P3.279 From the Ground Up: Building National Surveillance of Antimicrobial Resistance in<i>Neisseria Gonorrhoeae</i>in Canada
Bibliographic record
Abstract
Background While there is evidence that gonococcal antimicrobial resistance (GC AMR) is increasing in parts of Canada, a national, standardised surveillance system does not currently exist to confirm these suspicions or identify the risks associated with acquiring a resistant GC infection. Methods Currently, laboratory-based surveillance of GC AMR is standard practise for all positive gonorrhoea isolates tested by culture in Canada. Nine out of 13 provinces/territories employ culture for a proportion of the total gonorrhoea tests done in their jurisdictions (typically conducted by local/regional laboratories). Variation in methods at the provincial/territorial (P/T) level and limited epidemiologic data on resistant GC isolates limits national level surveillance. To address gaps in current systems, a national protocol for GC AMR has been developed and approved by the Health Canada-Public Health Agency of Canada Research Ethics Board, and recruitment of P/T health authorities is in progress. Due to P/T variations in public health legislation and health care practises, recruitment has necessitated innovative solutions to address the individual needs of jurisdictions while ensuring the coherence and comparability of the resulting data. Results In 2011, the proportion of GC isolates resistant to azithromycin, penicillin, erythromycin, ciprofloxacin and tetracycline was 0.4%, 22.2%, 26.6%, 29.3%, and 29.4%, respectively. Enhanced surveillance in two jurisdictions is expected to commence in 2013. Although slightly different mechanisms are being used to address provincial needs, efforts are being made to ensure that resulting data are consistent and adhere to the national protocol. Conclusion In Canada, surveillance of GC AMR is challenged by variations in practise and legislation at the P/T level and competing priorities at all levels of government. Through collaboration with public health partners, progress is being made in obtaining data for analysis of national-level trends to assess risk factors associated with GC AMR and guide treatment recommendations.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".