Methylprednisolone for Acute Spinal Cord Injury: 5-Year Practice Reversal
Bibliographic record
Abstract
OBJECTIVE: To re-evaluate practice patterns for methylprednisolone (MP) administration in patients with acute spinal cord injury (SCI) within the spinal surgery community across Canada five years after the publication of practice recommendations. METHODS: Canadian orthopedic and neurological spine surgeons were surveyed at their respective annual meetings about their practice of steroid administration for acute SCI by means of a questionnaire comprised of the same seven questions posed five years ago plus an additional question related to change of view. RESULTS: Forty-two surgeons and twenty-one residents directly involved in the acute management of SCI completed the questionnaire. Seventy-six percent of spinal surgeons do not prescribe MP for SCI in sharp contrast to 76% who prescribed it five years ago. Of the 24% who use steroids, the NASCIS II dosing regimen is most commonly followed. One third of physicians continue to administer MP because of fear of litigation. CONCLUSIONS: Over a five year period there has been a complete reversal in practice patterns of MP administration for SCI, along with an increased familiarity of the published literature. Attendance at meetings, participation in local group discussions, and peer-reviewed publications appear effective in altering practice preferences arising from peer pressure and even fear of litigation.
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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".