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- W3026833364 abstract "Despite all efforts, high pregnancy rates are often reported in HIV biomedical intervention trials conducted in African countries. We therefore aimed to develop a pregnancy risk scoring algorithm for targeted recruitment and screening strategies among a cohort of women in South Africa. The study population was ~ 10,000 women who enrolled in one of the six biomedical intervention trials conducted in KwaZulu Natal, South Africa. Cox regression models were used to create a pregnancy risk scoring algorithm which was internally validated using standard statistical measures. Five factors were identified as significant predictors of pregnancy incidence:<25 years old, not using injectable contraceptives, parity (<3), being single/not cohabiting and having ≥ 2 sexual partners in the past three months. Women with total scores of 21–24, 25–35 and 36+ were classified as being at “moderate”, “high”, “severe” risk of pregnancy. Sensitivity of the development and validation models were reasonably high (sensitivity 76% and 74% respectively). Our risk scoring algorithm can identify and alert researchers to women who need additional non-routine pregnancy assessment and counselling, with statistically acceptable accuracy and robustness." @default.
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- W3026833364 date "2020-12-01" @default.
- W3026833364 modified "2023-09-28" @default.
- W3026833364 title "Contraceptives and sexual behaviours in predicting pregnancy rates in HIV prevention trials in South Africa: Past, present and future implications" @default.
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- W3026833364 doi "https://doi.org/10.1016/j.srhc.2020.100531" @default.
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