ONS Guidelines™ for Cancer Treatment–Related Lymphedema
Bibliographic record
Abstract
PURPOSE: Lymphedema is a chronic condition that may result from cancer-related surgery. The incidence of lymphedema varies greatly; however, patients remain at risk for life and may experience decreased quality of life and functional capacity. Providing recommendations for an evidence-based guideline for care of cancer treatment-related lymphedema will help to improve outcomes for patients with this chronic condition. METHODOLOGIC APPROACH: A panel of healthcare professionals with patient representation convened to develop a national clinical practice guideline on prospective surveillance, risk reduction, and conservative treatment of lymphedema. Systematic reviews of the literature were conducted and the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) methodology approach was used to assess the evidence. FINDINGS: The panel made multiple recommendations for patients who are at risk for or experiencing lymphedema. IMPLICATIONS FOR NURSING: Early diagnosis and treatment of lymphedema may mitigate symptoms. This evidence-based guideline supports patients, clinicians, and other healthcare professionals in clinical decision making. SUPPLEMENTARY MATERIAL CAN BE FOUND AT HTTPS: //onf.ons.org/supplementary-material-ons-guidelines-cancer-treatment-related-lymphedema.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.139 | 0.040 |
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".