CERVICAL SPONDYLOTIC MYELOPATHY TREATED BY OBLIQUE CORPECTOMY
Bibliographic record
Abstract
OBJECTIVE: Anterolateral partial oblique corpectomy (OC) aims to decompress the cervical spinal cord without subsequent fusion and saves the patient from graft-, instrument-, and fusion-related complications. Although it is a promising technique, there are few studies dealing with its efficacy and safety. METHODS: In this prospective study, 40 consecutive patients underwent an OC (one to four levels from C3 to C7) for cervical spondylotic myelopathy; they ranged in age from 43 to 78 years (mean, 55 yr). The average follow-up period was 59 months (range, 24-98 mo). Clinical and radiological data were analyzed to assess the results and find possible factors related to outcomes. RESULTS: Thirty-seven (92.5%) of the 40 patients improved by the 6-month follow-up examination according to the Japanese Orthopedic Association score. The improvement was the most prominent in lower extremity dysfunction. Recovery was positively correlated with the preoperative Japanese Orthopedic Association score (r = 0.37, P = 0.018). Permanent Horner's syndrome developed in four patients (10%). During the long-term follow-up period, neurological improvement was maintained and there were no signs of postoperative instability, posture change, or axial pain. CONCLUSION: OC for treating multilevel cervical spondylotic myelopathy achieved good results with a low morbidity rate. The results of the current study suggest that OC is a good alternative to conventional median corpectomy and fusion techniques in selected cases.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".