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Record W4383872779 · doi:10.1128/jcm.00562-23

Terbinafine-Resistant Dermatophytes and the Presence of Trichophyton indotineae in North America

2023· article· en· W4383872779 on OpenAlexaboutno aff
Connie Cañete‐Gibas, James Mele, Hoja Patterson, Carmita Sanders, Dora Ferrer, Víctor García, Hongxin Fan, Marjorie David, Nathan P. Wiederhold

Bibliographic record

VenueJournal of Clinical Microbiology · 2023
Typearticle
Languageen
FieldMedicine
TopicNail Diseases and Treatments
Canadian institutionsnot available
FundersAstellas Pharma
KeywordsTerbinafineTrichophyton rubrumPosaconazoleDermatophyteItraconazoleTrichophytonBroth microdilutionVoriconazoleMicrobiologyBiologyMicrosporumMinimum inhibitory concentrationVeterinary medicineMedicineAntifungalAntibiotics

Abstract

fetched live from OpenAlex

resistance. Susceptibility testing was performed by CLSI broth microdilution methods, and species identification was performed by DNA sequence analysis. During this 2-year period, 271 dermatophyte isolates were included, the majority of which demonstrated low MIC values for terbinafine (geometric mean [GM] and modal MIC, 0.031 μg/mL and 0.008 μg/mL, respectively) and the azoles itraconazole, posaconazole, and voriconazole (0.035 to 0.049 μg/mL and ≤0.03 μg/mL). However, 18.6% of the isolates tested were resistant to terbinafine (MIC ≥ 0.5 μg/mL), including 21 T. rubrum and 21 T. indotineae isolates. These isolates were received from several different states in the United States and two provinces in Canada. In contrast, resistance to itraconazole was relatively rare. We also searched our laboratory database for earlier isolates that were resistant to terbinafine and identified 3 additional T. indotineae isolates, the earliest of which was from 2017. These results demonstrate that terbinafine resistance in dermatophytes was relatively common over this 2-year period and that T. indotineae is present in multiple areas in North America. Continued surveillance is warranted.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.172

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.026
GPT teacher head0.349
Teacher spread0.323 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations93
Published2023
Admission routes1
Has abstractyes

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