Efficacy and Safety of Surgical Interventions for Treating Multilevel Cervical Spondylotic Myelopathy via Anterior Approach: A Network Meta-Analysis.
Bibliographic record
Abstract
BACKGROUND: Anterior cervical discectomy, with or without interbody fusion, is a common technique to treat cervical spondylotic myelopathy (CSM). To date, controversy still exists among spine surgeons regarding the anterior surgical approach to be used for the treatment of multilevel CSM. OBJECTIVES: To evaluate the effectiveness and safety of anterior cervical discectomy and fusion (ACDF), anterior cervical corpectomy and fusion (ACCF), cervical total disc replacement (CTDR), and hybrid surgery (HS) in the treatment of multilevel CSM. STUDY DESIGN: Network meta-analysis (NMA) of randomized or nonrandomized controlled studies for the treatment of multilevel CSM. METHODS: The databases such as PubMed, CENTRAL, and EMBASE were used to search and identify the clinical trials involving the evaluations for the treatment of multilevel CSM. The Newcastle-Ottawa Scale was used for the assessment of methodological qualities, whereas the Cochrane Collaboration tool was used for assessing the risk of bias. Outcome assessments included duration of surgery, Neck Disability Index (NDI) scores, and complications. Odds ratio was used to express dichotomous outcomes, whereas mean difference with a 95% confidence interval was used to express continuous outcomes. RESULTS: Sixteen relevant studies were identified, and 1,639 patients were included in this analysis. CTDR demonstrated a prominently decreased NDI score and total incidence of complications compared with ACDF, ACCF, and HS. In addition, ACDF resulted in shorter operation times compared with ACCF, CTDR, and HS. The ranked order of NDI score improvement in decreasing order was: CTDR, HS, ACDF, followed by ACCF. The rank order for reduction in operation time increased progressively from ACDF, HS, ACCF to CTDR. The total incidence of complications also showed a decreasing trend in the decreasing order-CTDR, ACDF, HS, ACCF, and finally CTDR with the lowest complication rate. LIMITATIONS: The limitations of this NMA include inconformity of the follow-up times and surgical skill, and implants of different treatment centers vary. CONCLUSIONS: The analysis of this study has shown that the best method for improvement of functional outcome and reduction in total incidence of complications for multilevel CSM is CTDR. KEY WORDS: Multilevel cervical spondylotic myelopathy, anterior cervical discectomy and fusion, anterior cervical corpectomy and fusion, cervical total disc replacement, hybrid surgery, effectiveness, safety, network meta-analysis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| 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".