Laterality Defects in Primary Ciliary Dyskinesia: Relationship to Ultrastructural Defect or Genotype
Bibliographic record
Abstract
Abstract Rationale The association between organ laterality abnormalities and ciliary ultrastructural defect or genotype in primary ciliary dyskinesia is poorly understood. Objectives To determine if there is an association between presence and/or type of laterality abnormality and ciliary ultrastructural defect or genotype. Methods Participants with primary ciliary dyskinesia in a multicenter, prospective study were grouped based on ciliary ultrastructural defect or genotype. In a retrospective analysis of these data, the association of ciliary ultrastructural defect or genotype and likelihood of a laterality abnormality was evaluated by logistic regression adjusted for presence of two loss-of-function versus one or more not–loss-of-function variants. Results Of 559 participants, 286 (51.2%), 215 (38.5%), and 58 (10.4%) were identified as having situs solitus, situs inversustotalis, and situs ambiguus, respectively; heterotaxy, defined as situs ambiguus with complex cardiovascular defects, was present in 14 (2.5%). Compared with the group with inner dynein arm defects with microtubular disorganization, laterality defects were more likely in the outer dynein arm defects group (odds ratio [OR], 2.07; 95% confidence interval [CI], 1.21–3.54; P < 0.01) and less likely in the normal/near normal ultrastructure group (OR, 0.04; 95% CI, 0.013–0.151; P < 0.01). Heterotaxy was present in 11 of 242 (4.5%) in the outer dynein arm defects group but 0 of 96 in the inner dynein arm defects with microtubular disorganization group (P = 0.038). Conclusions In primary ciliary dyskinesia, risk of a laterality abnormality differs by ciliary ultrastructural defect. Pathophysiologic mechanisms underlying these differences require further exploration.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".