Minimum inhibitory concentrations of<i>Neisseria gonorrhoeae</i>strains in clients of the Amsterdam sexual health clinic with a Dutch versus an international sexual network
Bibliographic record
Abstract
OBJECTIVES: (Ng). To assess the role of travel in Ng strain susceptibility, we compared minimum inhibitory concentrations (MICs) for five antibiotics (ie, azithromycin, ceftriaxone, cefotaxime, cefixime and ciprofloxacin) in strains from clients with an exclusively Dutch sexual network and clients with an additional international sexual network. METHODS: From 2013 to 2019, we recorded recent residence of sexual partners of clients (and of their partners) with Ng at the Center for Sexual Health of Amsterdam. We categorised clients as having: (1) exclusively sexual partners residing in the Netherlands ('Dutch only') or (2) at least one partner residing outside the Netherlands. We categorised the country of residence of sexual partners by World Bank/EuroVoc regions. We analysed the difference of log-transformed MIC of Ng strains between categories using linear or hurdle regression for each antibiotic. RESULTS: We included 3367 gay and bisexual men who had sex with men (GBMSM), 516 women and 525 men who exclusively had sex with women (MSW) with Ng. Compared with GBMSM with a 'Dutch only' network, GBMSM with: (1) a Western European network had higher MICs for ceftriaxone (β=0.19, 95% CI=0.08 to 0.29), cefotaxime (β=0.19, 95% CI=0.08 to 0.31) and cefixime (β=0.06, 95% CI=0.001 to 0.11); (2) a Southern European network had a higher MIC for cefixime (β=0.10, 95% CI=0.02 to 0.17); and (3) a sub-Saharan African network had a lower MIC for ciprofloxacin (β=-1.79, 95% CI=-2.84 to -0.74). In women and MSW, higher MICs were found for ceftriaxone in clients with a Latin American and Caribbean network (β=0.26, 95% CI=0.02 to 0.51). CONCLUSIONS: For three cephalosporin antibiotics, we found Ng strains with slightly higher MICs in clients with partner(s) from Europe or Latin America and the Caribbean. International travel might contribute to the spread of Ng with lower susceptibility. More understanding of the emergence of AMR Ng is needed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".