Using a field quantitative real-time PCR test to rapidly identify highly viremic rift valley fever cases.

Autor: Njenga MK; International Emerging Infections Program, US Centers for Disease Control and Prevention-Kenya, Nairobi, Kenya. Knjenga@ke.cdc.gov, Paweska J, Wanjala R, Rao CY, Weiner M, Omballa V, Luman ET, Mutonga D, Sharif S, Panning M, Drosten C, Feikin DR, Breiman RF
Jazyk: angličtina
Zdroj: Journal of clinical microbiology [J Clin Microbiol] 2009 Apr; Vol. 47 (4), pp. 1166-71. Date of Electronic Publication: 2009 Jan 26.
DOI: 10.1128/JCM.01905-08
Abstrakt: Approximately 8% of Rift Valley fever (RVF) cases develop severe disease, leading to hemorrhage, hepatitis, and/or encephalitis and resulting in up to 50% of deaths. A major obstacle in the management of RVF and other viral hemorrhagic fever cases in outbreaks that occur in rural settings is the inability to rapidly identify such cases, with poor prognosis early enough to allow for more-aggressive therapies. During an RVF outbreak in Kenya in 2006 to 2007, we evaluated whether quantitative real-time reverse transcription-PCR (qRT-PCR) could be used in the field to rapidly identify viremic RVF cases with risk of death. In 52 of 430 RVF cases analyzed by qRT-PCR and virus culture, 18 died (case fatality rate [CFR] = 34.6%). Levels of viremia in fatal cases were significantly higher than those in nonfatal cases (mean of 10(5.2) versus 10(2.9) per ml; P < 0.005). A negative correlation between the levels of infectious virus particles and the qRT-PCR crossover threshold (C(T)) values allowed the use of qRT-PCR to assess prognosis. The CFR was 50.0% among cases with C(T) values of <27.0 (corresponding to 2.1 x 10(4) viral RNA particles/ml of serum) and 4.5% among cases with C(T) values of >or=27.0. This cutoff yielded 93.8% sensitivity and a 95.5% negative predictive value; the specificity and positive predictive value were 58% and 50%, respectively. This study shows a correlation between high viremia and fatality and indicates that qRT-PCR testing can identify nearly all fatal RVF cases.
Databáze: MEDLINE