P382 High prevalence of macrolide and quinolone-resistance mediating mutations in mycoplasma genitalium among gay and bisexual men (GBM) in Montréal, Canada
Bibliographic record
Abstract
Background Mycoplasma genitalium (MG) easily develops resistance to azithromycin and moxifloxacin, currently recommended first- and second-line treatments, respectively. Population-based data on prevalence of MG resistance mutations (macrolide and fluoroquinolone) are lacking. We estimated this prevalence among GBM. Methods The Engage study used respondent-driven sampling (RDS), to recruit sexually active cisgender and transgender men, ≥16 years. Participants completed a computer-assisted self-interview. Pharyngeal, urine and rectal specimens collected at cohort study visits between 11/2018–11/2019 were analyzed using Seegene Allplex™ CT/NG/MG/TV assay. MG positive samples were further analyzed using Seegene Allplex™ MG & AziR and Allplex™ MG & MoxiR assays. Results MG infection was detected in 44/717 participants. Resistance assays were performed on samples from 41 participants; median age=31yrs, 78% identified as gay, 17% were HIV-positive, and 20% reported C. trachomatis or N. gonorrhea infection over the past 6 months. Information on symptoms at study visit was available for 33 participants; all were asymptomatic. Sites of infection were rectum (n=23), urethra (n=16) or pharynx (n=2). Macrolide-resistance mediating mutations (MRMM) in 23S rRNA gene were found in 31 samples (A2058G, n=4; A2059G, n=27); 6 were wild-type and 4 failed to amplify MG. Prevalence of MRMM was 31/37 (84%). Quinolone-resistance mediating mutations (QRMM) in parC gene were found in (G248T, n=10; G248A, n=1; A247C, n=1); 25 were wild-type and 4 failed to amplify MG. No QRMM in gyrA gene was found. Prevalence of QRMM was 12/37 (32%). Combined mutations in 23S rRNA and parC genes was found in 11/35 MG-positive samples (31%). Conclusions Among asymptomatic MG-infected GBM in Montreal, almost one-third were infected by MG strains harboring resistance mutations to both antibiotics currently used to treat symptomatic infections. It is important that clinicians be aware of this high level of circulating resistance, have increased access to MG testing, and adjust their treatment strategies accordingly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".