Acute Adverse Events After Spinal Cord Injury and Their Relationship to Long-term Neurologic and Functional Outcomes: Analysis From the North American Clinical Trials Network for Spinal Cord Injury
Bibliographic record
Abstract
OBJECTIVES: There are few contemporary, prospective multicenter series on the spectrum of acute adverse events and their relationship to long-term outcomes after traumatic spinal cord injury. The goal of this study is to assess the prevalence of adverse events after traumatic spinal cord injury and to evaluate the effects on long-term clinical outcome. DESIGN: Multicenter prospective registry. SETTING: Consortium of 11 university-affiliated medical centers in the North American Clinical Trials Network. PATIENTS: Eight-hundred one spinal cord injury patients enrolled by participating centers. INTERVENTIONS: Appropriate spinal cord injury treatment at individual centers. MEASUREMENTS AND MAIN RESULTS: A total of 2,303 adverse events were recorded for 502 patients (63%). Penalized maximum logistic regression models were fitted to estimate the likelihood of neurologic recovery (ASIA Impairment Scale improvement ≥ 1 grade point) and functional outcomes in subjects who developed adverse events at 6 months postinjury. After accounting for potential confounders, the group that developed adverse events showed less neurologic recovery (odds ratio, 0.55; 95% CI, 0.32-0.96) and was more likely to require assisted breathing (odds ratio, 6.55; 95% CI, 1.17-36.67); dependent ambulation (odds ratio, 7.38; 95% CI, 4.35-13.06) and have impaired bladder (odds ratio, 9.63; 95% CI, 5.19-17.87) or bowel function (odds ratio, 7.86; 95% CI, 4.31-14.32) measured using the Spinal Cord Independence Measure subscores. CONCLUSIONS: Results from this contemporary series demonstrate that acute adverse events are common and are associated with worsened long-term outcomes after traumatic spinal cord injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.045 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".