Management of fever and neutropenia in paediatric cancer patients
Bibliographic record
Abstract
PURPOSE OF REVIEW: Fever and neutropenia is the most common complication in the treatment of childhood cancer. This review will summarize recent publications that focus on improving the management of this condition as well as those that seek to optimize translational research efforts. RECENT FINDINGS: A number of clinical decision rules are available to assist in the identification of low-risk fever and neutropenia however few have undergone external validation and formal impact analysis. Emerging evidence suggests acute fever and neutropenia management strategies should include time to antibiotic recommendations, and quality improvement initiatives have focused on eliminating barriers to early antibiotic administration. Despite reported increases in antimicrobial resistance, few studies have focused on the prediction, prevention, and optimal treatment of these infections and the effect on risk stratification remains unknown. A consensus guideline for paediatric fever and neutropenia research is now available and may help reduce some of the heterogeneity between studies that have previously limited the translation of evidence into clinical practice. SUMMARY: Risk stratification is recommended for children with cancer and fever and neutropenia. Further research is required to quantify the overall impact of this approach and to refine exactly which children will benefit from early antibiotic administration as well as modifications to empiric regimens to cover antibiotic-resistant organisms.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".