The journal of obstetrics and gynaecology research · 2010
Risk factors and algorithms for chlamydial and gonococcal cervical infections in women attending family planning clinics in Thailand.
СтатьяПоддержка NIH: внешняя программаНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Rugpao Sungwal, Rungruengthanakit Kittipong, Werawatanakul Yuthapong, Sinchai Wanida, Ruengkris Tosaporn, Lamlertkittikul Surachai, Pinjareon Sutham, Koonlertkit Sompong, Limtrakul Aram, Sriplienchan Somchai, Wongthanee Antika, Sirirojn Bangorn, Morrison Charles S, Celentano David D
Аннотация
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 <or=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.
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 <or=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.