Etiology of urethral discharge in West Africa: the role of Mycoplasma genitalium and Trichomonas vaginalis.
Bibliographic record
Abstract
OBJECTIVE: To determine the etiological role of pathogens other than Neisseria gonorrhoeae and Chlamydia trachomatis in urethral discharge in West African men. METHODS: Urethral swabs were obtained from 659 male patients presenting with urethral discharge in 72 primary health care facilities in seven West African countries, and in 339 controls presenting for complaints unrelated to the genitourinary tract. Polymerase chain reaction analysis was used to detect the presence of N. gonorrhoeae, C. trachomatis, Trichomonas vaginalis, Mycoplasma genitalium, and Ureaplasma urealyticum. FINDINGS: N. gonorrhoeae, T. vaginalis, C. trachomatis, and M. genitalium--but not U. urealyticum--were found more frequently in men with urethral discharge than in asymptomatic controls, being present in 61.9%, 13.8%, 13.4% and 10.0%, respectively, of cases of urethral discharge. Multiple infections were common. Among patients with gonococcal infection, T. vaginalis was as frequent a coinfection as C. trachomatis. M. genitalium, T. vaginalis, and C. trachomatis caused a similar clinical syndrome to that associated with gonococcal infection, but with a less severe urethral discharge. CONCLUSIONS: M. genitalium and T. vaginalis are important etiological agents of urethral discharge in West Africa. The frequent occurrence of multiple infections with any combination of four pathogens strongly supports the syndromic approach. The optimal use of metronidazole in flowcharts for the syndromic management of urethral discharge needs to be explored in therapeutic trials.
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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 | 0.001 | 0.001 |
| 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".