Surgical Treatment of Unstable Type II Odontoid Fractures in Skeletally Mature Individuals
Bibliographic record
Abstract
STUDY DESIGN: Systematic review of literature. OBJECTIVE: To determine the optimal indications and methods of surgical treatment for unstable type II odontoid fractures in skeletally mature individuals. SUMMARY OF BACKGROUND DATA: Odontoid fractures are a frequently encountered injury pattern in the cervical spine. The surgical treatment of type II odontoid fractures varies among spinal surgeons. The optimal surgical indications and treatment for type II odontoid fractures remains unclear. METHODS: Five primary research questions, based on safety and efficacy, were determined by consensus of a panel of spine trauma surgeons consisting of fellowship trained orthopedic and neurologic surgeons. A comprehensive review of the literature was performed using MeSH search terms in MEDLINE, PubMed, EMBASE, CINAHL, and the Cochrane Database of Systematic reviews. The quality of literature was rated as high, moderate, low, or very low. Using the GRADE evidence-based review system, the primary questions were answered using the literature review and expert opinion. These treatment recommendations were then rated as either strong or weak based on the quality of evidence and clinical expertise. RESULTS: The initial search resulted in over 1300 results. After initial application of all inclusion and exclusion criteria, 458 abstracts were reviewed from which 22 manuscripts were found to meet all criteria. These were obtained, reviewed, and used to create an evidentiary table. All articles were of either low or very low quality. CONCLUSION: There is no moderate or high quality literature on the surgical management of acute type II odontoid fractures. Optimal indications for either anterior or posterior treatment of fractures are described but with no comparative data. A single anterior odontoid screw is the recommended technique for anterior treatment. Posterior internal fixation (C1-C2 transarticular screw, C1-C2 segmental fixation) is the recommended technique for posterior treatment. In equivocally indicated instances, anterior or posterior treatment can be safely used with good outcome. In this scenario, surgical management decision should be influenced by surgeon and patient preference as well as cost considerations.
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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 | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".