Agar Gradient Diffusion Susceptibility Testing for Neisseria gonorrhoeae: A Reliable Alternative to Agar Dilution?
Bibliographic record
Abstract
Abstract Background Antimicrobial susceptibility testing by agar dilution, the gold-standard for determination of minimal inhibitory concentration (MIC) for N. gonorrhoeae, is a labor intensive technique usually performed in reference laboratories. Agar gradient diffusion is a simpler alternative to obtain MICs. However, correlation of N. gonorrhoeae MIC values obtained by the two methods is not well established. The objective of this study is to evaluate performance of agar gradient diffusion compared with agar dilution for N. gonorrhoeae. Methods Fifty strains of N. gonorrhoeae (34 isolates from clinical specimens; 14 WHO reference and two ATCC strains), all confirmed to be genetically distinct using molecular typing (NG-MAST), were selected. Isolates with known high MICs were targeted. Agar gradient diffusion MIC testing was done in a clinical laboratory on all strains for ceftriaxone, cefixime, and azithromycin while comparing two different commercial antimicrobial strips (bioMérieux, Alere) on three different culture media (BD, Oxoid, CLSI’s recommended medium). Agar dilution MIC testing according to CLSI was done at the Québec provincial reference laboratory on all strains. Performance of agar gradient diffusion was assessed by accuracy, using essential and categorical agreements, and by precision (reproducibility). Results When comparing agar dilution and agar gradient diffusion using bioMérieux strips on CLSI testing medium, essential agreements (within 1-log2 dilution) were 94, 88, and 82% for ceftriaxone, cefixime, and azithromycin, respectively. Categorical agreements were 100, 94, and 94%. Agar gradient diffusion, compared with agar dilution, had a tendency to under-estimate MIC for third-generation cephalosporins, not classifying 86% of isolates with decreased susceptibility (MIC 0.12–0.25 mg/l for ceftriaxone, 0.25 mg/l for cefixime) as such. Overall precision of agar gradient diffusion was 96%. Conclusion Agar gradient diffusion using bioMérieux strips on CLSI testing medium shows satisfactory accuracy compared with agar dilution for N. gonorrhoeae MIC testing of third-generation cephalosporins and azithromycin even in a carefully selected panel of strains. Disclosures M. Desjardins, bioMerieux: Research Contractor, Research support. BD: Research Contractor, Research support. Alere: Research Contractor, Research support. Oxoid: Research Contractor, Research support. C. Fortin, Alere: Research Contractor, Research support. bioMerieux: Research Contractor, Research support. BD: Research Contractor, Research support Oxoid: Research Contractor, Research support
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How this classification was reachedexpand
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".