Prevalencia de Chlamydia trachomatis en Trabajadoras Sexuales: Revisión Sistemática
Bibliographic record
Abstract
Background: Chlamydia trachomatis is the second sexually Transmitted infection in the world, being sex workers a risk group for its dissemination \n\nObjective: To determine the prevalence of Chlamydia trachomatis in sex workers, based on studies published between 1980 and 2017.\n\nMethods: Systematic review with an exhaustive and reproducible search of the scientific \nliterature. The phases of the PRISMA guideline were applied and themethodological quality was evaluated with STROBE. The description of the studies was carried out with frequencies; the global prevalence of infection was estimated as well as specific prevalences by country, period, sample and ge group, in SPSS 24.0 and EPIDAT 3.1.\n\nResults: We included 57 studies with a population of 46,370 workers in whom a prevalence \nof 14.6% was found (95%CI=14.3-15.0). The countries with the highest prevalence were Iran with 94.2%, Canadá with 82.9%,Tunisia with 72.9%, Cambodia with 72.2% and Cameroon with 39.3%. In the specific prevalences, the one reported in 1980-1990 was higher (45.1%), by continent it was lower in Europe (6.9%). Statistically significant \ndifferences were found in the prevalence of adolescents 82.9%) and adults (94.2) compared to young people (13.4%). Based on the sample, it was higher in serum or blood (39.15%).\n\nConclusions: A high prevalence of C. trachomatis in sex workers was found, which shows the importance of focusing interventions in this group. There was a high heterogeneity in the specific prevalences, which strengthens the need for local studies for each population in which the implementation of sanitary actions is intended.
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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 | 0.040 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".