Bibliographic record
Abstract
STUDY DESIGN: Literature review. OBJECTIVES: The purpose of this article is to review the available literature and formulate evidence-based recommendations for the use of methylprednisone in the setting of acute spinal cord injury (SCI). SUMMARY OF BACKGROUND DATA: Since the early 1990s, methylprednisolone has become widely prescribed for the treatment of acute SCI. Arguably, it has become a standard of care. METHODS: Through an electronic database search strategy and by cross-reference with published literature, appropriate clinical studies were identified. They were reviewed in chronologic order with respect to study design, outcome measures, results, and conclusions. RESULTS: Nine studies were identified that attempted to evaluate the role of steroids in nonpenetrating (blunt) spinal cord injury. Five of these were Class I clinical trials, and four were Class II studies. All of the studies failed to demonstrate improvement because of steroid administration in any of the a priori hypotheses testing. Although post hoc analyses were interesting, they failed to demonstrate consistent significant treatment effects. CONCLUSIONS: From an evidence-based approach, methylprednisolone cannot be recommended for routine use in acute nonpenetrating SCI. Prolonged administration of high-dose steroids (48 hours) may be harmful to the patient. Until more evidence is forthcoming, methylprednisolone should be considered to have investigational (unproven) status only.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".