Community-Based Prevalence Estimates of Chlamydia trachomatis and Neisseria gonorrhoeae Infections Among Gay, Bisexual, and Other Men Who Have Sex With Men in Montréal, Canada
Bibliographic record
Abstract
BACKGROUND: Reported cases of Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) infections are increasing among Canadian men. Estimates of community-based CT/NG prevalence are lacking among gay, bisexual, and other men who have sex with men (GBM). METHODS: Respondent driven sampling was used to recruit GBM in Montréal, Canada between February 2017 and June 2018. Specimens provided from urogenital, rectal, and pharyngeal sites were analyzed using nucleic acid amplification test to detect CT/NG. Prevalence estimates of CT/NG, overall and by anatomical site were calculated. All estimates are respondent-driven sampling-adjusted. RESULTS: Among 1177 GBM, the prevalence of rectal, urogenital, pharyngeal and overall were respectively 2.4%, 0.4%, 0.4%, and 2.8% for CT infections, and 3.1%, 0.4%, 3.5%, and 5.6% for NG infections. If testing had been limited to the urogenital site, 80% and 94% of CT and NG infections, respectively, would have been missed. CONCLUSIONS: This community-based study among GBM shows that the CT prevalence was about half of that observed for NG. A large part of CT/NG infections involves only the extragenital sites, highlighting the need for systematic multisite screening regardless of symptoms. In the mist of the COVID-19 pandemic and the limited CT/NG screening capacity due to test kits shortage, it might be considered to prioritize rectal and pharyngeal CT/NG testing over urogenital testing in asymptomatic GBM.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 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".