Anterior Instrumentation for Traumatic C1–C2 Instability
Bibliographic record
Abstract
STUDY DESIGN: Technical note, case report. and review of literature. OBJECTIVE: Description of anterior transarticular internal fixation for traumatic C1-C2 instability. SUMMARY OF BACKGROUND DATA: The currently effective posterior approaches for instrumentation of the C1-C2 junction require considerable soft tissue dissection and prone patient positioning. Some medical and anatomic conditions restrict the posterior approach. MATERIALS AND METHODS: An odontoid screw and anterior transarticular C1-C2 screws were used to instrument an unstable injury at this junction. The lesion consisted of a type II dens fracture and C1 ring disruption. Two high-quality fluoroscopy machines, a radiolucent OSI fracture table, and the Synframe (Synthes, Paoli, PA) retraction system are used for this procedure. The implant of choice is the 4.0-mm cannulated titanium screw. RESULTS: At 4-month follow-up, successful stabilization without failure of hardware is documented. The patient's neurologic status is stable, with a minor residual left upper extremity motor deficit. The patient has restricted C-spine rotation but no neck pain with movement. CONCLUSION: Anterior stabilization through a standard Smith-Robinson approach of the C1-C2 junction with screws into the odontoid and the lateral masses of C1 is effective. Supine positioning and minimal soft tissue dissection are advantages of this method over standard posterior transarticular instrumentation. Knowledge of the local anatomy, strict adherence to the operative protocol, and high-quality fluoroscopy avoid potential surgical complications.
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 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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".