ACR Appropriateness Criteria <sup>®</sup> Metastatic Epidural Spinal Cord Compression and Recurrent Spinal Metastasis
Bibliographic record
Abstract
Metastatic epidural spinal cord compression (MESCC) is an oncologic emergency and if left untreated, permanent paralysis will ensue. The treatment of MESCC is governed by disease, patient, and treatment factors. Patient's preferences and goals of care are to be weighed into the treatment plan. Ideally, a patient with MESCC is evaluated by an interdisciplinary team promptly to determine the urgency of the clinical scenario. Treatment recommendations must take into consideration the risk-benefit profiles of surgical intervention and radiotherapy for the particular individual's circumstance, including neurologic status, performance status, extent of epidural disease, stability of the spine, extra-spinal disease status, and life expectancy. In patients with high spinal instability neoplastic score (SINS) or retropulsion of bone fragments in the spinal canal, surgical intervention should be strongly considered. The rate of development of motor deficits from spinal cord compression may be a prognostic factor for ultimate functional outcome, and should be taken into account when a treatment recommendation is made. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed every three years by a multidisciplinary expert panel. The guideline development and review include an extensive analysis of current medical literature from peer-reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances where evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.
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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 | 0.007 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.013 |
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".