Is anterior cervical plating necessary for cage constructs in anterior cervical discectomy and fusion surgery for cervical degenerative disorders? Evidence-based on the systematic overview of meta-analyses
Bibliographic record
Abstract
Systematic review of meta-analyses. To perform a systematic review of meta-analyses to compare the clinical and radiological outcomes following anterior cervical discectomy and fusion with stand-alone cage (SAC) and anterior cervical cage-plate constructs (ACCPC). The systematic overview was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and reported as per Cochrane Handbook for Systematic Reviews of Interventions following the methodology described in reporting Overview of reviews. Based on the available level-1 evidence, SAC offers significantly better benefits over ACCPC, in terms of shorter operative time (p < 0.00001; I2 = 0%), lower blood loss (p = 0.01; I2 = 0%), lesser rates of post-operative dysphagia (p = 0.02; I2 = 0%), reduced overall expenditure (p = 0.001) and long-term adjacent segment degeneration (ASD)/anterior longitudinal ligament ossification (ALO; p = 0.0003; I2 = 0%). There is no significant difference between the two constructs with regard to fusion rates, functional outcome scores, follow-up radiological sagittal alignment parameters or cage subsidence. Based on the available evidence, SAC constructs in ACDF reduce blood loss, decreases operative time, mitigates post-operative dysphagia, lessens hospital-related expenditure and minimises long-term ASD rates.
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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 | 0.027 | 0.069 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.048 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".