Arm Morbidity and Disability After Breast Cancer: New Directions for Care
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: To chart the incidence and course of three types of arm morbidity (lymphedema, pain, and range of motion [ROM] restrictions) in women with breast cancer 6-12 months after surgery and the relationship between arm morbidity and disability. DESIGN: Longitudinal mixed methods approach. SETTING: Four sites across Canada. SAMPLE: 347 patients with breast cancer 6-12 months after surgery at first point of data collection. METHODS: Incidence rates were calculated for three types of arm morbidity, correlations between arm morbidity and disability were computed, and open-ended survey responses were compiled and reviewed. MAIN RESEARCH VARIABLES: Lymphedema, pain, ROM, and arm, shoulder, and hand disabilities. FINDINGS: Almost 12% of participants experienced lymphedema, 39% reported pain, and about 50% had ROM restrictions. Little overlap in the three types of arm morbidity was observed. Pain and ROM restrictions correlated significantly with disability, but most women did not discuss arm morbidity with healthcare professionals. CONCLUSIONS: Pain and ROM restrictions are prevalent 6-12 months after surgery, but lymphedema is not. Pain and ROM restrictions are associated with disability. IMPLICATIONS FOR NURSING: Screening for pain and ROM restrictions should be part of breast cancer follow-up care. Left untreated, arm morbidity could have a long-term effect on quality of life. Additional research into the longevity of various arm morbidity symptoms and possible interrelationships also is required.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".