Predicting Neurologic Recovery after Surgery in Patients with Deficits Secondary to MESCC
Bibliographic record
Abstract
STUDY DESIGN: Systematic literature review and expert survey OBJECTIVE.: The aim of this study was to determine factors associated with neurologic improvement in patients with neurologic deficits secondary to metastatic epidural spinal cord compression (MESCC). Clear understanding of these factors will guide surgical decision-making by helping to elucidate which patients are more likely to benefit from surgery and how surgeons can increase the probability of neurologic and functional restoration. SUMMARY OF BACKGROUND DATA: Surgical spinal cord decompression has been shown to improve neurologic function in patients with symptomatic MESCC. However, prognostication of neurologic improvement after surgery remains challenging, owing to sparse data and complexity of these patients. METHODS: PubMed and Embase databases were searched for relevant publications. PRISMA Statement guided publication selection and data reporting. GRADE guidelines were used for evidence quality evaluation and recommendation formulation. RESULTS: Low-quality evidence supports the use of the duration and severity of neurologic deficit as predictors of neurological recovery in patients with MESCC. Low-quality evidence supports the use of thoracic level of compression and previous irradiation as adverse predictors of neurological recovery. Nearly all of the AOSpine Knowledge Forum Tumor members who responded to the survey agreed that ambulation with assistance represented a successful surgical result and that duration of ambulation loss and the severity of weakness should be considered when trying to predict whether surgery would result in restoration of ambulation. CONCLUSIONS: Review of literature and expert opinion support the importance of duration of ambulation loss and the severity of neurologic deficit (muscle strength, bladder function) in prediction of neurologic recovery among patients with symptomatic MESCC. Efforts to reduce the duration of ambulation loss and to prevent progression of neurologic deficits should be made to improve the probability of neurologic recovery. LEVEL OF EVIDENCE: 2.
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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 | 0.018 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.015 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".