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Record W2118140266 · doi:10.5737/23688076253281284

INTERNATIONAL PERSPECTIVE: Management of chemotherapy-induced febrile neutropenia among adult oncology patients: A review

2015· review· en· W2118140266 on OpenAlexvenueno aff
Audai Nader Saeed, Nijmeh Al‐Atiyyat

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2015
Typereview
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsnot available
Fundersnot available
KeywordsFebrile neutropeniaMedicineAntibioticsNeutropeniaChemotherapyIntensive care medicineClinical OncologyInternal medicineOncologyCancer

Abstract

fetched live from OpenAlex

The aim of this literature review is to investigate the safest and most appropriate actions for the management of chemotherapy-induced febrile neutropenia. A literature search was undertaken, including major computerized electronic databases (PUBMED, SPRINGER, and WILEY). All studies that discuss colony stimulating factor plus antibiotics versus antibiotics or colony stimulating factors alone for the treatment of febrile neutropenia in adult oncology patients were sought. A review of the selected studies was performed. Most studies focus on the prompt assessment and management for oncology patients who are experiencing febrile neutropenia by using appropriate antibiotics and highlight the importance of using antibiotics and colony stimulating factor in the management of chemotherapy-induced neutropenic fever. Key words: febrile neutropenia, chemotherapy, management, oncology patients

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.007
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.047
GPT teacher head0.417
Teacher spread0.370 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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

Citations0
Published2015
Admission routes1
Has abstractyes

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