Are Ureaplasma spp. a Cause of Nongonococcal Urethritis? A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Nongonococcal urethritis (NGU) is the most common male reproductive tract syndrome. Ureaplasmas spp. including U. urealyticum and U. parvum, have been increasingly reported to be implicated in NGU. However, there are still many contradictions about their pathogenic role in NGU. AIMS: The goals of this study were to evaluate the association of Ureaplasmas spp. with NGU, and to compare the prevalence of Ureaplasmas spp. infection in China relative to the world average. METHODS: A systematic review and meta-analysis was conducted following standard guidelines for meta-analysis. The quality of included studies was assessed by Newcastle-Ottawa scale. RESULTS: A total of seven studies involving 1,507 NGU patients and 1,223 controls were eligible for meta-analysis. There was no significant difference in the Ureaplasma spp. positive rate between the NGU and control groups. However, the U. urealyticum positive rate was significantly higher in NGU patients compared to controls; the U. parvum positive rate was significantly higher in controls compared to NGU patients. Furthermore, within the NGU patient group, the positive rate of U. urealyticum was significantly higher than that of U. parvum, whereas within the control group, the opposite trend was observed. Compared to the world average, a significantly higher positive rate of Ureaplasma spp. was observed in both the NGU and control groups in China. CONCLUSIONS: Our analysis supports that U. urealyticum, but not U. parvum, is an etiological agent in NGU. More detailed studies of these two species in China and the world could contribute to a better understanding of the epidemiology and pathogenesis, and facilitate the development of better strategies for treatment and prevention of NGU.
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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 | 0.013 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.038 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".