Bibliographic citations
Durango, H., (2022). Desarrollo y validación de una regla de predicción clínica para diagnosticar la infección por el virus de Oropouche en pacientes con síndrome febril agudo [Tesis, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/659667
Durango, H., Desarrollo y validación de una regla de predicción clínica para diagnosticar la infección por el virus de Oropouche en pacientes con síndrome febril agudo [Tesis]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2022. http://hdl.handle.net/10757/659667
@misc{renati/399204,
title = "Desarrollo y validación de una regla de predicción clínica para diagnosticar la infección por el virus de Oropouche en pacientes con síndrome febril agudo",
author = "Durango Chavez, Hilda Victoria",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2022"
}
Background. Oropouche fever is an infectious disease caused by the Oropouche virus (OROV). The diagnosis and prediction of the clinical picture continue to be a great challenge for clinicians who manage patients with acute febrile syndrome. Several symptoms have been associated with OROV virus infection in patients with febrile syndrome; however, to date, there is no clinical prediction rule. Objective. To assess the performance of a prediction model based solely on signs and symptoms to diagnose Oropouche virus infection in patients with acute febrile syndrome. Materials and Methods. Validation study, which included 923 patients with acute febrile syndrome registered in the Epidemiological Surveillance database of three areas of Peru during the years 2015-2016. Results. A total of 97 patients (19%) were positive for OROV infection in the development group and 23.6% in the validation group. The area under the curve was 0.65 and the sensitivity, specificity, PPV, NPV, LR + and LR- were 78.2%, 35.1%, 27.6%, 83.6%, 1.20 and 0.62, respectively. Conclusions. The development of a clinical prediction model for the diagnosis of Oropouche based solely on signs and symptoms does not work well because the clinic is nonspecific and is related to other arbovirus infections, which makes it difficult to predict the diagnosis, especially in areas co-infection endemics of these diseases. Epidemiological surveillance of OROV using laboratory tests such as molecular PCR is recommended.
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