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Record W4206612282 · doi:10.5327/1516-3180.057

Use of glucocorticoids in acute spinal cord injuries: a last decade analysis

2021· article· en· W4206612282 on OpenAlexaboutno aff
Guilherme Dantas Campos Pinto, Gabriela Arcoverde Wanderley, Gustavo Sales Santa Cruz, Luís Eduardo Nobrega Nogueira Alves, Wagner Gonçalves Horta

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisMedicineRandomized controlled trialMethylprednisoloneDrug trialSpinal cord injurySpinal cordClinical trialPhysical therapySurgeryInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Introduction: The early use of methylprednisolone (MP) pulse represents the only treatment suggested to stop neurological outcomes in non-operable acute spinal cord injuries (ASCI). The protocol of the drug use dates from the 1990s and results of the NASCIS 2 randomized clinical trial. However, such conduct is still an issue for discussion, due to limited evidence. Objective: To compare the results of the main studies about the use of MP in the ASCI published in the last decade. Methods: This is a narrative review of the use of MP in the ASCI. A search was carried out using the keywords “acute spinal cord injury” and “methylprednisolone” on PubMed and Cochrane, in April 2021. Indexed meta- analysis from 2011 to 2020 were used as filters. All studies (3) were selected for analysis and comparison of their results. Results: Cochrane meta-analysis, in 2012 concluded that MP administration results in an improvement of the neurological outcome and presents good safety margin. Although it agrees with the drug harmless, a Canadian study in 2017 pointed out the MP offers a poor motor function benefit in the long term. Recently, in 2019, a meta-analysis from the American Academy of Neurology, did not recommend the use of MP in the ASCI, because of the lack of benefit in neurological function and increased occurrence of complications after the adoption of the therapy. Conclusion: Data from the last ten years of analysis demonstrates a progressive decrease in the evidence in favor of the use of MP in the ASCI.

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 imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.024
Bibliometrics0.0070.012
Science and technology studies0.0000.000
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.420
Teacher spread0.343 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreReview

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

Citations0
Published2021
Admission routes1
Has abstractyes

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