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Sex Transm Infect ; 82(2): 175-81, 2006 Apr.
Article in English | MEDLINE | ID: mdl-16581750

ABSTRACT

OBJECTIVE: To develop a risk assessment algorithm that will increase the identification and treatment of women with cervical infection in rural Haiti. METHODS: Study participants were randomly selected from new patients who accessed services at a women's health clinic in rural Haiti between June 1999 and December 2002. This case-control study included women who tested positive for chlamydia and/or gonorrhoea based on the Gen-Probe PACE 2 laboratory test as cases. Controls were women who tested negative for both of these infections. RESULTS: Women from this area of rural Haiti had a limited level of education and lived in impoverished housing conditions. The sensitivity estimates of Haitian Ministry of Health and WHO algorithms for detecting chlamydia and/or gonorrhoea were generally low (ranging from 16.1% to 68.1%) in this population. Risk scores based on logistic regression models of local risk factors for chlamydia and gonorrhoea were developed and sensitivity estimates were higher for algorithms based on these risk scores (up to 98.8%); however, specificity was compromised. CONCLUSIONS: A risk assessment algorithm to identify women with chlamydia and/or gonorrhoea is more sensitive and less specific than the syndromic management approach advocated by WHO and adapted by the Haitian Ministry of Health. Using a risk assessment tool with high sensitivity based on local risk factors of cervical infection will maximise access to care, improve outcomes, and decrease morbidity in women who have cervical infection in rural Haiti.


Subject(s)
Algorithms , Chlamydia Infections/diagnosis , Gonorrhea/diagnosis , Rural Health , Adult , Case-Control Studies , Chlamydia Infections/epidemiology , Chlamydia Infections/therapy , Female , Gonorrhea/epidemiology , Gonorrhea/therapy , Haiti/epidemiology , Health Services Accessibility/organization & administration , Humans , Poverty , Regression Analysis , Risk Assessment , Sensitivity and Specificity , Treatment Outcome
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