Antifungal susceptibility of bloodstream yeasts isolated at a public children’s hospital in Brazil: comparison of the Etest<sup>®</sup> and the AFST–EUCAST microdilution method
Bibliographic record
Abstract
This study compared the minimum inhibitory concentration (MIC) results from the proposed standard methods of the Antifungal Susceptibility Testing Subcommittee of the European Committee on Antibiotic Susceptibility Testing (AFST-EUCAST) with the commercial system Etest(R) in the evaluation of susceptibility to flucytosine, fluconazole, itraconazole, voriconazole, and amphotericin B of 136 Candida spp. isolated from the blood of hospitalized children. The results presented a greater agreement among Etest(R) MICs +/-2 log2 dilutions of AFST-EUCAST for fluconazole (98.1% and 96.3%) and voriconazole (100% and 100%) for Candida albicans and Candida parapsilosis. For Candida glabrata, the agreement was greater only for fluconazole (81.8%) and voriconazole (100%). For amphotericin B, the agreement between the methods was low for all species. The agreement percentage among the Etest(R) and AFST-EUCAST susceptibility profiles was high according to the MIC breakpoints recommended by the M27-A2 protocol for the majority of the yeasts, except for fluconazole and itraconazole against Candida tropicalis and for itraconazole against C. glabrata and Candida krusei. According to both methodologies, a great number of Candida spp. isolates showed an in vitro susceptibility to all evaluated antifungal agents. Overall, both procedures can be reliable techniques for susceptibility tests of yeasts, but the assessment of interlaboratory agreement and correlation of MICs by different methods with in vivo response are of great importance.
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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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".