A Pan-Canadian Practice Guideline and Algorithm: Screening, Assessment, and Supportive Care of Adults with Cancer-Related Fatigue
Bibliographic record
Abstract
PURPOSE: The purpose of the present systematic review was to develop a practice guideline to inform health care providers about screening, assessment, and effective management of cancer-related fatigue (crf) in adults. METHODS: The internationally endorsed adapte methodology was used to develop a practice guideline for pan-Canadian use. A systematic search of the literature identified a broad range of evidence: clinical practice guidelines, systematic reviews, and other guidance documents on the screening, assessment, and management of crf. The search included medline, embase, cinahl, the Cochrane Library, and other guideline and data sources to December 2009. RESULTS: Two clinical practice guidelines were identified for adaptation. Seven guidance documents and four systematic reviews also provided supplementary evidence to inform guideline recommendations. Health professionals across Canada provided expert feedback on the adapted recommendations in the practice guideline and algorithm through a participatory external review process. CONCLUSIONS: Practice guidelines can facilitate the adoption of evidence-based assessment and interventions for adult cancer patients experiencing fatigue. Development of an algorithm to guide decision-making in practice may also foster the uptake of a guideline into routine care.
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 | 0.042 | 0.113 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.009 | 0.004 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".