TY - JOUR
T1 - Risk factors and algorithms for chlamydial and gonococcal cervical infections in women attending family planning clinics in Thailand
AU - Rugpao, Sungwal
AU - Rungruengthanakit, Kittipong
AU - Werawatanakul, Yuthapong
AU - Sinchai, Wanida
AU - Ruengkris, Tosaporn
AU - Lamlertkittikul, Surachai
AU - Pinjareon, Sutham
AU - Koonlertkit, Sompong
AU - Limtrakul, Aram
AU - Sriplienchan, Somchai
AU - Wongthanee, Antika
AU - Sirirojn, Bangorn
AU - Morrison, Charles S.
AU - Celentano, David D.
N1 - Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.
PY - 2010/2
Y1 - 2010/2
N2 - Aim: To identify risk factors associated with and evaluate algorithms for predicting Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) cervical infections in women attending family planning clinics in Thailand. Methods: Eligible women were recruited from family planning clinics from all regions in Thailand. The women were followed at 3-month intervals for 15-24 months. At each visit, the women were interviewed for interval sexually transmitted infection (STI) history in the past 3 months, recent sexual behavior, and contraceptive use. Pelvic examinations were performed and endocervical specimens were collected to test for CT and NG using polymerase chain reaction. Results: Factors associated with incident CT/NG cervical infections in multivariate analyses included region of country other than the north, age ≤25 years, polygamous marriage, acquiring a new sex partner in the last 3 months, abnormal vaginal discharge, mucopurulent cervical discharge, and easily induced bleeding of the endocervix. Three models were developed to predict cervical infection. A model incorporating demographic factors and sexual behaviors had a sensitivity of 61% and a specificity of 71%. Incorporating additional factors did not materially improve test performance. Positive predictive values for all models evaluated were low. Conclusion: In resource-limited settings, algorithmic approaches to identifying incident cervical infections among low-risk women may assist providers in the management of these infections.
AB - Aim: To identify risk factors associated with and evaluate algorithms for predicting Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) cervical infections in women attending family planning clinics in Thailand. Methods: Eligible women were recruited from family planning clinics from all regions in Thailand. The women were followed at 3-month intervals for 15-24 months. At each visit, the women were interviewed for interval sexually transmitted infection (STI) history in the past 3 months, recent sexual behavior, and contraceptive use. Pelvic examinations were performed and endocervical specimens were collected to test for CT and NG using polymerase chain reaction. Results: Factors associated with incident CT/NG cervical infections in multivariate analyses included region of country other than the north, age ≤25 years, polygamous marriage, acquiring a new sex partner in the last 3 months, abnormal vaginal discharge, mucopurulent cervical discharge, and easily induced bleeding of the endocervix. Three models were developed to predict cervical infection. A model incorporating demographic factors and sexual behaviors had a sensitivity of 61% and a specificity of 71%. Incorporating additional factors did not materially improve test performance. Positive predictive values for all models evaluated were low. Conclusion: In resource-limited settings, algorithmic approaches to identifying incident cervical infections among low-risk women may assist providers in the management of these infections.
KW - Algorithm
KW - Cervical infection
KW - Chlamydial infection
KW - Gonococcal infection
KW - Risk factor
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U2 - 10.1111/j.1447-0756.2009.01105.x
DO - 10.1111/j.1447-0756.2009.01105.x
M3 - Article
C2 - 20178541
AN - SCOPUS:76349099116
SN - 1341-8076
VL - 36
SP - 147
EP - 153
JO - Journal of Obstetrics and Gynaecology Research
JF - Journal of Obstetrics and Gynaecology Research
IS - 1
ER -