Process Benchmarking Appraisal of Surgical Decompression of Spinal Cord following Traumatic Cervical Spinal Cord Injury: Opportunities To Reduce Delays in Surgical Management
Bibliographic record
Abstract
Prior pre-clinical and clinical studies indicate that early decompression of the spinal cord (≤ 24 h post-trauma) may have benefits regarding clinical outcomes and neurological recovery after spinal cord injury (SCI). This study examines the benchmarking of management of patients with acute traumatic cervical SCI in order to determine the potential barriers and ideal timelines for each step to early surgical decompression. We reviewed patient charts and the Surgical Trial in Acute Spinal Cord Injury Study (STASCIS) forms regarding the time and reasons for delay of each step in the management of patients with SCI. The reasons for delays were classified into: 1) health care-related ("extrinsic") factors and 2) patient-related ("intrinsic") factors. The cases were grouped into patients who underwent early surgical decompression of spinal cord (early-surgery group) and individuals who underwent later decompression (later-surgery group). Whereas both groups showed comparable time periods related to intrinsic factors, patients in the early surgery group had a significantly shorter time period associated with extrinsic factors when compared with the later surgery group. Both groups were comparable regarding pre-hospital time, time in a second general hospital prior to transfer to a spine center, and time in the trauma emergency department. Patients in the early surgery group had a significantly shorter waiting time, shorter waiting time for assessment by a spine surgeon, and a shorter waiting time for a surgical decision than did the later surgery group. Our benchmarking analysis suggests that health-related factors are key determinants of the timing from SCI to spinal cord decompression. Time in the general hospital and time of waiting for a surgical decision were the most important causes of delay of surgical spinal cord decompression. Early surgery is possible in the vast majority of the cases.
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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 | 0.012 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".