Effect of Neuromuscular Electrical Stimulation After Total Knee Arthroplasty: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
Background: This systematic review and meta-analysis aimed to evaluate the effect of neuromuscular electrical stimulation (NMES) on quadriceps muscle strength, pain, and function outcomes following total knee arthroplasty (TKA). Methods: PubMed/Medline, Embase, Web of Science, CENTRAL, Scopus, PsycINFO, PEDro, CINAHL, CNKI, and Wanfang were systematically searched for randomized controlled trials (RCTs) from their inception to 18 June 2021. Results: Nine RCTs that involving 691 patients were included in the meta-analysis. Our pooled analysis showed that NMES improved quadriceps muscle strength after TKA within 1 months [standardized mean difference (SMD): 0.81; 95% CI: 0.51–1.11], 1–2 months (SMD: 0.55; 95% CI: 0.13–0.97), 3–4 months (SMD: 0.42; 95% CI: 0.18–0.66), and 12–13 months (SMD: 0.46; 95% CI: 0.18–0.74), pain between 1 and 2 months [mean difference (MD): −0.62; 95% CI: −1.04 to −0.19], pain between 3 and 6 months (MD: −0.44; 95% CI: −0.74 to −0.14) Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) between 3 and 4 months (MD: −0.43; 95% CI: −0.82 to −0.05), timed up and go test (TUG) within 1 month (MD: −2.23; 95% CI: −3.40 to −1.07), 3 minutes walk test between 3 and 6 months (MD: 28.35; 95% CI: 14.55–42.15), and SF-36 MCS between 3 and 6 months after TKA (MD: 4.20, 95% CI: 2.41–5.98). Conclusion: As a supplementary treatment after TKA, postoperative NMES could improve the short-term to long-term quadriceps muscle strength, mid-term pain, and mid-term function following TKA. However, many outcomes failed to achieve statistically meaningful changes and minimal clinically important difference (MCID), thus the clinical benefits remained to be confirmed. Level of Evidence: Therapeutic level I. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/ , identifier CRD42021265609.
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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 | 0.021 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.040 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".