Diagnosis and management of metastatic spine disease
Bibliographic record
Abstract
With continued growth of the elderly population and improvements in cancer therapies, the number of patients with symptomatic spinal metastases is likely to increase, and this is a condition that commonly leads to debilitating neurological dysfunction and pain. Advancements in surgical techniques of resection and spinal reconstruction, improvements in clinical outcomes following various treatment modalities, generally increased overall survival in patients with metastatic spine disease, and a recent randomized trial by Patchell and colleagues demonstrating the superiority of a combined surgical/radiotherapeutic approach over a radiotherapy-only strategy have led many to suggest increasingly aggressive interventions for patients with such lesions. Optimal management of spinal metastases encompasses numerous medical specialties, including neurosurgery, orthopedic surgery, medical and radiation oncology, radiology, and rehabilitation medicine. In this review, the clinical presentation, diagnosis, and management of spinal metastatic disease are discussed. Ultimately, the goal of treatment in patients with spinal metastases remains palliative, and clinical judgment is required to select the appropriate patients for surgical intervention.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".