Safety and Feasibility of Early Activity-Based Therapy Following Severe Traumatic Spinal Cord Injury: Results from a Single-Arm Pilot Trial
Bibliographic record
Abstract
Early activity-based therapy (E-ABT) has the potential to decrease complications and radically improve neurofunctional recovery following traumatic spinal cord injury (TSCI). Unfortunately, E-ABT after TSCI has never been attempted in humans due to practical obstacles and potential safety concerns. This study aims to report on the safety and feasibility outcomes of the Protocol for Rapid Onset of Mobilization in Patients with Traumatic SCI (PROMPT-SCI) trial: the first-ever trial of E-ABT in critically ill patients who suffered a severe TSCI. To do so, 45 patients with severe TSCI were recruited to participate in the PROMPT-SCI trial between April 2021 and August 2023. The intervention consisted of daily 30-min sessions of motor-assisted in-bed leg cycling for 14 days, starting within 48 h of early surgery (≈72 h from the initial trauma). Adverse events were closely monitored, and completion rates were evaluated. Out of the 45 participants, 36 (80%) completed a full and safe session within 48 h of surgery and all participants managed to achieve this outcome within 72 h of surgery. Over the full 14-day protocol, the average completion rate of sessions was 87.2 ± 22.7% (range: 7.1-100.0%). A total of three patients were mechanically ventilated during the protocol and all three had 100% completion of sessions. Frequent reasons for unattempted/incomplete sessions were scheduling conflicts with activities related to care (e.g., bronchoscopy) and fatigue/uncontrolled pain before initiating cycling. We also report no neurological deterioration caused by cycling and no major adverse event recorded during or between sessions. In conclusion, this study suggests that E-ABT can be safely initiated within 48-72 h after a severe TSCI with no major adverse event. In the form of daily passive in-bed leg cycling, E-ABT is also acceptable for target users, and feasible over the course of the first weeks after the initial trauma, as shown by our excellent rate of completed sessions (87%). The present results also suggest that improved collaboration with intensive care unit staff, including intensivists and nurses, could improve these rates even further.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".