P.091 Anterior surgical fixation for cervical spine flexion-distraction injuries
Bibliographic record
Abstract
Background: Optimal surgical management for flexion--distraction cervical spine injuries remains controversial with anterior, posterior, and circumferential fixation being accepted. Here, we examined risk factors for clinical and radiographic failure in patients with one segment cervical flexion-distraction injuries having undergone anterior surgical fixation. Methods: A retrospective review of 57 consecutive patients undergoing anterior fixation for cervical flexion-distraction injuries between 2008-2012 was performed. The primary outcome was the number of patients requiring additional surgical stabilization and/or radiographic failure. Data collected inlcuded age, gender, mechanism and level of injury, facet pattern injury, and vertebral endplate fracture. Results: Six patients failed clinically and/or radiographically (11%). Four patients (7%) required additional posterior fixation. Two patients identified met radiographic failure criteria, however had fused radiographically, were stable clinically, and no further treatment was pursued. Progressive kyphosis and translation correlated with need for revision (p<0.05 and p=0.02, respectively). No differences were identified for all other clinical and radiological factors assessed. Conclusions: This study supports the growing body of evidence for anterior fixation alone for flexion-distraction injuries. Findings suggest that measurements including segmental translation and kyphosis may predict radiographic failure and need for further surgical stabilization in some patients. Assessment for independent risk factors for anterior approach failure with a validated predictive scoring model should be considered.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.009 | 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".