A pilot study of a randomized controlled trial to evaluate the effects of progressive resistance exercise training on shoulder dysfunction caused by spinal accessory neurapraxia/neurectomy in head and neck cancer survivors
Bibliographic record
Abstract
BACKGROUND: Shoulder dysfunction remains a frequent complication after neck dissection procedures for head and neck cancer. METHODS: We conducted a pilot study to evaluate the effects of progressive resistance exercise training (PRET) on shoulder dysfunction caused by spinal accessory neurapraxia/neurectomy in patients with head and neck cancer. Twenty patients (mean age, 61 +/- 7.7 years) were randomly assigned to PRET or standard care intervention. Subjects assigned to the PRET group exercised three times per week for 12 weeks. The goal of the exercise program was to enhance scapular stability and strength of the upper extremity. The resistance-training program was progressive in terms of number of sets and repetitions performed, as well as the amount of weight lifted, depending on performance status. RESULTS: The completion rate for the trial was 85% (17 of 20). The exercise group completed 93% of scheduled exercise sessions. Significant improvements were found in favor of the PRET group in active shoulder external rotation (p =.001), shoulder pain (p =.038), and overall score for shoulder pain and disability (p =.045). CONCLUSIONS: The study results demonstrate a high rate of completion and adherence with our PRET program among patients with head and neck cancer. The preliminary findings, although limited, also suggest a potential therapeutic role for resistance exercise as an adjunct to standard physical therapy treatment.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".