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Record W1999139232 · doi:10.1097/mop.0b013e32834c4b12

Advances in management of low-risk febrile neutropenia

2011· review· en· W1999139232 on OpenAlexafffund
Oliver Teuffel, Lillian Sung

Bibliographic record

VenueCurrent Opinion in Pediatrics · 2011
Typereview
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsSickKids FoundationInstitute for Clinical Evaluative SciencesHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsMedicineFebrile neutropeniaIntensive care medicineAmbulatoryAmbulatory careNeutropeniaInpatient careHealth careInternal medicineChemotherapy

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.971
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.076
GPT teacher head0.404
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations16
Published2011
Admission routes2
Has abstractyes

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