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
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it