Surveillance of Antimicrobial Resistance in Neisseria gonorrhoeae in Alberta from 2016–2022
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: can develop resistance to antimicrobial treatments, posing a challenge to effective management of patients. Alberta, Canada, monitors the antimicrobial susceptibility of gonorrhea isolates to track resistance trends. This study aims to retrospectively analyze susceptibility data and demographic trends from gonorrhea cases in the province over a seven-year period. METHODS: Antimicrobial susceptibility testing was performed using gradient strip methodology on gonorrhea isolates from Alberta, evaluating both historical and currently recommended antimicrobials for treatment of gonorrhea. Susceptibility testing results were interpreted using Clinical and Laboratory Standards Institute (CLSI) breakpoints. Provincial antimicrobial susceptibility testing data were analyzed using STATA v.17, incorporating antimicrobial resistance patterns and demographic information from provincial databases. RESULTS: isolates were cultured from 3617 individuals. All isolates tested were susceptible to ceftriaxone and cefixime, except for a single resistant isolate in 2018. Azithromycin susceptibility ranged from 99% to 88%, with the lowest susceptibility observed in 2018. Males exhibited higher rates of antimicrobial non-susceptibility than females across all drugs tested, except for tetracycline. CONCLUSIONS: Ongoing antimicrobial susceptibility surveillance in Alberta is crucial for identifying resistance trends and informing the development of effective treatment strategies for gonorrhea.
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| 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".