A Case Report on the Impact of Physiotherapy on Shoulder Function in Breast Cancer Patients Undergoing Surgery
Bibliographic record
Abstract
Early breast cancer treatment can cause shoulder dysfunction, which is a well-known and prevalent adverse effect (1). In individuals treated surgically for breast cancer, physiotherapy was found to enhance shoulder function considerably (1). Breast cancer is the most common type of cancer in women and the leading cause of death and morbidity (2). Every year, 1.67 million new instances of breast cancer are identified worldwide, with 458,000 fatalities (2). Although 89 percent of breast cancer survivors live for at least five years after treatment, side symptoms can continue for months or even years(2). The most common upper-limb side effects are pain and joint dysfunction, with prevalence rates ranging from 12% to 51% for pain and 1.5 percent to 50% for joint dysfunction. Surgery is the most common treatment for primary breast cancer. Shoulder exercises are commonly advised to reduce mobility and strength loss as well as prevent lymphedema. Several clinical services have been developed to help with shoulder range of motion rehabilitation and secondary lymphedema prevention(3) . The goal of this study was to see how additional postoperative physiotherapy affected shoulder function after the initial postoperative healing period, especially when given for a longer period. Patients who have had a mastectomy are always at risk of getting shoulder pain and adhesive capsulitis, and they must take precautions (3). Key words: Modified radical mastectomy, shoulder pain, breast cancer, lymph nodes, physiotherapy rehabilitation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".