Morrison Charles S, Murphy Lisa, Kwok Cynthia, Weiner Debra H
Clinical Research and Biostatistics Divisions, Family Health International, P.O. Box 13950, Research Triangle Park, NC 27709, USA.
Contraception. 2007 Mar;75(3):185-92. doi: 10.1016/j.contraception.2006.10.004. Epub 2006 Dec 12.
The IUD is a highly effective, safe, inexpensive and long-lasting contraceptive. However, IUDs may increase PID risk during the early postinsertion period when inserted in women with cervical infections. We developed a simple algorithm to identify women at low risk of current sexually transmitted infection (STI) who are appropriate IUD candidates in regions with moderate or high STI prevalence.
We used data sets from family planning populations in Kenya, Zimbabwe, Jamaica and the United States to develop optimum algorithms. We then validated these algorithms using data sets from family planning populations in Thailand and Uganda.
A simple unweighted algorithm based on age, living with partner, education, bleeding between periods and a behavioral risk score (number of sex partners, condom use) was the most useful. Adding clinical signs did not improve algorithm performance. Women categorized at low risk by this algorithm were at substantially reduced risks of cervical infection. Women identified at high STI risk had at least twice the risk as the overall clinic populations. Women in the moderate-risk group had STI risks similar to the overall clinic populations.
Women categorized as low risk by the algorithm can be referred for IUD insertion while women categorized at high risk should not receive an IUD without further testing or treatment. Women in the moderate-risk group should be triaged based on the STI prevalence of the overall clinic population. A simple checklist has been developed to help providers estimate a client's risk of current STI and to guide appropriate triage.
宫内节育器(IUD)是一种高效、安全、廉价且长效的避孕方法。然而,在患有宫颈感染的女性中插入IUD时,在插入后的早期阶段可能会增加盆腔炎(PID)的风险。我们开发了一种简单的算法,以识别当前性传播感染(STI)低风险且在STI患病率中等或高的地区适合使用IUD的女性。
我们使用了来自肯尼亚、津巴布韦、牙买加和美国计划生育人群的数据集来开发最佳算法。然后,我们使用来自泰国和乌干达计划生育人群的数据集对这些算法进行了验证。
一种基于年龄、与伴侣同住、教育程度、经期出血情况和行为风险评分(性伴侣数量、避孕套使用情况)的简单非加权算法最为有用。添加临床体征并未改善算法性能。通过该算法分类为低风险的女性宫颈感染风险大幅降低。被确定为STI高风险的女性风险至少是整个诊所人群的两倍。中度风险组的女性STI风险与整个诊所人群相似。
通过该算法分类为低风险的女性可被转诊进行IUD插入,而高风险分类的女性在未经进一步检测或治疗的情况下不应接受IUD。中度风险组的女性应根据整个诊所人群的STI患病率进行分流。已制定了一份简单的清单,以帮助医疗服务提供者评估客户当前STI的风险并指导适当的分流。