Macrolide-Resistant Mycoplasma genitalium Impairs Clinical Improvement of Male Urethritis After Empirical Treatment
Bibliographic record
Abstract
BACKGROUND: Mycoplasma genitalium (MG) is associated with urethritis in men and could play a role in clinical outcome. We examined clinical improvement of symptoms in men receiving empirical treatment for urethritis and correlated the outcome with Neisseria gonorrhoeae (NG), Chlamydia trachomatis (CT), MG, and MG macrolide resistance-associated mutations (MRAM) status. METHODS: At the sexually transmitted infection clinic in Amsterdam, the Netherlands, empirical treatment for gonococcal urethritis is 1 g ceftriaxone and for nongonococcal urethritis 1 g azithromycin. In 2018 to 2019, we tested urine samples of men with urethritis for CT, NG, and MG using transcription-mediated amplification assays. Mycoplasma genitalium-positive samples were tested for MRAM using quantitative polymerase chain reaction. Two weeks after receiving therapy, men were sent a text message inquiring after clinical improvement. RESULTS: We evaluated 2505 cases of urethritis. The positivity rates of NG, CT, and MG were 26% (648 of 2489), 29% (726 of 2489), and 23% (522 of 2288), respectively. In 768 of 2288 of the cases (34%), no causative agent was detected. Most cases were infected with a single pathogen: NG, 417 of 2288 (18%); CT, 486 of 2288 (21%); and MG, 320 of 2288 (14%). The prevalence of MRAM among MG-positives was 74% (327 of 439). For 642 (25.6%) cases, we could evaluate clinical improvement after treatment of whom 127 (20%) indicated no improvement; 9% (15 of 174) in NG cases, 18% (35 of 195) in CT cases, 14% (4 of 28) in MG wild-type cases, and 40% (38 of 94) in MG-MRAM cases. Clinical improvement in MG-MRAM cases was significantly lower compared with all other groups (P < 0.001). CONCLUSIONS: Presence of MG-MRAM is associated with lack of clinical improvement in azithromycin-treated nongonococcal urethritis.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".