Acute Spinal Cord Injury, Part II: Contemporary Pharmacotherapy
Bibliographic record
Abstract
Spinal cord injury (SCI) remains a common and devastating problem of modern society. Through an understanding of underlying pathophysiologic mechanisms involved in the evolution of SCI, treatments aimed at ameliorating neural damage may be developed. The possible pharmacologic treatments for acute spinal cord injury are herein reviewed. Myriad treatment modalities, including corticosteroids, 21-aminosteroids, opioid receptor antagonists, gangliosides, thyrotropin-releasing hormone (TRH) and TRH analogs, antioxidants and free radical scavengers, calcium channel blockers, magnesium replacement therapy, sodium channel blockers, N -methyl-D-aspartate receptor antagonists, alpha-amino-3-hydroxy-5-methylisoxazole-4-propionic acid-kainate receptor antagonists, modulators of arachadonic acid metabolism, neurotrophic growth factors, serotonin antagonists, antibodies against inhibitors of axonal regeneration, potassium channel blockers (4-aminopyridine), paclitaxel, clenbuterol, progesterone, gabexate mesylate, activated protein C, caspase inhibitors, tacrolimus, antibodies against adhesion molecules, and other immunomodulatory therapy have been studied to date. Although most of these agents have shown promise, only one agent, methylprednisolone, has been shown to provide benefit in large clinical trials. Given these data, many individuals consider methylprednisolone to be the standard of care for the treatment of acute SCI. However, this has not been established definitively, and questions pertaining to methodology have emerged regarding the National Acute Spinal Cord Injury Study trials that provided these conclusions. Additionally, the clinical significance (in contrast to statistical significance) of recovery after methylprednisolone treatment is unclear and must be considered in light of the potential adverse effects of such treatment. This first decade of the new millennium, now touted as the Decade of the Spine, will hopefully witness the emergence of universal and efficacious pharmacologic therapy and ultimately a cure for SCI.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".