Risk factors and algorithms for chlamydial and gonococcal cervical infections in women attending family planning clinics in Thailand

Sungwal Rugpao, Kittipong Rungruengthanakit, Yuthapong Werawatanakul, Wanida Sinchai, Tosaporn Ruengkris, Surachai Lamlertkittikul, Sutham Pinjareon, Sompong Koonlertkit, Aram Limtrakul, Somchai Sriplienchan, Antika Wongthanee, Bangorn Sirirojn, Charles S. Morrison, David D. Celentano

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)147-153
Number of pages7
JournalJournal of Obstetrics and Gynaecology Research
Volume36
Issue number1
DOIs
StatePublished - Feb 2010

Keywords

  • Algorithm
  • Cervical infection
  • Chlamydial infection
  • Gonococcal infection
  • Risk factor

ASJC Scopus subject areas

  • Obstetrics and Gynecology

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