<i>In Vitro</i> Activity of Amikacin against Isolates of Mycobacterium avium Complex with Proposed MIC Breakpoints and Finding of a 16S rRNA Gene Mutation in Treated Isolates
Bibliographic record
Abstract
Amikacin is a major drug used for the treatment of Mycobacterium avium complex (MAC) disease, but standard laboratory guidelines for susceptibility testing are not available. This study presents in vitro amikacin MICs for 462 consecutive clinical isolates of the MAC using a broth microdilution assay. Approximately 50% of isolates had amikacin MICs of 8 μg/ml, and 86% had MICs of ≤16 μg/ml. Of the eight isolates (1.7%) with MICs of 64 μg/ml, five had an MIC of 32 μg/ml on repeat testing. Ten isolates (2.1%) had an initial amikacin MIC of >64 μg/ml, of which seven (1.5%) had MICs of >64 μg/ml on repeat testing. These seven isolates had a 16S rRNA gene A1408G mutation and included M. avium, Mycobacterium intracellulare, and Mycobacterium chimaera. Clinical data were available for five of these seven isolates, all of which had received prolonged (>6 months) prior therapy, with four that were known to be treated with amikacin. The 16S mutation was not detected in isolates with MICs of ≤64 μg/ml. We recommend primary testing of amikacin against isolates of the MAC and propose MIC guidelines for breakpoints that are identical to the CLSI guidelines for Mycobacterium abscessus: ≤16 μg/ml for susceptible, 32 μg/ml for intermediate, and ≥64 μg/ml for resistant. If considered and approved by the CLSI, this will be only the second drug recommended for primary susceptibility testing against the MAC and should facilitate its use for both intravenous and inhaled drug therapies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".