Evaluation of Adverse Events in Total Disc Replacement: A Meta-Analysis of FDA Summary of Safety and Effectiveness Data
Bibliographic record
Abstract
STUDY DESIGN: Systematic review and meta-analysis. OBJECTIVES: The safety of new technology such as cervical total disc replacement (TDR) is of paramount importance and is best evaluated in randomized clinical trials (RCT). We compared complication risks of TDR to fusion using data from Investigational Device Exemptions. METHODS: A systematic review of FDA Summary of Safety and Effectiveness reports of the 8 approved cervical TDRs was performed. These were all randomized controlled trials comparing anterior cervical discectomy and fusion (ACDF) to TDR. Important outcome variables were dysphagia, wound infection, neurologic injuries, heterotopic ossification, death, and secondary surgeries. A random effects model was selected a priori. Data on adverse events was abstracted and analyzed by calculating relative risk of ACDF to TDR by meta-analysis techniques. RESULTS: The study included 3027 patients with 1377 randomized to ACDF and 1652 to TDR. No statistical differences were present between the 2 groups in dysphagia/dysphonia, hardware related, heterotopic ossification, death, and overall neurologic adverse events and incidence of neurologic deterioration. The relative risk of wound-related problems ACDF to TDR was 0.76 (95% confidence interval [CI] = 0.59, 0.98) favoring ACDF, which was statistically significant, but these were minor and never required a second surgical procedure for deep wound infection. The relative risk of ACDF to TDR in surgical-related neurologic events and secondary surgeries was 1.62 (95% CI = 1.04, 2.53) and 1.79 (95% CI = 1.17, 2.74), both favoring TDR. CONCLUSIONS: Cervical TDR appears to be as safe as or safer than ACDF at 2-year follow-up.
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How this classification was reachedexpand
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".