03 / MOLECULAR TYPING AND IDENTIFICATION OF ANTIMICROBIAL RESISTANCE MARKERS IN NEISSERIA GONORRHOEAE POSITIVE CLINICAL SPECIMENS COLLECTED IN A REMOTE NORTHERN REGION OF CANADA
Bibliographic record
Abstract
Background: Reported rates of gonorrhea have increased dramatically in Canada, with reports suggesting a high burden in remote northern regions; antimicrobial resistance (AMR) to currently recommended antimicrobials have been reported. AMR data are not available for infections diagnosed directly from specimens by nucleic acid amplification testing (NAAT). Molecular assays were used to provide enhanced molecular typing and predicted molecular AMR data on NAAT specimens from a remote northern region in Canada. Method: Between 2015 and 2017, we evaluated 1220 (2015,n=335; 2016,n=444; 2017,n=441) Neisseria gonorrhoeae positive NAATs (Aptima urine and urogenital swabs) for N. gonorrhoeae multi-antigen sequence typing (NG-MAST). Of these, 401 were further analyzed for resistance mutations to cephalosporins (penA, ponA, mtrR, porB mutations), ciprofloxacin (gyrA and parC mutations) and azithromycin (23SrRNA mutations) by real-time PCR assays. Results: Sequence types (ST) were obtained for over 90% (1127/1220) of the specimens tested. A total of 53 STs were identified from 2015-2017 with ST4637 (44.3%, 499/1127) and ST10451 (20.6%, 233/1127) the most common. Of the 401 specimens that were analyzed for mutations associated with resistance to cephalosporins, ciprofloxacin and azithromycin, 69.6% yielded results associated with potential susceptibility for all 3 antibiotics. No azithromycin-resistance associated mutations were identified. Seventy-one specimens were identified with both ciprofloxacin and cephalosporin-resistance mutations, the majority of these specimens were ST10451 (n=61). A further 12 specimens belonging to 5 different STs had only ciprofloxacin-resistance associated mutations. There were 173 specimens with no resistance mutations detected, the majority were ST4637 (n=38), ST13808 (n=16) and 20 other STs with 1 to 16 specimens in each.Conclusions: The enhanced molecular typing and predicted molecular antimicrobial resistance surveillance data will allow public health authorities to better understand the transmission of gonococcal infections and guide public health decision-making in the prevention, treatment and control of gonorrhea in remote regions where cultures are not available.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".