P251 Developing partner notification outcomes for bacterial STI by sex-partner type: international perspectives
Bibliographic record
Abstract
Background Sex-partner type influences sexually transmitted infection (STI) risk. Evaluating partner notification (PN) outcomes by sex-partner type could facilitate effective targeting of resources for PN for STIs. To inform development of PN outcomes for bacterial STIs, we reviewed PN guidelines and randomised control trials (RCTs) for sex-partner type characterisation and its impact on PN outcomes. Methods We searched online/via experts for PN guidelines worldwide and systematically reviewed RCTs of PN for bacterial STIs in PubMed to December 2018. We extracted data on PN recommendations and outcomes by sex-partner type. Results We found PN guidelines from United Kingdom (UK), United States of America (USA), Canada, Australasia, Australia, and New Zealand (NZ). They recommend collecting sex-partner data using terms such as: ‘regular’/‘main’/‘primary’/‘casual’/‘past’/‘anonymous’, without providing definitions. Australasian, NZ, Australian, and USA guidelines recommend prioritising PN based on factors that can enhance STI risk (e.g. having multiple partners), and emphasise PN of ‘regular’ partners to prevent index case re-infection. Only Australian guidelines outline auditable PN outcomes accounting for sex-partner type: index-reported number of treated ‘current regular partners’ or ‘all past partners (includes current casual partners)’. Ten of 28 RCTs reported study participants’ baseline data on sex-partner type (e.g. ‘steady’/‘regular’/‘main’/‘long-term’/‘casual’/‘one-time’), without defining them. Three RCTs reported PN outcomes by sex-partner type. Two RCTs reported higher chlamydia/gonorrhoea/trichomonas treatment rates for ‘main’ than ‘casual’ partners using expedited-partner-therapy (EPT) vs. patient-referral. Another RCT reported no difference in chlamydia re-infection rates in EPT vs. self-referral among women with a single ‘steady’ partner than women in overall trial. Conclusion Current PN guidelines do not define sex-partner type nor address public health benefits of notifying different sex-partners. Sex-partner type definitions should be developed and integrated in clinical practice. RCTs should examine the effect of sex-partner types on PN outcomes. PN guidelines should account for sex-partner type based on evidence from RCTs. Disclosure No significant relationships.
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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 | 0.134 | 0.451 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.032 | 0.004 |
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".