A Clinical Practice Guideline for the Management of Acute Spinal Cord Injury: Introduction, Rationale, and Scope
Bibliographic record
Abstract
Acute spinal cord injury (SCI) is a traumatic event that results in disturbances to normal sensory, motor, or autonomic function and ultimately affects a patient's physical, psychological, and social well-being. The management of patients with SCI has drastically evolved over the past century as a result of increasing knowledge on injury mechanisms, disease pathophysiology, and the role of surgery. There still, however, remain controversial areas surrounding available management strategies for the treatment of SCI, including the use of corticosteroids such as methylprednisolone sodium succinate, the optimal timing of surgical intervention, the type and timing of anticoagulation prophylaxis, the role of magnetic resonance imaging, and the type and timing of rehabilitation. This lack of consensus has prevented the standardization of care across treatment centers and among the various disciplines that encounter patients with SCI. The objective of this guideline is to form evidence-based recommendations for these areas of controversy and outline how to best manage patients with SCI. The ultimate goal of these guidelines is to improve outcomes and reduce morbidity in patients with SCI by promoting standardization of care and encouraging clinicians to make evidence-informed decisions.
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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 | 0.011 | 0.041 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.013 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 0.008 |
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".