SEVERE CERVICAL MYELOPATHY: APPROACHES AND POSTOPERATIVE EVALUATION
Bibliographic record
Abstract
ABSTRACT Objectives: To evaluate and compare the clinical evolution of surgical approaches used in patients with severe cervical myelopathy. Methods: Retrospective observational study in which 19 patients with myelopathy who underwent surgery were evaluated. Neurological assessments using the Frankel scale were conducted both preoperatively and one year following surgery, and the modified Japanese Orthopedic Association (JOA), Nurick, and Visual Analog Scale for pain (VAS) questionnaires were applied 1 year after the surgical procedure. Results: 89% of the participants were male and the average age was 63.9 years. No patient had postoperative neurological worsening, 12 patients (63.16%) had mild pain, and seven (36.84%) had moderate pain. The group with degenerative disease showed neurological improvement after surgery and the exclusively anterior approach was used in 84% of the cases, the exclusively posterior approach in 10% of the cases, and the dual approach in 6% of the cases. Conclusion: Surgical treatment has good results for inhibiting the unfavorable natural evolution of myelopathy within 1 year following surgery and promotes neurological improvement in degenerative cases, making it possible to use the anterior access route in most cases. Level of evidence III; Retrospective Study.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".