P.130 The natural history of central cord syndrome and the role of surgical intervention: a retrospective review from 2005-2010
Bibliographic record
Abstract
Background: The management of central cord syndrome (CCS) is controversial. There is a perception that CCS patients tend to improve without the need for surgical intervention. The purpose of this study was to compare the clinical improvements of patients with traumatic SCI, both with and without CCS. Methods: Nova Scotia Provincial Trauma Registry was retrospectively reviewed from 2005-2010. Improvement in the American Spinal Injury Association (ASIA) Impairment Scale (AIS) was determined after mean 5 months follow-up. Results: The study population comprised 96 cases with SCI, subdivided into cases with AIS grade A, non-CCS cases with AIS grades B-D and CCS cases. 88% of the non-CCS and 65% of the CCS patients underwent surgical decompression, with mean operative times being 71.6±137.8 and 102.9±144.6 post injury (p=0.45). The mean improvements in the mean ASIA motor scores for the three groups were 1.3±6.5 and 15.6±35.0 and 22.5±14.6 (p=0.004) respectively, with a statistically significant difference only between the CCS and AIS grade A groups (p<0.001). 20%, 54% and 10% of the patients respectively, underwent an improvement of ≥ one AIS grades (p=0.018, c2=8.0). Conclusions: This retrospective review investigates the natural history of CCS and explores the role of surgical intervention on optimizing patient outcome.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".