Cryptococcus neoformans-Cryptococcus gattii Species Complex: an International Study of Wild-Type Susceptibility Endpoint Distributions and Epidemiological Cutoff Values for Amphotericin B and Flucytosine
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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 it