No Evidence for a Sustained Increase in Sexually Transmitted Diseases Among Heterosexuals in Amsterdam, The Netherlands A 12-Year Trend Analysis at the Sexually Transmitted Disease Outpatient Clinic Amsterdam
Bibliographic record
Abstract
In Brief Objectives: Sexually transmitted diseases (STDs) are on the rise, mainly among men having sex with men (MSM). Goal: The goal of this study was to evaluate whether STD increases as seen in MSM are also visible among heterosexuals. Study Design: Attendees of the STD clinic in Amsterdam, The Netherlands, are routinely tested for chlamydia, gonorrhea, and syphilis. Additionally, all women are tested for trichomoniasis. STD time trends of heterosexual attendees between 1994 and 2005 were analyzed by logistic regression and generalized linear models with a negative binomial distribution. Results: The number of consultations doubled since 1994. However, no long-term increase was seen in the number of syphilis and gonorrhea infections. Additionally, the trichomonas prevalence declined. However, the number of chlamydia infections increased over time. Conclusions: Although the number of attendees increased, no evidence for increasing STD incidence was found among heterosexuals. The increase in chlamydia infections can probably be explained by increased screening resulting from increased numbers of attendees. Although the number of heterosexuals attending the Amsterdam sexually transmitted disease clinic, The Netherlands, increased considerably, no sustained increase was found in the number of gonorrhea or syphilis infections.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".