Exercise for Women With or at Risk for Breast Cancer–Related Lymphedema
Bibliographic record
Abstract
Breast cancer accounts for approximately one third of all cancers diagnosed in American women. In 2005, it was estimated that 211,240 women would be diagnosed with invasive breast cancer in the United States and 58,490 would be diagnosed with in situ breast cancer.1 Although advancements in technology have led to early detection and a higher survival rate,2 approximately 40,410 US women were expected to die from this disease in 2005.1 Many women experience secondary complications of the disease and its treatments, including decreased quality of life (QOL), weight gain, sleep disturbances, poor body image, fatigue,3 increased risk for osteoporosis, cardiovascular disease, premature menopause, and lymphedema.4 Breast cancer is commonly treated by surgery, chemotherapy, or radiation. Axillary dissection or radiation can result in lymphedema due to obstruction, trauma, and inflammation of the lymphatic system.5 Lymphedema has been defined as an abnormal accumulation of protein-rich fluid,4,6 edema, and chronic inflammation5,7 and can elicit pain, tightness, and heaviness in the upper extremity (UE), as well as lead to recurrent skin infections.8 Lymphedema is classified into 3 stages based on severity. Stage I lymphedema is spontaneously reversible9 and typically involves pitting edema, an increase in UE girth, and heaviness.8 Stage II is marked by a spongy consistency of the tissue without signs of pitting edema. Tissue fibrosis causes limbs to harden and increase in size. Stage III, lymphostatic elephantiasis, is the most advanced stage but is rarely seen following breast cancer treatment.9 Management of lymphedema in women with breast cancer has been a subject of debate for many years. Treatment options include elevation, massage, compression garments, pneumatic compression pumps, and complex physical therapy.8 Traditionally, women who had been treated for breast cancer and those with pre-existing lymphedema …
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 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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".