Functional Electrical Stimulation Therapy of Voluntary Grasping Versus Only Conventional Rehabilitation for Patients With Subacute Incomplete Tetraplegia
Bibliographic record
Abstract
BACKGROUND: Functional electrical stimulation therapy (FET) has a potential to improve voluntary grasping among individuals with tetraplegia secondary to traumatic spinal cord injury (SCI). OBJECTIVE: This single-site, randomized controlled trial examined the efficacy of 40 hours of FET with conventional occupational therapy (COT) compared with COT alone to improve grasping. METHODS: Twenty-four subjects with subacute traumatic incomplete SCI (C4-C7, AIS B-D) consented to participate in 40 hours of therapy over 8 weeks, beyond the conventional rehabilitation program. Subjects were randomized to receive FET + COT (n = 9) or COT (n = 12). The key outcomes were changes in Functional Independence Measure (FIM) self-care subscores, Spinal Cord Independence Measure (SCIM) self-care subscores, and Toronto Rehabilitation Institute Hand Function Test (TRI-HFT) performed at baseline and follow-up. RESULTS: At the end of the treatments, the change in mean FIM self-care subscore for the FET + COT group was 20.1 versus 10 (P = .015) for the COT group. Subjects randomized to FET + COT also had greater improvements in the SCIM and TRI-HFT. No longer term follow-up was feasible. CONCLUSION: FET significantly reduced disability and improved voluntary grasping beyond the effects of considerable conventional upper extremity therapy in individuals with tetraplegia.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.004 | 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".