Reality of Accomplishing Surgery within 24 Hours for Complete Cervical Spinal Cord Injury: Clinical Practices and Safety
Bibliographic record
Abstract
Substantial clinical data support an association between superior neurological outcomes and early (within 24 h) surgical decompression for those with traumatic cervical spinal cord injury (SCI). Despite this, much discussion persists around feasibility and safety of this time threshold, particularly for those with a complete cervical SCI. This study aims to assess clinical practices and the safety profile of early surgery across a large sample of North American trauma centers. Data were derived from the Trauma Quality Improvement Program database from 2010-2016. Adult patients with a complete cervical SCI (American Spinal Injury Association [ASIA] A) who underwent surgery were included. Patients were stratified into those receiving surgery at or before 24 h and those receiving delayed intervention. Risk-adjusted variability in surgical timing across trauma centers was investigated using mixed-effects regression. In-hospital adverse events including death, major complications, and immobility-related complications were compared between groups after propensity score matching. There were 2862 patients from 353 North American trauma centers included; 1760 (61.5%) underwent surgery within 24 h. Case-mix and hospital-level characteristics explained only 6% of the variability in surgical timing both between centers and within centers. No significant differences in adverse events were identified between groups. These findings suggest a relatively large proportion of patients are not receiving surgery within the recommended time frame, despite apparent safety. Moreover, patient and hospital-level characteristics explain little of the variability in time-to-surgery. Further knowledge translation is needed to increase the proportion of patients in whom surgery is performed before the 24-h threshold so patients might reach their greatest potential for neurological recovery.
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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 | 0.005 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".