Clinical Predictors of Recovery after Blunt Spinal Cord Trauma: Systematic Review
Bibliographic record
Abstract
Several clinical, imaging, and therapeutic factors affecting recovery following spinal cord injury (SCI) have been described. A systematic review of the topic is still lacking. Our primary aim was to systematically review clinical factors that may predict neurological and functional recovery following blunt traumatic SCI in adults. Such work would help guide clinical care and direct future research. Both Medline and Embase (to April 2008) were searched using index terms for various forms of SCI, paraplegia, or quadri/tetraplegia, and functional and neurological recovery. The search was limited to published articles that were in English and included human subjects. Article selection included class I and II evidence, blunt traumatic SCI, injury level above L1-2, baseline assessment within 72 h of injury, use of American Spinal Injury Association (ASIA) scoring system for clinical assessment, and functional and neurological outcome. A total of 1526 and 1912 citations were located from Medline and Embase, respectively. Two surgeons reviewed the titles, abstracts, and full text articles for each database. Ten articles were identified, only one of which was level 1 evidence. Age and gender were identified as two patient-related predictors. While motor and functional recovery decreased with advancing age for complete SCI, there was no correlation considering incomplete ones. Therefore, treatment should not be restructured based on age in incomplete SCI. Among injury-related predictors, severity of SCI was the most significant. Complete injuries correlated with increased mortality and worse neurological and functional outcomes. Other predictors included SCI level, energy transmitted by the injury, and baseline electrophysiological testing.
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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 | 0.004 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.009 | 0.016 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".