The burden of acute care of patients with traumatic vs. non-traumatic SCI: A comparative study
Bibliographic record
Abstract
OBJECTIVE: Spinal tumors are the leading cause of acute SCI. Little is known about the care pathway and outcomes of patients with SCI due to NESCC. This paper aims to compare the burden of care of patients with TSCI vs. SCI caused by neoplastic epidural spinal cord compression (NESCC). DESIGN: Retrospective cohort study. SETTING: Level-1 trauma center in Montreal, Canada. PARTICIPANTS: of 441 consecutive patients with TSCI, or NESCC. METHODS: Sociodemographic variables and injury characteristics were collected. The rates of pneumonia, urinary tract infection, pressure injury, and the length of stay in the acute care before discharge were compared between patients with NTSCI vs. TSCI. Multivariable analyzes were then performed to determine if the etiology of SCI was independently associated with the outcomes above. RESULTS: Of the 441 patients recruited, 124 presented with NESCC and 317 with TSCI. Individuals with NESCC were less likely be male, were older, had more comorbidities and were more likely to present incomplete paraplegia. In addition, they had lower rates of pneumonia (8.1% vs. 19.2%; P = 0.004), UTI (10.5% vs. 20.5%; P = 0.013), and shorter average acute length of stay (21.7 ± 18.4 vs. 28.3 ± 20.2; P = 0.002), while the rates of pressure injuries were similar. At the multivariable level, a NTSCI was associated with lower odds of urinary tract infection (OR = 0.235; P = 0.013) and shorter LOS (=-0.189; P = 0.004). CONCLUSION: Despite being older and presenting more comorbidities, patients with NESCC have lower rates of acute complications and shorter length of stays in the acute hospitalization, regardless of the severity of the initial injury.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".