The Effect of Prospective Monitoring and Early Physiotherapy Intervention on Arm Morbidity Following Surgery for Breast Cancer: A Pilot Study
Bibliographic record
Abstract
PURPOSE: Significant arm morbidity is reported following surgery for breast cancer, yet physiotherapy is not commonly part of usual care. This study compared the effect on arm morbidity after surgery for breast cancer of a clinical care pathway including preoperative education, prospective monitoring, and early physiotherapy (experimental group) to that of preoperative education alone (comparison group). METHODS: A prospective quasi-experimental pretest-posttest, non-equivalent group design compared two clinical sites; Site A (n=41) received the experimental intervention, and Site B (n=31) received the comparison intervention. At baseline (preoperative) and 7 months postoperative, shoulder range of motion (ROM), upper-extremity (UE) strength, UE circumference, pain, UE function, and quality of life were assessed. RESULTS: The experimental group maintained shoulder flexion ROM at 7 months, whereas the comparison group saw a decrease (mean 1° [SD 9°] vs. -6° [SD 15°], p=0.03). A lower incidence of arm morbidity and better quality of life were observed in the experimental group, but these findings were not statistically significant. Baseline characteristics and surgical approaches differed between the two sites, which may have had an impact on the findings. CONCLUSION: Initial results are promising and support the feasibility of integrating a surveillance approach into follow-up care. This pilot study provides the foundation for a larger, more definitive trial.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".