Contraceptives and sexual behaviours in predicting pregnancy rates in HIV prevention trials in South Africa: Past, present and future implications.
• Identifying the most influential factors associated with pregnancy incidence is crucial in HIV prevention trials. • We developed an algorithm to predict women at highest risk of pregnancy during the study follow-ups. • Four out of five risk factors in our pregnancy scoring algorithm, namely, young...
| Published in: | Sexual & Reproductive HealthCare Vol. 26 |
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| Main Authors: | , , , , , |
| Format: | research tables/charts Journal Article |
| Published: |
Elsevier B.V.
Dec2020
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=147227547&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 147227547 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 18775756 B70F jtl: Sexual & Reproductive HealthCare issn: 18775756 maglogo: N pubinfo: dt: Dec2020 vid: 26 pid: 467 pub: Elsevier B.V. place: New York, New York artinfo: ui: 147227547 147227547 147227547 10.1016/j.srhc.2020.100531 147227547 ppct: 1 formats: tig: atl: Contraceptives and sexual behaviours in predicting pregnancy rates in HIV prevention trials in South Africa: Past, present and future implications. aug: au: Wand, Handan Reddy, Tarylee Dassaye, Reshmi Moodley, Jothi Naidoo, Sarita Ramjee, Gita affil: Kirby Institute, University of New South Wales, Kensington 2052, New South Wales, Australia sug: subj: Contraceptive Agents HIV Infections Prevention and Control Sexual Behavior Algorithms Risk Assessment In Pregnancy South Africa Human Cox Proportional Hazards Model Regression Sensitivity and Specificity Age Factors Parity Sexual Partners Counseling Prospective Studies Pregnancy Female Female ab: • Identifying the most influential factors associated with pregnancy incidence is crucial in HIV prevention trials. • We developed an algorithm to predict women at highest risk of pregnancy during the study follow-ups. • Four out of five risk factors in our pregnancy scoring algorithm, namely, younger age, single/not cohabiting, low number of children and higher number of sexual partners, were also identified as significant predictors of HIV infections among women who enrolled in HIV prevention trials. • Collectively, these overlapping risk factors indicate the seriousness of the problem and the potential future burden in HIV prevention trials particularly for pregnant HIV infected women and their unborn babies. • This is the first and the largest study to report age-specific probabilities of becoming pregnant during a biomedical intervention trial among South African women. 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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