Surveillance for Antimicrobial Resistance in Gonorrhea: The Alberta Model, 2012–2016
Bibliographic record
Abstract
Alberta established a surveillance system in 2001 to monitor resistance to antibiotics used for the treatment of gonorrhea. A retrospective review of gonorrhea cases during the last five years was conducted. All cases of gonorrhea were reportable to public health by testing laboratories and clinicians. Specimens were primarily submitted for nucleic acid amplification testing (NAAT); three sentinel sites obtained specimens for culture and NAAT. The Provincial Laboratory for Public Health conducted E-tests on isolates for multiple antibiotics. A proportion of isolates and NAAT specimens were submitted to the National Microbiology Laboratory for sequence typing (ST). Data were combined and analyzed using SAS version 9.4. Between 2012 and 2016, 13,132 gonorrhea cases were reported; 22.0% (n = 2891) had isolates available for susceptibility testing. All culture positive isolates were susceptible to ceftriaxone. Decreased susceptibility (0.5 ug/mL) to cefixime was reported in four cases in 2014. Resistance to azithromycin (≥2 ug/mL) ranged between 0.4% and 1.8%. Many (n = 509) unique STs were identified; the most prevalent sequence groups (SG) were SG-7638 (n = 367), SG-5985 (n = 145), and SG-11299 (n = 127). The Alberta model for maintaining surveillance for antimicrobial resistance in gonorrhea employs culture and NAAT specimens, providing information crucial to informing provincial treatment guidelines.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".