C.04 Dynamic MRI in the evaluation of the craniocervical junction of pediatric down syndrome patients
Bibliographic record
Abstract
Background: Down syndrome is the most common inherited disorder. Some patients develop craniocervical instability. Existing screening guidelines were developed prior to direct imaging of the neuraxis. We present parameters for potential instability using dynamic MRI of the craniocervical junction. Methods: A retrospective review from 2001 – 2015 was carried out. Patients were symptomatic if they had myelopathy or signal changes at the craniocervical junction. Radiographic measurements were taken. Data analysis was performed with SPSS. Results: 36 patients were included. Symptomatic patients had smaller CCD (9.4 mm vs 13.8 mm; p=0.003) and greater ADI (4.4mm vs 3.0 mm; p=0.01) on resting MRI . During dynamic imaging, symptomatic patients had greater changes in CCD (5.2 vs 2.7 mm; p <0.001) and ADI (2.8 vs 1.3 mm; p=0.04). These patients were also more likely to have a bony anomaly (0.5 vs 0.13; p=0.03). Conclusions: This study identifies parameters that can be used to distinguish unstable patients. A CCD of less than 5 mm or ADI greater than 4.4 mm on static MRI; change greater than 3 mm in ADI or 5mm on CCD during dynamic MRI; or any bony abnormality warrants further investigation. Asymptomatic patients should be followed although most do not progress.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".