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Of Yeasts and Hyphae: A Hematologist’s Approach to Antifungal Therapy

2006· review· en· W2112746751 on OpenAlexaff
Eric J. Bow

Bibliographic record

VenueHematology · 2006
Typereview
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsHealth Sciences Centre
Fundersnot available
KeywordsMedicineIntensive care medicineAntifungalDiseaseImmunosuppressionAntimicrobialChemoprophylaxisInvasive candidiasisInternal medicineFluconazoleOncologyImmunologyBiologyDermatology

Abstract

fetched live from OpenAlex

Improvements in anticancer treatments, the ability to modify myelosuppression profiles, greater duration and intensity of immunosuppression, and the variety of available antimicrobial therapies have influenced the spectrum of pathogens associated with invasive fungal infection complicating treatment of hematological malignancies and hematopoietic stem cell transplantation. The approaches to the management of these infections encompass strategies of prevention for all those at risk, preemptive therapy based upon surrogates of infection before the onset of clinical disease, empirical therapy for patients with clinical evidence of early disease, and directed or targeted therapy for infected patients with established disease. Chemoprophylaxis is effective if applied to the highest risk patients over the duration of the risk. Preemptive strategies, while promising, have yet to be validated and linked to reliably predictive non-microbiological diagnostic techniques. Empirical antifungal therapy, as it is currently applied, now seems questionable. Patients with probable or proven invasive fungal infection still have suboptimal outcomes despite the availability of promising anti-fungal agents. Strategies examining the concept of dose-intensity and combination regimens require careful study and cannot yet be regarded as an acceptable standard of practice.

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 score0.964
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.084
GPT teacher head0.369
Teacher spread0.284 · 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

Citations13
Published2006
Admission routes1
Has abstractyes

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