Evaluation of the effectiveness of telerehabilitation in cases with rotator cuff tendinopathy
Bibliographic record
Abstract
Objective: Our study was designed to investigate the effectiveness of adding telerehabilitation (TR) to a home exercise program (HEP) in patients with rotator cuff tendinopathy. Patients and Methods: The study included 45 patients diagnosed with rotator cuff tendinopathy and randomly assigned into two groups. The control group was given a HEP, while the study group received the same program supplemented with TR and following the intervention, patients’ shoulder joint range of motion (ROM) was assessed with a goniometer, and functionality was evaluated using the Western Ontario Rotator Cuff Index (WORC) and the Simple Shoulder Test (SST). Results: In intra-group assessments, there was a significant decrease in the WORC physical symptoms subscale in the TR group at the follow-up assessment (p<0.001), whereas no significant difference was found in the HEP group (p=0.189). Regarding the total SST score, an increase was seen in the TR group post-treatment (p<0.001), while no difference was found in the HEP group (p=0.373). Upon comparing TR and HEP, including increased active abduction of the right shoulder, as well as active flexion, abduction, and external rotation of the left shoulder, the two groups groups showed that TR group patients had significantly better results than HEP group patients in WORC and SST (p=0.007 and p=0.007 respectively). Conclusion: The results of our study indicate that following a HEP with TR enhances shoulder mobility and functionality more effectively than the HEP alone in patients with rotator cuff pathology.
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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) | 0.002 | 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".