The In Vitro Activity of Rezafungin Against Uncommon Species of <i>Candida</i>
Bibliographic record
Abstract
BACKGROUND: Invasive candidiasis (IC) is increasing due to the rising numbers of immunocompromised patients. Increasing azole resistance rates and daily dosing required for most echinocandins have complicated its treatment. The approval of rezafungin has provided an option for weekly echinocandin treatment. The susceptibility of less common Candida spp. to rezafungin is unclear. We looked at the minimum inhibitory concentrations (MICs) of rezafungin and comparator agents against Candida spp. collected as part of a global surveillance program. METHOD: The CLSI reference broth microdilution method was performed to test 590 clinical isolates of 28 different Candida species, including Candida auris. Species-specific interpretative criteria by breakpoints or epidemiological cutoff values were applied where available. RESULTS: values were noted for C. guilliermondii (1/1 mg/L) and for isolates in the C. parapsilosis complex (C. orthopsilosis, 0.5/1 mg/L, C. metapsilosis, 0.12/0.5 mg/L). Rezafungin was active against 97.7% of C. dubliniensis and 95.4% of C. auris by CLSI breakpoints. For fluconazole, 69.7% of C. guilliermondii, 85.7% of C. orthopsilosis, and 100% of C. metapsilosis were wildtype by ECV, and 10.8% of C. auris were susceptible by CDC breakpoint. CONCLUSIONS: Rezafungin was highly active by in vitro testing against less common Candida spp. Rezafungin MICs were comparable to other echinocandins. Rezafungin is a desirable therapeutic alternative due to its reduced dosing frequency.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".