Molecular Surveillance and Prediction of Antimicrobial Resistance of Neisseria gonorrhoeae in Northern Alberta, Canada, 2015 to 2018
Bibliographic record
Abstract
BACKGROUND: The aims of this study was to describe molecular surveillance of Neisseria gonorrhoeae in the North Zone of Alberta (NZ) and to determine its value in predicting antimicrobial resistance. METHODS: Sequence types (STs) and single-nucleotide polymorphism (SNP) assays were performed on nucleic acid amplification testing (NAAT) samples. Sequence types of NAATs were matched to ST of cultures from across Alberta. Antimicrobial resistance prediction of NAATs for cephalosporins, azithromycin, and ciprofloxacin using SNP was compared with matching ST culture results using agar dilution and whole-genome sequencing. RESULTS: Of 2755 eligible specimens (2492 cases), 61.9% (1646 specimens) were sent for sequence typing, identifying 196 unique ST. Antimicrobial resistance data for 1307 additional cases were available using matching cultures. Decreased susceptibility (DS) to antimicrobials used for gonorrhea treatment was rare in the NZ; according to the SNP assay, none of the specimens had predicted DS to cephalosporins or azithromycin resistance. However, of the NZ NAAT samples tested in this study, 10.7% (131 of 1220) were predicted to have intermediate cephalosporin minimum inhibitory concentrations and 9.6% (115 of 1204) were resistant to ciprofloxacin. Based on cultures, the proportions of resistance in all of Alberta were as follows: DS to cephalosporins, 0.6% (20 of 3373); DS to intermediate cephalosporin, 16.9% (570 of 3373); azithromycin resistance, 1.2% (41 of 3373); and ciprofloxacin resistance, 32.2% (1087 of 3373). CONCLUSIONS: Our results highlight our ability to use culture-independent methods to predict antimicrobial resistance in N. gonorrhoeae.
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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 | 0.000 |
| 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 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".