Cervical kyphosis after posterior cervical laminectomy with and without fusion
Bibliographic record
Abstract
BACKGROUND: Cervical posterior instrumentation and fusion is often performed to avoid post-laminectomy kyphosis. However, larger comparative analyses of cervical laminectomy with or without fusion are sparse. METHODS: A retrospective, two-center, comparative cohort study included patients after stand-alone dorsal laminectomy with (n = 91) or without (n = 46) additional fusion for degenerative cervical myelopathy with a median follow-up of 59 (interquartile range (IQR) 52) months. The primary outcome was the C2-7 Cobb angle and secondary outcomes were Neck Disability Index (NDI), modified Japanese Orthopaedic Association (mJOA) scale, revision rates, T1 slope and C2-7 sagittal vertical axis (C2-7 SVA) at final follow-up. Logistic regression analysis adjusted for potential confounders (i.e. age, operated levels, and follow-up). RESULTS: Preoperative C2-7 Cobb angle and T1 slope were higher in the laminectomy group, while the C2-7 SVA was similar. The decrease in C2-7 Cobb angle from pre- to postoperatively was more pronounced in the laminectomy group (- 6° (IQR 20) versus -1° (IQR 7), p = 0.002). When adjusting for confounders, the decrease in C2-7 Cobb angle remained higher in the laminectomy group (coefficient - 12 (95% confidence interval (CI) -18 to -5), p = 0.001). However, there were no adjusted differences for postoperative NDI (- 11 (- 23 to 2), p = 0.10), mJOA, revision rates, T1 slope and C2-7 SVA. CONCLUSION: Posterior cervical laminectomy without fusion is associated with mild loss of cervical lordosis of around 6° in the mid-term after approximately five years, however without any clinical relevance regarding NDI or mJOA in well-selected patients (particularly in shorter segment laminectomies of < 3 levels).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".