour, P < .001), and higher frequency of lobar collapse and situs inversus (PCD = 70% and 48% respectively, control = 0% for both, P < .001). Situs inversus, lobar collapse, or oxygen need for >2 days had 87% (95% confidence interval: 74-94) sensitivity and 96% (95% confidence interval: 85-99) specificity for PCD. CONCLUSIONS: When encountering term neonates with unexplained respiratory distress, clinicians should consider PCD in those with lobar collapse, situs inversus, and/or prolonged oxygen therapy (>2 days).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".