Bibliographic record
Abstract
PURPOSE OF REVIEW: To describe and discuss the most recent advances in the management of low-risk febrile neutropenia in children with cancer. RECENT FINDINGS: Several risk stratification tools for children with febrile neutropenia have been developed, although none of these tools have been directly compared and few have been validated in independent populations. However, there is good evidence that, for pediatric patients with febrile neutropenia at low risk for severe infection, outpatient management is a well tolerated and efficacious alternative to inpatient care. Moreover, major progress has been made in obtaining and understanding perceived quality of life and preferences for outpatient management in pediatric cancer patients. Many parents prefer inpatient management although child quality of life is, in general, anticipated to be higher with outpatient intravenous therapy. Finally, outpatient strategies are more cost-effective as compared with traditional management in hospital. SUMMARY: Outpatient management is a well tolerated and cost-effective strategy for low-risk febrile neutropenia in children with cancer, although parental preferences are highly variable for outpatient versus inpatient management. Future research should examine the effectiveness of outpatient strategies through conduct of large cohort studies. Other future work could focus on development of decision aids and other tools to facilitate ambulatory approaches.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".