A Series of Systematic Reviews on the Treatment of Acute Spinal Cord Injury: A Foundation for Best Medical Practice
Bibliographic record
Abstract
The treatment of acute spinal cord injury (SCI) is a multidisciplinary effort that spans from the time of injury through to an acute care center, and in some cases the remainder of the individual's life. Recovery from SCI depends on the care received at each point along this spectrum in time. In order to facilitate the practice of evidence-based medicine and best clinical practices, a multidisciplinary team of clinicians and researchers systematically reviewed the literature on SCI and set out to answer pertinent clinical questions and establish evidence-based recommendations. This article introduces the series of systematic reviews, summarizes the most notable findings, and gives an overview of the questions asked in each review and the evidence-based recommendations for care. Some of the most important recommendations are as follows: (1) Patients should be immobilized before transport to a hospital using a cervical collar, head immobilization, and a spinal board; (2) MRI is strongly recommended for the prognostication of acute SCI; (3) early surgical intervention (from 8-24 h) should be considered following acute traumatic SCI; (4) SCI patients are at significant risk of cardiovascular and respiratory problems and management should proactively anticipate these potential complications; and (5) outcomes can be improved by management in specialized centers with access to intensive care.
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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 | 0.037 | 0.217 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.019 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| 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".