Comparison of Anterior and Posterior Surgical Approaches for Cervical Ossification of the Posterior Longitudinal Ligament Stratified by Spinal Levels: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVE: To compare the outcomes of anterior and posterior surgical approaches for treating cervical ossification of the posterior longitudinal ligament across multiple spinal levels, including 1-2 spinal levels, ≥ 3 levels, or studies that operated on both spinal levels, called mixed spinal levels. METHODS: A search strategy using pertinent keywords was employed in the MEDLINE, Embase, Scopus, and Web of Science databases. Data on Modified Japanese Orthopaedic Association (mJOA) scores, radiographic outcomes, and complications were extracted. A random-effects meta-analysis, subgroup meta-analysis, and sensitivity analysis were performed. RESULTS: Among 13 included studies, the anterior approach was statistically associated with improved C2-C7 Cobb angle, mJOA scores between 6 and 12 months, and mJOA recovery rates at more than 12 months (mean difference: 5.87°, 0.49°, and 18.81°, respectively). Conversely, the laminoplasty (LAMP) approach was more effective at maintaining the range of motion in patients with ≥ 3 spinal levels operated on (mean difference: -1.78°). The odds ratio (OR) of C5 palsy revealed lower odds in anterior approaches following surgery at ≥ 3 spinal levels (OR: 0.24, 95% confidence interval: 0.15 to 0.37). The odds of dysphagia following surgery at mixed spinal levels were higher in anterior approaches (OR: 3.68, 95% confidence interval: 1.24 to 10.94). CONCLUSIONS: LAMP significantly preserved cervical range of motion. LAMP and laminectomy with fusion reduced dysphagia but increased C5 palsy. The anterior approach improved alignment and function, but the mJOA score and recovery rate were not clinically meaningful. Patient-specific characteristics should be taken into account when selecting the surgical approach.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.036 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".