Antimicrobial susceptibilities and distribution of sequence types of <i>Neisseria gonorrhoeae</i> isolates in Canada: 2010
Bibliographic record
Abstract
The monitoring of antimicrobial susceptibilities in Neisseria gonorrhoeae isolates and characterization of N. gonorrhoeae multiantigen sequence types (NG-MAST, ST) provide important surveillance data as resistance rates continue to rise. A total of 2970 N. gonorrhoeae isolates were collected by Canadian provincial public health laboratories in 2010, and 1233 were submitted to the National Microbiology Laboratory for testing. The NG-MAST and minimum inhibitory concentration (MIC) by agar dilution were determined for each isolate. Of the 2970 isolates, 25.1% were resistant to penicillin, 34.6% resistant to tetracycline, 31.5% resistant to erythromycin, 35.9% resistant to ciprofloxacin, and 1.2% resistant to azithromycin. Decreased susceptibility to cefixime (MIC ≥ 0.25 mg/L) and ceftriaxone (MIC ≥ 0.125 mg/L) was identified in 3.2% and 7.3% of the isolates, respectively. The most common STs found in Canada were ST1407 (13.3%), ST3150 (11.3%), and ST3158 (9.0%), with 249 different STs identified among the isolates. Within the ST1407 group, 19.5% and 43.3% isolates have decreased susceptibility to cefixime and ceftriaxone, respectively. ST1407, the most prevalent NG-MAST in Canada in 2010, has been associated with high-level ceftriaxone MICs and with cefixime treatment failure cases worldwide. Identification and monitoring of STs and corresponding antimicrobial resistance profiles may be useful in surveillance programs and be used to inform public health actions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".