Management of Acute Traumatic Central Cord Syndrome: A Narrative Review
Bibliographic record
Abstract
STUDY DESIGN: Narrative review. OBJECTIVES: To provide an updated overview of the management of acute traumatic central cord syndrome (ATCCS). METHODS: A comprehensive narrative review of the literature was done to identify evidence-based treatment strategies for patients diagnosed with ATCCS. RESULTS: ATCCS is the most commonly encountered subtype of incomplete spinal cord injury and is characterized by worse sensory and motor function in the upper extremities compared with the lower extremities. It is most commonly seen in the setting of trauma such as motor vehicles or falls in elderly patients. The operative management of this injury has been historically variable as it can be seen in the setting of mechanical instability or preexisting cervical stenosis alone. While each patient should be evaluated on an individual basis, based on the current literature, the authors' preferred treatment is to perform early decompression and stabilization in patients that have any instability or significant neurologic deficit. Surgical intervention, in the appropriate patient, is associated with an earlier improvement in neurologic status, shorter hospital stay, and shorter intensive care unit stay. CONCLUSIONS: While there is limited evidence regarding management of ATCCS, in the presence of mechanical instability or ongoing cord compression, surgical management is the treatment of choice. Further research needs to be conducted regarding treatment strategies and patient outcomes.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".