Neisseria gonorrhoeae Multiantigen Sequence Typing Is Beneficial in Further Characterizing Gonococcal Populations in Alberta, Canada
Bibliographic record
Abstract
BACKGROUND: Antimicrobial resistance testing and behavioral data combined with Neisseria gonorrhoeae multiantigen sequence typing (NG-MAST) can help to define gonococcal populations and identify, characterize, and compare clusters of infection. METHODS: Antimicrobial resistance testing, using E test, was reviewed for gonococcal isolates in Alberta, Canada, from 2007 to 2011. Antimicrobial resistance testing was conducted on isolates demonstrating antimicrobial resistance and those with cefixime minimum inhibitory concentrations (MICs) of 0.06 μg/mL or greater. Demographic and behavioral information was obtained from provincial surveillance data. NG-MAST typing was conducted on a proportion of isolates. RESULTS: Gonococcal isolates were available for 2250 (26.4%) of 8535 cases of gonorrhea in Alberta from 2007 to 2011. The proportion of cases with decreased susceptibility to cefixime (≥0.06 μg/mL) increased from 0.7% to 2.4% between 2007 and 2009 to a high of 10.1% in 2010 and 8.9% in 2011. Six isolates with cefixime MIC of 0.25 μg/mL were noted: 5 were from men who have sex with men (MSM) and 1 was a pharyngeal isolate from a heterosexual female. Twenty-four (1.1%) isolates were azithromycin resistant (MIC ≥2.0 μg/mL); there were no significant differences between cases resistant or susceptible to azithromycin. NG-MAST of gonococcal isolates in Alberta suggests the entry of multiple strains into the province. Three clusters were identified: Cluster A predominantly in MSM, including sequence type 1407, a ST previously associated with decreased susceptibility to expanded spectrum cephalosporins; Cluster B, a predominantly heterosexual cluster with most cases in Edmonton; and Cluster C among MSM. CONCLUSIONS: Our data highlight the use of NG-MAST in further defining gonococcal populations.
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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 | 0.001 |
| 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) | 0.002 | 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".