A Systematic Review of Safety Reporting in Acute Spinal Cord Injury Clinical Trials: Challenges and Recommendations
Bibliographic record
Abstract
Accurate safety information in published clinical trials guides the assessment of risk-benefit, as well as the design of future clinical trials. Comprehensive reporting of adverse events, toxicity, and discontinuations from acute spinal cord injury clinical trials is an essential step in this process. Here, we sought to assess the degree of "satisfactoriness" of reporting in past clinical trials in spinal cord injury. A review of citations from MEDLINE and EMBASE identified eligible clinical trials in acute (within 30 days) spinal cord injury. English language studies, published between 1980 and 2020, with sensory, motor, or autonomic neurological assessments as the primary outcome measure were eligible for inclusion. Criteria were then established to qualify the safety reporting as satisfactory (i.e., distinguished severe/life-threatening events), partially satisfactory, or unsatisfactory (i.e., only mentioned in general statements, or reported but without distinguishing severe events). A total of 40 trials were included. Satisfactory reporting for clinical adverse events was observed in 30% of trials; partially satisfactory was achieved by 10% of the trials, and the remaining 60% were unsatisfactory. The majority of trials were determined to be unsatisfactory for the reporting of laboratory-defined toxicity (82.5%); only 17.5% were satisfactory. Discontinuations were satisfactorily reported for the majority of trials (80%), with the remaining partially satisfactory (5%) or unsatisfactory (15%). Reporting of safety in clinical trials for acute spinal cord injury is suboptimal. Due to the complexities of acute spinal cord injury (e.g., polytrauma, multiple systems affected), tailored and specific standards for tracking adverse events and safety reporting should be established.
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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 | 0.305 | 0.635 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.017 | 0.011 |
| Bibliometrics | 0.025 | 0.021 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.012 | 0.019 |
| Open science | 0.009 | 0.006 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".