Electroestimulación y feedback neuromuscular en la fase inicial de rehabilitación de la artroplastia total de la rodilla
Bibliographic record
Abstract
espanolObjetivo: Estudiar el efecto de la electroestimulacion con feedback del cuadriceps (EENM-feedback) en un programa estandar de rehabilitacion de artroplastia total de rodilla. Material y metodo: ensayo clinico en 83 pacientes intervenidos de artroplastia de rodilla por gonartrosis primaria. El protocolo postoperatorio se aleatorizo en un grupo de rehabilitacion estandar con EENM-feedback y otro grupo control de rehabilitacion estandar. Se valoro el balance articular (BA), el test «timed up and go» (TUG) y el cuestionario funcional WOMAC, antes de la artroplastia, al alta del hospital, al mes y a los 3 meses. Resultados: El BA y el WOMAC evolucionaron igual en ambos grupos. Al tercer mes, el TUG mejoro siginificativamente en el grupo de EENM-feedback (p Conclusiones: La aplicacion de EENM-feedback en el postoperatorio de la artroplastia total de rodilla puede ayudar a mejorar la capacidad de deambulacion a corto-medio plazo EnglishBackground: The aim of this study was to study the effect of feedback and neuromuscular electrical stimulation (feedback-NMS) on an standard rehabilitation protocol after total knee arthroplasty (TKA). Methods: Clinical trial in 83 patients undergoing TKA for primary knee osteoarthritis. After surgery, patients were randomized in feedback-NMS rehabilitation program or standard rehabilitation. Range of movement (ROM), timed up and go test (TUG) and the Western Ontario and MacMaster Universities (WOMAC osteoarthritis index) were tested previous surgery, at hospital discharge, one month and three moths after. Results: Changes in ROM and WOMAC values were similar in both groups. At three months TUG values were better than previous in feedback-NMS group (p Conclusions: Feedback and NMS as a immediate therapy after TKA can help to improve walking capacity in short-mid term
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".