The Effect of Medical Male Circumcision on Urogenital Mycoplasma genitalium Among Men in Kisumu, Kenya
Bibliographic record
Abstract
BACKGROUND: We determined the prevalence of urethral Mycoplasma genitalium (MG) infection and whether infection was associated with circumcision status among men enrolled in the randomized trial of medical male circumcision to prevent HIV acquisition in Kisumu, Kenya. METHODS: MG and Trichomonas vaginalis were detected in first void urine by APTIMA transcription-mediated amplification assay. first void urine and urethral swabs were assessed for Neisseria gonorrhoeae (NG) and Chlamydia trachomatis (CT) by polymerase chain reaction assay. Herpes simplex virus type 2 antibodies were detected by IgG ELISA. Multivariable logistic regression identified factors associated with MG infection. RESULTS: Specimens were collected between July and September 2010, and 52 (9.9%; 95% confidence interval [CI]: 7.3%-12.4%) MG infections were detected among 526 men. N. gonorrhoeae and T. vaginalis were not associated with MG. CT coinfection was 5.8% in MG-infected men, and 0.8% among MG-uninfected men (P = 0.02). MG infection was predominantly asymptomatic (98%). The prevalence of MG was 13.4% in uncircumcised men versus 8.2% in circumcised men (P = 0.06). Being circumcised nearly halved the odds of MG (adjusted odds ratio [aQR] = 0.54; 95% CI: 0.29-0.99), adjusted for other variables significant at the P < 0.05 level: herpes simplex virus type 2 infection (aOR = 2.05; 95% CI: 1.05-4.00), CT infection (aOR = 2.69; 95% CI: 1.44-5.02), and washing the penis ≤1 hour after sex (aOR = 0.47; 95% CI: 0.24-0.95). CONCLUSIONS: MG infection was reduced among men who were circumcised, adding to the benefits of male circumcision in preventing several sexually transmitted infections.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".