Transarticular Screws in the Management of C1−C2 Instability in Children
Bibliographic record
Abstract
C1-C2 instability is a challenging problem in the pediatric population. Small patient size and poor healing potential in the at-risk groups, such as patients with Down syndrome and os odontoideum, make fixation difficult. Instability in patients with Down syndrome is a common problem, and traditional methods of fixation have a high complication rate and are a challenge given the frequent anatomic abnormalities such as an incomplete or hypoplastic arch, os odontoideum, and incomplete passive reduction. The purpose of this study was to review our experience of transarticular screw use in pediatric patients and to define the potential applications of this technique in pediatric C1-C2 instability. Twelve patients, with C1-C2 instability managed with transarticular screws at the authors' institution, were reviewed. The youngest patient treated was 5 years old with a mean age for the group of 11.5 years. The group consisted of 3 patients with Down syndrome and 9 patients with os odontoideum. Three of the patients with os odontoideum failed previous posterior wiring. Two patients presented with an acute spinal cord injury in the setting of chronic instability. Preoperative computed tomography or magnetic resonance imaging was used in all patients to define the vascular and bony anatomy. No further surgery has been required at a mean follow-up of 5.1 years in all patients. Although vertebral size and congenital anomalies may make screw positioning challenging, the technique allows fixation in the absence of a complete posterior arch of C1 and eliminates the need for instrumentation in the canal. This technique also provides a high fusion rate in a complicated patient population.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".