Evolving Profile of Acute Spinal Cord Injury Demographics, Outcomes, and Surgical Treatment in North America: Analysis of a Prospective Multi-Center Dataset of 989 Patients
Bibliographic record
Abstract
Changes in demography and injury patterns have altered the profile and outcome of acute spinal cord injury (SCI) over time. This study sought to describe recent trends in epidemiology and early clinical outcomes using the multi-center North American Clinical Trial Network (NACTN) for Spinal Cord Injury Registry. All participants with blunt acute traumatic SCI ( n = 782) were grouped into three five-year time intervals from 2005 to 2019 (2005–2009, 2010–2014, and 2015–2019). Baseline demographics, clinical scores, medical co-morbidities, as well as early clinical outcomes were extracted. Categorical and continuous variables were analyzed to determine between-group differences. Subgroup analysis was performed for participants <50 and ≥50 years of age. Over the duration of the study period, there was an increase in age at presentation ( p = 0.0077) as well as a greater incidence of falls as the mechanism of injury. Participants who were ≥50 years of age were more likely to sustain incomplete SCI (<0.0003) and central cord syndrome (< 0.0001). In the most recent period (2015–2019), a greater proportion of NACTN participants underwent surgery within 24 h of injury (63% vs. 41% vs. 41%, p = 0.0001). There was a statistically significant increase in cardiac complications ( p < 0.0001) and decrease in pulmonary complications ( p < 0.0001) during the study period. Data from the NACTN registry shows that the age of participants with acute SCI is increasing, falls have become the major mechanism of injury, and central cord injury is becoming increasingly prevalent. While early surgical intervention for acute SCI is more common in recent years, cardiac complications are more prevalent while pulmonary complications are less prevalent.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".