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Diagnosis and treatment of infectious vaginitis: Proposal for a new algorithm.
Eleutério, José; Campaner, Adriana Bittencourt; de Carvalho, Newton Sergio.
Afiliación
  • Eleutério J; Department of Health for Women, Children, and Adolescents, Faculty of Medicine, Federal University of Ceará, Fortaleza, Brazil.
  • Campaner AB; Department of Gynecology and Obstetrics, Faculty of Medical Sciences of Santa Casa de São Paulo, São Paulo, Brazil.
  • de Carvalho NS; Department of Gynecology and Obstetrics, Infectious Diseases in Gynecology and Obstetrics Sector, Federal University of Paraná, Curitiba, Paraná, Brazil.
Front Med (Lausanne) ; 10: 1040072, 2023.
Article en En | MEDLINE | ID: mdl-36844222
ABSTRACT

Background:

Vaginitis is the most common gynecologic diagnosis in primary care, and most women have at least one episode during their lives. The need for standardized strategies to diagnose and treat vaginitis, both in primary care and among gynecologists, is emphasized. The Brazilian Group for Vaginal Infections (GBIV, acronym in Portuguese) aimed to update the practical approach to affected women by reviewing and discussing recent literature, and developing algorithms for diagnosis and treatment of vaginitis.

Methods:

A literature search within biomedical databases PubMed and SCieLo was conducted in January 2022. The available literature was evaluated by three experienced researchers, members of the GBIV, to summarize the main data and develop practical algorithms. Results and

conclusion:

Detailed algorithms were developed with the main goal to improve gynecological practice considering different scenarios and access to diagnostic tools, from the simplest to the most complex tests. Different age groups and specific contexts were also considered. The combination of anamnesis, gynecological examination, and complementary tests remains the basis of a proper diagnostic and therapeutic approach. Periodic updates of these algorithms are warranted as new evidence becomes available.
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Front Med (Lausanne) Año: 2023 Tipo del documento: Article País de afiliación: Brasil

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Front Med (Lausanne) Año: 2023 Tipo del documento: Article País de afiliación: Brasil