Publications by authors named "Marie Aimee Unyuzimana"
Article Synopsis
- There is a pressing need for algorithms in Africa that integrate STI management with local health data to improve diagnosis and treatment options for conditions like gonorrhea and chlamydia.
- A new risk algorithm was developed for diagnosing these infections in symptomatic Rwandan women, utilizing a study sample of 468 participants and then validated with another group of 305 women.
- The algorithm demonstrated a strong predictive ability, with an 81% sensitivity and 85% NPV, significantly outperforming the current national criteria for STI diagnosis in Rwanda.
Introduction: The longstanding inadequacies of syndromic management for genital ulceration and inflammation are well-described. The Rwanda National Guidelines for sexually transmitted infection (STI) syndromic management are not yet informed by the local prevalence and correlates of STI etiologies, a component World Health Organization guidelines stress as critical to optimize locally relevant algorithms.
Methods: Radio announcements and pharmacists recruited symptomatic patients to seek free STI services in Kigali.