Frequency and Correlates of Mycoplasma genitalium Antimicrobial Resistance Mutations and Their Association With Treatment Outcomes: Findings From a National Sentinel Surveillance Pilot in England
Bibliographic record
Abstract
Background Mycoplasma genitalium infection is a public health concern due to extensive antimicrobial resistance. Using data from a pilot of M. genitalium antimicrobial resistance surveillance, we determined the prevalence and risk factors for resistance among specimens from sexual health clinic attendees and assessed treatment outcomes. Methods Seventeen sexual health clinics in England sent consecutive M. genitalium–positive specimens to the national reference laboratory from January to March 2019. Regions of the 23S rRNA, parC, and gyrA genes associated with macrolide and fluoroquinolone resistance, respectively, were amplified and sequenced where appropriate. Fisher exact tests, and univariate and multivariable logistic regression models were used to determine associations between demographic, clinical, and behavioral factors and resistance-associated mutations. Results More than two-thirds (173 of 249 [69%]) of M. genitalium specimens had mutations associated with macrolide resistance, whereas predicted fluoroquinolone (21 of 251 [8%]) and dual-drug (12 of 237 [5%]) resistance were less prevalent. No specimens had both gyrA and parC resistance-associated mutations. Macrolide resistance was more common in specimens from men who have sex with men compared with heterosexual men (adjusted odds ratio, 2.64; 95% confidence interval, 1.09–6.38; P = 0.03). There was an association between both macrolide and fluoroquinolone resistance and having a previous sexually transmitted infection (P = 0.06). Only 19% of individuals returned for a test of cure. Of those infected with a macrolide-resistant genotype who were given azithromycin, 57 of 78 (73%) were known or assumed to be clinically cured; however, 43 of these 57 (75%) also received doxycycline. Of the 21 with a macrolide-resistant genotype who failed treatment, 18 of 21 (86%) also received doxycycline. Conclusions Although macrolide resistance was widespread, particularly among specimens from men who have sex with men and those with a previous sexually transmitted infection diagnosis in the past year, resistance-associated mutations in M. genitalium did not seem to be unequivocally predictive of treatment failure.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".