Developing and validating a risk algorithm to diagnose Neisseria gonorrhoeae and Chlamydia trachomatis in symptomatic Rwandan women.

ABSTRACT:

Background

Algorithms that bridge the gap between syndromic sexually transmitted infection (STI) management and treatment based in realistic diagnostic options and local epidemiology are urgently needed across Africa. Our objective was to develop and validate a risk algorithm for Neisseria gonorrhoeae (NG) and Chlamydia trachomatis (CT) diagnosis among symptomatic Rwandan women and to compare risk algorithm performance to the current Rwandan National Criteria for NG/CT diagnosis.

Methods

The risk algorithm was derived in a cohort (n = 468) comprised of symptomatic women in Kigali who sought free screening and treatment for sexually transmitted infections and vaginal dysbioses at our research site. We used logistic regression to derive a risk algorithm for prediction of NG/CT

SUBMITTER: Wall KM 

PROVIDER: S-EPMC8080377 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature