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Record W3136868899 · doi:10.1111/ijd.15495

The increasing problem of treatment‐resistant fungal infections: a call for antifungal stewardship programs

2021· review· en· W3136868899 on OpenAlexaff
Aditya K. Gupta, M. Venkataraman, Helen J. Renaud, Richard C. Summerbell, Neil H. Shear, Vincent Piguet

Bibliographic record

VenueInternational Journal of Dermatology · 2021
Typereview
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsWomen's College HospitalHealth Sciences CentreSunnybrook Health Science CentreUniversity of TorontoMediprobe Research (Canada)Public Health Ontario
Fundersnot available
KeywordsAntifungalStewardship (theology)MedicineAntimicrobial stewardshipIntensive care medicineIncidence (geometry)AntibioticsAntibiotic resistanceMicrobiologyBiologyDermatologyPolitical science

Abstract

fetched live from OpenAlex

Antimicrobial stewardship (AMS) programs have been widely recognized among the public health community. These programs focus majorly on bacterial infections, efficient antibiotic use, and measures to curb increasing antibacterial resistance. AMS programs are successfully established around the globe; however, very few include antifungal stewardship (AFS). The increasing incidence of superficial and invasive fungal infections, combined with delayed or inaccurate diagnosis, has contributed to the overprescribing and overuse of antifungal agents. Such increased exposure to antifungal agents may be a reason for the emergence of increasing antifungal resistance among fungal pathogens. With mounting reports of treatment failures and resistant infections, the evidence to support the need for AFS programs is increasing. AFS is an emerging branch of AMS programs that requires global attention and recognition.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.058
GPT teacher head0.389
Teacher spread0.331 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations34
Published2021
Admission routes1
Has abstractyes

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