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Record W2164149772 · doi:10.1128/aac.01519-13

Interlaboratory Variability of Caspofungin MICs for Candida spp. Using CLSI and EUCAST Methods: Should the Clinical Laboratory Be Testing This Agent?

2013· article· en· W2164149772 on OpenAlexaffabout
Ana Espinel‐Ingroff, Maiken Cavling Arendrup, Michael A. Pfaller, Lucas Xavier Bonfietti, Beatriz Bustamante, Rafael Cantón, Erja Chryssanthou, Manuel Cuenca‐Estrella, Éric Dannaoui, A. Fothergill, Jeffrey Fuller, Peter Gaustad, Gloria M. González, Josep Guarro, Cornelia Lass‐Flörl, Shawn R. Lockhart, Jacques F. Meis, Caroline B. Moore, Luis Ostrosky‐Zeichner, Teresa Peláez, S. R. B. S. Pukinskas, G. St‐Germain, Maria Walderez Szeszs, John Turnidge

Bibliographic record

VenueAntimicrobial Agents and Chemotherapy · 2013
Typearticle
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsInstitut National de Santé Publique du QuébecUniversity of Alberta
FundersCenters for Disease Control and Prevention
KeywordsCaspofunginMicrobiologyCandida glabrataCorpus albicansMicafunginBiologyBroth microdilutionCandida albicansVeterinary medicineAntifungalAmphotericin BMedicineAntimicrobialMinimum inhibitory concentration

Abstract

fetched live from OpenAlex

Although Clinical and Laboratory Standards Institute (CLSI) clinical breakpoints (CBPs) are available for interpreting echinocandin MICs for Candida spp., epidemiologic cutoff values (ECVs) based on collective MIC data from multiple laboratories have not been defined. While collating CLSI caspofungin MICs for 145 to 11,550 Candida isolates from 17 laboratories (Brazil, Canada, Europe, Mexico, Peru, and the United States), we observed an extraordinary amount of modal variability (wide ranges) among laboratories as well as truncated and bimodal MIC distributions. The species-specific modes across different laboratories ranged from 0.016 to 0.5 μg/ml for C. albicans and C. tropicalis, 0.031 to 0.5 μg/ml for C. glabrata, and 0.063 to 1 μg/ml for C. krusei. Variability was also similar among MIC distributions for C. dubliniensis and C. lusitaniae. The exceptions were C. parapsilosis and C. guilliermondii MIC distributions, where most modes were within one 2-fold dilution of each other. These findings were consistent with available data from the European Committee on Antimicrobial Susceptibility Testing (EUCAST) (403 to 2,556 MICs) for C. albicans, C. glabrata, C. krusei, and C. tropicalis. Although many factors (caspofungin powder source, stock solution solvent, powder storage time length and temperature, and MIC determination testing parameters) were examined as a potential cause of such unprecedented variability, a single specific cause was not identified. Therefore, it seems highly likely that the use of the CLSI species-specific caspofungin CBPs could lead to reporting an excessive number of wild-type (WT) isolates (e.g., C. glabrata and C. krusei) as either non-WT or resistant isolates. Until this problem is resolved, routine testing or reporting of CLSI caspofungin MICs for Candida is not recommended; micafungin or anidulafungin data could be used instead.

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)0.123
metaresearch head score (Gemma)0.163
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.123
Threshold uncertainty score0.652

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1230.163
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0010.003
Scholarly communication0.0040.003
Open science0.0020.001
Research integrity0.0030.002
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 head0.113
GPT teacher head0.407
Teacher spread0.294 · 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 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

Citations208
Published2013
Admission routes2
Has abstractyes

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