Use of clinical measures to document the effect of passive cycling on knee extensor spasticity and the ability to perform activities of daily living in spinal cord injury: a case report
Bibliographic record
Abstract
The effects, on spasticity-related clinical measure results [initial knee flexion velocity during the pendulum test (F1-VEL); Spinal Cord Injury Spasticity Evaluation Tool (SCI-SET) scores], of a 5-week passive cycling program were assessed in a 67-year-old man with chronic, complete, thoracic-level SCI. Three weekly evaluations were performed before and after training, at the start, middle, and end of the training (ET), and 24 h following ET. The F1-VEL increased significantly from baseline, from ET to the 2-week follow-up evaluation. A trend was found for an improvement from baseline in SCI-SET scores, from middle of training onwards. These findings, which can inform clinical decisions and clinical trial development, suggest that the F1-VEL pendulum test result may be used to document the effect on knee extensor spasticity of a passive cycling program in chronic, complete, thoracic-level SCI. Whether this is also true for the SCI-SET requires future confirmation.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".