Craniocervical Dissociation in Pediatric Patients
Bibliographic record
Abstract
AIMS: The aims of this study were to document the injury pattern in pediatric traumatic craniocervical dissociation (CCD) and identify features of survivors. METHODS: Pediatric traumatic CCDs, diagnosed between January 2004 and July 2016, were reviewed. Survivors and nonsurvivors were compared. Categorical and continuous variables were analyzed with Fisher exact and t tests, respectively. RESULTS: Twenty-seven children were identified; 10 died (37%). The median age was 60 months (ranges, 6-109 months [survivors], 2-98 months [nonsurvivors]). For survivors, the median follow-up was 13.4 months (range, 1-109 months). The median time to mortality was 1.5 days (range, 1-7 days). The injury modality was motor vehicle collision in 18 (67%), pedestrian struck in 8 (30%), and 1 shaken infant (3%). For nonsurvivors, CCD was equally diagnosed by plain radiograph and head/cervical spine computed tomography scan. For survivors, CCD was diagnosed by computed tomography in 7 (41%), magnetic resonance imaging in 10 (59%), and none by radiograph. Seven diagnosed by magnetic resonance imaging (41%) had nondiagnostic initial imaging but persistent neck pain. Magnetic resonance imaging was obtained and was diagnostic of CCD in all 7 (P < 0.01). Survivors required significantly less cardiopulmonary resuscitation (P < 0.01), had lower Injury Severity Scores (P < 0.01), higher Glasgow Coma Scale scores (P < 0.01), and shorter transport times (P < 0.01). Significantly more involved in motor vehicle collisions survived (P = 0.04). Nine (53%) had no disability at follow-up evaluation. CONCLUSIONS: In pediatric CCD, high-velocity mechanism, cardiac arrest, high Injury Severity Score, and low Glasgow Coma Scale score are associated with mortality. If CCD is correctly managed in the absence of cardiac arrest or traumatic brain or spinal cord injury, children may survive intact.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".