Comparison of complication rates between anterior versus posterior approaches for treating unstable Hangman's fracture. A systematic review and meta-analysis
Bibliographic record
Abstract
Study design: Systematic Review and Meta-analysis. Objective: To compare the complication rates associated with anterior and posterior approaches for the surgical treatment of unstable hangman's fractures. Methods: A systematic review and meta-analysis were performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines in PubMed, Web of Science, and Scopus databases to identify comparative studies reporting complications of anterior versus posterior approaches for the treatment of unstable hangman's fractures. Results: The search yielded 1163 papers from which 5 studies were fully included. One hundred fifteen (115) patients were operated on using an anterior approach versus 65 through a posterior approach. The average complication rates for the anterior and posterior approaches were 26.1 % and 13.8 %, respectively. No complications following the anterior approach required pharmacological or surgical intervention (Clavien-Dindo, Grade 1), while 88.9 % of complications following the posterior approach did (Clavien-Dindo, Grade 2). Conclusion: No significant differences in the complication rates were found when comparing anterior versus posterior surgery for treating a C2 traumatic spondylolisthesis. However, most of the complications presented in the posterior surgery group were more severe.
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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 | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.009 | 0.008 |
| 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) | 0.002 | 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".