Comparison of cervical disc arthroplasty and anterior cervical discectomy and fusion for the treatment of cervical disc degenerative diseases on the basis of more than 60 months of follow-up: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: This meta-analysis was designed to investigate the long-term efficacy and safety between cervical disc arthroplasty (CDA) and anterior cervical discectomy and fusion (ACDF) in treating cervical disc degenerative diseases (CDDDs). METHODS: Literature search was performed on Pubmed, Embase, Cochrane Library, and Web of Science before Jan 2019. Surgical details, clinical outcomes, range of motion (ROM), complications, and reoperation rates between CDA and ACDF groups were compared and analyzed. A fixed- or random-effects model was applied based on different heterogeneity. STATA (Version 11.0) software was used to perform data analysis. RESULTS: A total of 13 randomized controlled trial studies with more than 60 months of follow-up (mean 83.1 months) were enrolled in this meta-analysis. Pool results indicated that the CDA group exhibited significantly better outcomes in clinical scores (odds ratio [OR] = 1.54, 95% confidence interval [CI]: 1.15-2.08, p = 0.004) and preservation of ROM (mean difference = 1.77, 95% CI: 1.60-1.95, p < 0.001) than the ACDF group. Meanwhile, the incidence of adjacent segment disease (ASD) (OR = 0.51, 95% CI: 0.35-0.76, p = 0.001) and occurrence of reoperation (OR = 0.41, 95% CI: 0.25-0.69, p = 0.001) were lower in the CDA group than in the ACDF group. CONCLUSIONS: At long-term follow-up, CDA showed better efficacy in terms of clinical outcomes, ROM, ASD, and reoperation than ACDF for treating CDDDs. However, our results require further validation in large-sample and high-quality studies.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.055 |
| Bibliometrics | 0.006 | 0.005 |
| 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) | 0.002 | 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".