The Role of Anterior Cervical Discectomy and Fusion on Relieving Axial Neck Pain in Patients With Single-Level Disease: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Study Design: Systematic review and meta-analysis. Objectives: This study aims to evaluate the effects of anterior cervical decompression and fusion (ACDF) on axial neck pain in adult patients receiving surgery for myelopathy, radiculopathy, or a combination of both. Methods: Two independent reviewers completed a librarian-assisted search of 4 databases. Visual Analogue Scale (VAS) and Neck Disability Index (NDI) scores were extracted preoperatively and at 3, 6, 12, 24, 36, 48, and 48+ months postoperatively for ACDF groups and pooled using a random-effects model. Results: Of 17 850 eligible studies, 37 were included for analysis, totaling 2138 patients analyzed with VAS and 2477 with NDI score. Individual VAS mean differences were reduced at 6 weeks (−2.5 [95% confidence interval (CI): −3.5 to −1.6]), 3 months (−2.9 [−3.7 to −2.2]), 6 months (−3.2 [−3.9 to −2.6]), 12 months (−3.7 [−4.3 to −3.1]), 24 months (−4.0 [−4.4 to −3.5]), 48 months (−4.6 [−5.5 to −3.8]), and >48 months (−4.7 [−5.8 to −3.6]) follow-up ( P < .0001 for all endpoints). Individual NDI mean differences were reduced at 6 weeks (−26.7 [−30.9 to −22.6]), 3 months (−29.8 [−32.7 to −26.8]), 6 months (−31.2 [−35.5 to −26.8)], 12 months (−29.3 [−33.2 to −25.4]), 24 months (−28.9 [−32.6 to −25.2]), 48 months (−33.1 [−37.4 to −28.7]), and >48 months (−37.6 [−45.9 to −29.3]) follow-up ( P < .0001 for all endpoints). Conclusions: ACDF is associated with a significant reduction in axial neck pain compared with preoperative values in patients being treated specifically for myelopathy or radiculopathy. This influences the preoperative discussions surgeons may have with patients regarding their expectations for surgery. The effects seen are stable over time and represent a clinically significant reduction in axial neck pain.
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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 | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.038 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".