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Record W2072963919 · doi:10.1017/s0317167100002006

Why Do You Prescribe Methylprednisolone for Acute Spinal Cord Injury? A Canadian Perspective and a Position Statement

2002· article· en· W2072963919 on OpenAlexaffvenueabout
R. John Hurlbert, Richard J. Moulton

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2002
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversity of CalgarySt. Michael's HospitalFoothills Medical Centre
Fundersnot available
KeywordsMethylprednisoloneMedicineGuidelinePosition statementOrthopedic surgerySpinal cord injuryRegimenPhysical therapySpinal cordSurgeryFamily medicinePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the practice patterns for methylprednisolone administration for patients with acute spinal cord injury (SCI) within the spinal surgery community across Canada, and the reasons behind these patterns. METHODS: Canadian neurological and orthopedic spine surgeons were surveyed at their respective annual meetings with a questionnaire asking seven questions with respect to their practice standards. RESULTS: Sixty surgeons completed the survey representing approximately two-thirds of surgeons treating acute SCI within Canada. The NASCIS III dosing regimen is the most commonly prescribed steroid protocol. However, one-quarter of surgeons do not administer steroids at all. Of those who administer methylprednisolone, most do so because of peer pressure or out of fear of litigation. CONCLUSIONS: The vast majority of spine surgeons in Canada either do not prescribe methylprednisolone for acute SCI, or do so for what might be considered the wrong reasons. These results demonstrate the need for an evidence-based practice guideline. The Canadian Spine Society and the Canadian Neurosurgical Society fully endorse the recommendations of the steroid task force (see preceding paper).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.811
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0030.005
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.077
GPT teacher head0.381
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations82
Published2002
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicSpinal Cord Injury ResearchFrench-language works237,207