Comparing Conventional Physical Therapy Rehabilitation With Neuromuscular Electrical Stimulation After TKA
Bibliographic record
Abstract
Rehabilitation following total knee arthroplasty (TKA) is a costly, cumbersome, and often painful process. Physical therapy contributes to the successful outcome of TKA but can be expensive. Alternative methods of obtaining good functional results that help minimize costs are desirable. Neuromuscular electrical stimulation (NMES) is a potential option. Neuromuscular electrical stimulation has been shown to increase quadriceps muscle strength and activation following TKA. Functional scores also improve following TKA when NMES is added to conventional therapy protocols vs therapy alone. The authors hypothesized that rehabilitation managed by a physical therapist would not result in a functional advantage for patients undergoing TKA when compared with NMES and an unsupervised at-home range of motion exercise program and that patient satisfaction would not differ between the 2 groups. Seventy patients were randomized into a postoperative protocol of conventional physical therapy with a licensed therapist, including range of motion exercises and strengthening exercises, or into a program of NMES and range of motion exercises performed at home without therapist supervision. Noninferiority of the NMES program was obtained 6 weeks postoperatively (Knee Society pain/function scores, Western Ontario and McMaster Universities Osteoarthritis Index, flexion). Noninferiority was shown 6 months postoperatively for all parameters. The results suggest that rehabilitation managed by a physical therapist results in no functional advantage or difference in patient satisfaction when compared with NMES and an unsupervised at-home range of motion program. Neuromuscular electrical stimulation and unsupervised at-home range of motion exercises may provide an option for reducing the cost of the postoperative TKA recovery process without compromising quadriceps strength or patient satisfaction.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".