Multicenter Study of Epidemiological Cutoff Values and Detection of Resistance in Candida spp. to Anidulafungin, Caspofungin, and Micafungin Using the Sensititre YeastOne Colorimetric Method
Bibliographic record
Abstract
Neither breakpoints (BPs) nor epidemiological cutoff values (ECVs) have been established for Candida spp. with anidulafungin, caspofungin, and micafungin when using the Sensititre YeastOne (SYO) broth dilution colorimetric method. In addition, reference caspofungin MICs have so far proven to be unreliable. Candida species wild-type (WT) MIC distributions (for microorganisms in a species/drug combination with no detectable phenotypic resistance) were established for 6,007 Candida albicans, 186 C. dubliniensis, 3,188 C. glabrata complex, 119 C. guilliermondii, 493 C. krusei, 205 C. lusitaniae, 3,136 C. parapsilosis complex, and 1,016 C. tropicalis isolates. SYO MIC data gathered from 38 laboratories in Australia, Canada, Europe, Mexico, New Zealand, South Africa, and the United States were pooled to statistically define SYO ECVs. ECVs for anidulafungin, caspofungin, and micafungin encompassing ≥97.5% of the statistically modeled population were, respectively, 0.12, 0.25, and 0.06 μg/ml for C. albicans, 0.12, 0.25, and 0.03 μg/ml for C. glabrata complex, 4, 2, and 4 μg/ml for C. parapsilosis complex, 0.5, 0.25, and 0.06 μg/ml for C. tropicalis, 0.25, 1, and 0.25 μg/ml for C. krusei, 0.25, 1, and 0.12 μg/ml for C. lusitaniae, 4, 2, and 2 μg/ml for C. guilliermondii, and 0.25, 0.25, and 0.12 μg/ml for C. dubliniensis. Species-specific SYO ECVs for anidulafungin, caspofungin, and micafungin correctly classified 72 (88.9%), 74 (91.4%), 76 (93.8%), respectively, of 81 Candida isolates with identified fks mutations. SYO ECVs may aid in detecting non-WT isolates with reduced susceptibility to anidulafungin, micafungin, and especially caspofungin, since testing the susceptibilities of Candida spp. to caspofungin by reference methodologies is not recommended.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".