Identifying appropriate IUD candidates in areas with high prevalence of sexually transmitted infections

Background

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.

Methods

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.

Results

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.

Conclusion

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.