Cryptococcus neoformans-Cryptococcus gattii Species Complex: an International Study of Wild-Type Susceptibility Endpoint Distributions and Epidemiological Cutoff Values for Amphotericin B and Flucytosine
Bibliographic record
Abstract
Clinical breakpoints (CBPs) are not available for the Cryptococcus neoformans-Cryptococcus gattii species complex. MIC distributions were constructed for the wild type (WT) to establish epidemiologic cutoff values (ECVs) for C. neoformans and C. gattii versus amphotericin B and flucytosine. A total of 3,590 amphotericin B and 3,045 flucytosine CLSI MICs for C. neoformans (including 1,002 VNI isolates and 8 to 39 VNII, VNIII, and VNIV isolates) and 985 and 853 MICs for C. gattii, respectively (including 42 to 259 VGI, VGII, VGIII, and VGIV isolates), were gathered in 9 to 16 (amphotericin B) and 8 to 13 (flucytosine) laboratories (Europe, United States, Australia, Brazil, Canada, India, and South Africa) and aggregated for the analyses. Additionally, 442 amphotericin B and 313 flucytosine MICs measured by using CLSI-YNB medium instead of CLSI-RPMI medium and 237 Etest amphotericin B MICs for C. neoformans were evaluated. CLSI-RPMI ECVs for distributions originating in ≥3 laboratories (with the percentages of isolates for which MICs were less than or equal to ECVs given in parentheses) were as follows: for amphotericin B, 0.5 μg/ml for C. neoformans VNI (97.2%) and C. gattii VGI and VGIIa (99.2 and 97.5%, respectively) and 1 μg/ml for C. neoformans (98.5%) and C. gattii nontyped (100%) and VGII (99.2%) isolates; for flucytosine, 4 μg/ml for C. gattii nontyped (96.4%) and VGI (95.7%) isolates, 8 μg/ml for VNI (96.6%) isolates, and 16 μg/ml for C. neoformans nontyped (98.6%) and C. gattii VGII (97.1%) isolates. Other molecular types had apparent variations in MIC distributions, but the number of laboratories contributing data was too low to allow us to ascertain that the differences were due to factors other than assay variation. ECVs may aid in the detection of isolates with acquired resistance mechanisms.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".