Shoulder Dysfunction in Breast Cancer Survivors: Can Treatment Type or Musculoskeletal Factors Identify Those at Higher Risk?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background and Objective: Breast cancer is the most commonly diagnosed cancer in Canadian women. Breast cancer survivors are known to experience shoulder dysfunction, but the influence of musculoskeletal and treatment factors has yet to be investigated in a Saskatchewan population, which was the purpose of this study. Methods: Two study designs were used to assess risk factors for dysfunction: (1) a cross-sectional Web-based questionnaire and (2) prospective cohort analysis of preoperative musculoskeletal assessment combined with postoperative Shoulder Pain and Disability Index (SPADI) score. Data from the survey were summarized and analyzed using χ 2 tests ( P < .05), while nonparametric measures were used to calculate temporal differences and associations between musculoskeletal risk factors and disability. Results: Commonly reported shoulder problems after treatment were stiffness (63.5%), restricted range of motion (61.9%), and changes in arm/hand sensation (61.9%). Axillary lymph node dissection and radiation therapy were associated with more shoulder problems than other treatment types. SPADI scores increased by an average of 8.1% from baseline to 3 months postsurgery. A clinically significant 18% increase between these time points was moderately associated with a history of shoulder problems and restricted humeral extension preoperatively (average = 37.7° vs 48.9°). Conclusions: Breast cancer survivors from Saskatchewan have a high prevalence of shoulder problems following treatment. Clinically significant impairments in shoulder function are associated with select treatment types and preoperative impairments. These results can be used to identify high-risk patients before cancer treatment and direct their 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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it