Condom Effectiveness for Reducing Transmission of Gonorrhea and Chlamydia: The Importance of Assessing Partner Infection Status
Bibliographic record
Abstract
This analysis examined the importance of differential exposure to infected partners in epidemiologic studies of latex condom effectiveness for prevention of sexually transmitted infections. Cross-sectional, enrollment visit data were analyzed from Project RESPECT, a trial of counseling interventions conducted at five publicly funded US sexually transmitted disease clinics between 1993 and 1997. The association between consistent condom use in the previous 3 months and prevalent gonorrhea and chlamydia (Gc/Ct) was compared between participants known to have infected partners and participants whose partner infection status was unknown. Among 429 participants with known Gc/Ct exposure, consistent condom use was associated with a significant reduction in prevalent gonorrhea and chlamydia (30% vs. 43%; adjusted prevalence odds ratio = 0.42, 95% confidence interval: 0.18, 0.99). Among 4,314 participants with unknown Gc/Ct exposure, consistent condom use was associated with a lower reduction in prevalent gonorrhea and chlamydia (24% vs. 25%; adjusted prevalence odds ratio = 0.82, 95% confidence interval: 0.66, 1.01). The number of unprotected sex acts was significantly associated with infection when exposure was known (p for trend < 0.01) but not when exposure was unknown (p for trend = 0.73). Restricting analyses to participants with known exposure to infected partners provides a feasible and efficient mechanism for reducing confounding from differential exposure to infected partners in condom effectiveness studies.
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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 | 0.026 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".