The Resurgence of Lymphogranuloma Venereum: Changing Presentation of Lymphogranuloma Venereum in the Era of HIV Preexposure Prophylaxis, 2004 to 2022
Bibliographic record
Abstract
BACKGROUND: Before the early 2000s, the sexually transmitted infection lymphogranuloma venereum (LGV) was rare in high-income countries. Initially, most cases in these countries were among symptomatic men who have sex with men (MSM) living with HIV. In the context of widespread HIV preexposure prophylaxis (PrEP), LGV's epidemiology may be changing. We aimed to characterize the epidemiology and clinical presentation of LGV in the PrEP era. METHODS: A retrospective chart review was performed on all LGV cases occurring between November 2004 to October 2022 in British Columbia (BC), Canada. Cases were stratified by having occurred before (2004-2017) or after widespread PrEP availability in BC (2018-2022). Annual rates and test positivity percentages were calculated. Bivariate logistic regression was performed to identify drivers of asymptomatic infection in the PrEP era. RESULTS: Among 545 cases identified, 205 (37.6%) occurred pre-PrEP and 340 (62.4%) occurred during the PrEP era. Most cases were among MSM (97.2%). The estimated rate of LGV has doubled from 2018 to 2022, reaching 1535.2 cases per 100,000 PrEP users. Most PrEP-era cases were among HIV-negative individuals (65.3%), particularly those on PrEP (72.6%). Cases in the PrEP era were often asymptomatic compared with pre-PrEP (38.6% vs. 19.3%; P < 0.001). Users of PrEP were more likely to experience asymptomatic infection compared with HIV-negative PrEP nonusers (odds ratio, 2.07; 95% confidence interval, 1.07-3.99). CONCLUSIONS: In the context of increased asymptomatic testing, LGV may be increasing in BC. Most infections now occur among HIV-negative MSM. A high proportion of infections are asymptomatic.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".