Assessment and management of acute spinal cord injury: From point of injury to rehabilitation
Bibliographic record
Abstract
CONTEXT: Spinal cord injury (SCI) is a devastating condition that can lead to significant neurological impairment and reduced quality of life. Despite advancements in our understanding of the pathophysiology and secondary injury mechanisms involved in SCI, there are currently very few effective treatments for this condition. The field, however, is rapidly changing as new treatments are developed and key discoveries are made. METHODS: In this review, we outline the pathophysiology, management, and long-term rehabilitation of individuals with traumatic SCI. We also provide an in-depth overview of emerging therapies along the spectrum of the translational pipeline. EVIDENCE SYNTHESIS: The concept of "time is spine" refers to the concept which emphasizes the importance of early transfer to specialized centers, early decompressive surgery, and early delivery of other treatments (e.g. blood pressure augmentation, methylprednisolone) to affect long-term outcomes. Another important evolution in management has been the recognition and prevention of the chronic complications of SCI including respiratory compromise, bladder dysfunction, Charcot joints, and pressure sores through directed interventions along with early integration of physical rehabilitation and mobilization. There have also been significant advances in neuroprotective and neuroregenerative strategies for SCI, many of which are actively in clinical trial including riluzole, Cethrin, stem cell transplantation, and the use of functional electrical stimulation. CONCLUSION: Pharmacologic treatments, cell-based therapies, and other technology-driven interventions will likely play a combinatorial role in the evolving management of SCI as the field continues to evolve.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".