Multilevel Oblique Corpectomy Without Fusion
Bibliographic record
Abstract
STUDY DESIGN: The authors provide their results in performing multilevel oblique corpectomy for degenerative spondylotic myelopathy in 48 patients. OBJECTIVE: To demonstrate the efficacy and safety of the multilevel oblique corpectomy when applied in selected cases. SUMMARY OF BACKGROUND DATA: The technique of multilevel oblique corporectomies for treatment of cervical spondylogenetic myeloradiculopathies allows anterolateral access to the cervical spine so that the spinal canal and conjugate foramen can be widened at more than one level, without the need for vertebral stabilization. METHODS: During a 7-year period, multilevel oblique corpectomy was performed in 48 consecutive patients for degenerative spondylotic myelopathy. The outcomes were analyzed according to the Japanese Orthopaedic Association classification modified to Western customs, and according to Nurick's scale 1 month, 1 year, and 2 years after surgery. Spinal stability was evaluated in all patients by plain radiograph films of the cervical spine, lateral views in flexion and extension, on discharge, 1 month and 1 year after operation. RESULTS: Significant clinical improvement occurred in 29 patients with a complete functional recovery in 22; moderate improvement was achieved in 12 patients; neurological status remained stable in 5, and it worsened in 2. All patients showed spinal stability. CONCLUSIONS: Multilevel oblique corpectomy was found to be a safe technique that guarantees good results in terms of both regression of clinical symptoms and long-term spinal stability.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.006 | 0.001 |
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".