Early Surgery for Traumatic Spinal Cord Injury: Where Are We Now?
Bibliographic record
Abstract
STUDY DESIGN: Narrative review. OBJECTIVE: There is a strong biological rationale to perform early decompression after traumatic spinal cord injury (SCI). With an enlarging clinical evidence base, most spine surgeons internationally now favor early decompression for the majority of SCI patients; however, a number of pertinent questions remain surrounding this therapy. METHODS: A narrative review evaluating the status of early surgery for SCI. In particular, we addressed the following questions: (1) Which patients stand to benefit most from early surgery? 2) What is the most appropriate time threshold defining early surgery? RESULTS: Although heterogeneity exists, the evidence generally seems to support early surgery. While the best evidence exists for cervical SCI, there is insufficient data to support a differential effect for early surgery depending on neurological level or injury severity. When comparing thresholds to define early versus late surgery-including a later threshold (48-72 hours), an earlier threshold (24 hours), and an ultra-early threshold (8-12 hours)-the 2 earlier time points seem to be associated with the greatest potential for improved outcomes. However, existing prehospital and hospital logistics pose barriers to early surgery in a significant proportion of patients. An overview of recommendations from the recent AOSpine guidelines is provided. CONCLUSION: In spite of increasing acceptance of early surgery post SCI, further research is needed to (1) identify subgroups of patients who stand to derive particular benefit-in particular to develop more evidence-based approaches for central cord syndrome and (2) investigate the efficacy and feasibility of ultra-early surgery targeting more aggressive timelines.
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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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".