Retrospective Study of Rehabilitation Exercise Combined with Extracorporeal Shock Wave Therapy for Knee Osteoarthritis
Bibliographic record
Abstract
BACKGROUND The aim of this study was to investigate the effect of rehabilitation exercise combined with extracorporeal shock wave therapy (ESWT) on knee osteoarthritis (KOA). MATERIAL AND METHODS The clinical data of 217 patients with KOA who underwent ESWT in our hospital from December 2017 to January 2020 were retrospectively analyzed. The patients were divided into a rehabilitation exercise (RE) group and a non-rehabilitation exercise (NRE) group according to whether they were given RE. The treatment course of the 2 groups was 5 weeks. Pain Visual Analog Scale (VSA), Western Ontario and McMaster Universities knee osteoarthritis index visualized scale (WOMAC), Lequesne index scores, Range of motion (ROM) score, and Japanese Orthopaedic Association (JOA) scores were used to evaluate the treatment effect of the 2 groups of patients. RESULTS After 5 weeks of treatment, the VSA scores (p<0.001), WOMAC scores (P<0.001) and Lequesne index scores (P<0.001) of the RE group and NRE group were significantly lower than those before treatment, while ROM score (P<0.001) and JOA score (p=0.006) were significantly increased. Compared with the NRE group, the VAS score (3.14±0.64 vs. 4.78±0.85, P=0.002), WOMAC score (20.37±4.06 vs. 27.82±4.57, P<0.001) and Lequesne index score (6.13±1.83 vs. 7.35±2.21, P=0.019) in the RE group were significantly lower than those in the NHE group; however, the ROM score (89.13±9.83 vs. 79.15±6.25, P=0.021) and JOA score (79.53±7.59 vs. 67.85±8.27, P=0.016) were significantly higher than those in the NRE group. CONCLUSIONS RE combined with ESWT has a positive effect on KOA, which may more significantly relieve the patient's clinical symptoms and improve joint function and quality of life.
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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 | 0.000 | 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 | 0.001 | 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) | 0.002 | 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".