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  • Title: Predictors of male partner treatment for sexually transmitted infection.
    Author: Secura GM, Desir FA, Mullersman JL, Madden T, Allsworth JE, Peipert JF.
    Journal: Sex Transm Dis; 2012 Oct; 39(10):769-75. PubMed ID: 23001263.
    Abstract:
    BACKGROUND: Patient-initiated notification is a commonly used practice for notifying sex partners of possible exposure to a sexually transmitted infection (STI); however, 46% to 75% of partners are never treated. The Contraceptive CHOICE Project (CHOICE) is a longitudinal cohort study of women that provides no-cost contraception, STI testing, treatment to participants, and free partner treatment. Our objective was to evaluate characteristics of women who tested positive for chlamydia, gonorrhea, or trichomoniasis, and their association with successful partner treatment. METHODS: We analyzed baseline survey and STI testing, notification, and treatment data from the first 5087 participants enrolled in CHOICE. We considered "treated partners" to be men who received antibiotic treatment at the study clinic or by a prescription through the study. Independent predictors of successful partner treatment were identified using univariate analysis and multivariable analysis using Poisson regression with robust error variance. RESULTS: Forty-four percent of male partners were successfully treated. Women whose partners were less likely to obtain treatment were black (adjusted Relative Risk (RR adj) RR adj = 0.6; 95% confidence interval [CI]: 0.5-0.8) or reported some concern about future STI with the partner (RR adj = 0.6; 95% CI: 0.4, 0.8). Women whose partners were more likely to receive treatment were living with their partner (RR adj = 1.4; 95% CI: 1.1-1.8) or reported recent inconsistent condom use (RR adj = 1.5; 95% CI: 1.1-2.1). CONCLUSIONS: The male partner treatment rate resulting from female patient-initiated partner notification in our study was low. Our findings highlight the need to develop novel notification interventions that yield higher partner treatment rates and consider patient-specific factors, such as race and relationship status.
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