Approach to Fever Assessment in Ambulatory Cancer Patients Receiving Chemotherapy: A Clinical Practice Guideline
Bibliographic record
Abstract
BACKGROUND: This guideline was prepared by the Fever Assessment Guideline Development Group, a group organized by the Program in Evidence-Based Care at the request of the Cancer Care Ontario Systemic Treatment Program. The mandate was to develop a standardized approach (in terms of definitions, information, and education) for the assessment of fever in cancer patients receiving chemotherapy. METHODS: The guideline development methods included a search for existing guidelines, literature searches in medline and embase for systematic reviews and primary studies, internal review by content and methodology experts, and external review by targeted experts and intended users. RESULTS: The search identified eight guidelines that had partial relevance to the topic of the present guideline and thirty-eight primary studies. The studies were mostly noncomparative prospective or retrospective studies. Few studies directly addressed the topic of fever except as one among many symptoms or adverse effects associated with chemotherapy. The recommendations concerning fever definition are supported mainly by other existing guidelines. No evidence was found that directly pertained to the assessment of fever before a diagnosis of febrile neutropenia was made. However, some studies evaluated approaches to symptom management that included fever among the symptoms. Few studies directly addressed information needs and resources for managing fever in cancer patients. CONCLUSIONS: Fever in patients with cancer who are receiving systemic therapy is a common and potentially serious symptom that requires prompt assessment, but currently, evidence to inform best practices concerning when, where, and by whom that assessment is done is very limited.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".