Predicting Neisseria gonorrhoeae and Chlamydia trachomatis Infection Using Risk Scores, Physical Examination, Microscopy, and Leukocyte Esterase Urine Dipsticks Among Asymptomatic Women Attending a Family Planning Clinic in Kenya

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Abstract
Sexually transmitted infections (STIs) continue to exert a tremendous health burden on women in developing countries. Poor socioeconomic status, inadequate knowledge, lack of diagnostic facilities, and shortages of effective treatment all contribute to the high incidence of STIs. The use of clinical algorithms for the detection and management of STIs has gained widespread acceptance in settings where there are limited resources. Evaluation of these algorithms have been few, especially in women who are not recognized as members of high-risk groups. To develop a simple scoring system based on historical and demographic data, physical findings, microscopy, and leukocyte esterase (LE) urine dipsticks to predict cervical gonococcal and chlamydial infection among asymptomatic women. One thousand and forty-eight women attending an urban family planning clinic in Nairobi were randomly selected to participate. After the identification of factors that were associated with infection, we assigned one point each for: age 25 or younger, single status, two or more sex partners in the past year, cervical discharge, cervical swab leukocytes, and a positive LE urine dipstick. Identification of any one of these six factors gave a sensitivity of 85% and a specificity of 30% for the detection of cervical infections. A positive LE urine dipstick had a sensitivity of 63% and a specificity of 47% when used alone and did not contribute to the identification of infection if a physical examination was performed. The application of existing clinical algorithms to this population performed poorly. The use of risk scores, physical examination, microscopy, and the urine LE dipstick, used alone or in combination, as predictors of gonococcal or chlamydial cervical infection was of limited utility in low-risk, asymptomatic women. Accurate diagnostic testing is necessary to optimize treatment.