Functional Electrical Stimulation for Improving Gait in Persons With Chronic Stroke
Bibliographic record
Abstract
BACKGROUND: The long-term management of stroke is an area of increasing clinical interest, and it is important to identify therapeutic interventions that are effective in the chronic phase post stroke. OBJECTIVE: To conduct a systematic review on the effectiveness of functional electrical stimulation (FES) in improving lower extremity function in chronic stroke. METHODS: Multiple databases (PubMed, CINAHL, EMBASE, and Scopus) were searched for relevant articles. Studies were included for review if (1) ≥50% of the study population has sustained a stroke, (2) the study design was a randomized controlled trial (RCT), (3) the mean time since stroke was ≥6 months, (4) FES or neuromuscular electrical stimulation (NMES) was compared to other interventions or a control group, and (5) functional lower extremity outcomes were assessed. Methodological quality was assessed using the PEDro tool. A standardized mean difference (SMD ± SE and 95% confidence interval [CI]) was calculated for the 6-minute walk test (6MWT). Pooled analysis was conducted for treatment effect of FES on the 6MWT distance using a fixed effects model. RESULTS: Seven RCTs (PEDro scores 5-7) including a pooled sample size of 231 participants met inclusion criteria. Pooled analysis revealed a small but significant treatment effect of FES (0.379 ± 0.152; 95% CI, 0.081 to 0.677; P = .013) on 6MWT distance. CONCLUSION: FES may be an effective intervention in the chronic phase post stroke. However, its therapeutic value in improving lower extremity function and superiority over other gait training approaches remains unclear.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".