Indexado em
- Genamics JournalSeek
- RefSeek
- Universidade de Hamdard
- EBSCO AZ
- OCLC- WorldCat
- publons
- Fundação de Genebra para Educação e Pesquisa Médica
- Euro Pub
- Google Scholar
Links Úteis
Compartilhe esta página
Folheto de jornal
Periódicos de Acesso Aberto
- Agro e Aquicultura
- Alimentos e Nutrição
- Bioinformática e Biologia de Sistemas
- Bioquímica
- Ciência de materiais
- Ciencias ambientais
- Ciências Clínicas
- Ciências Farmacêuticas
- Ciências gerais
- Ciências Médicas
- Cuidados de enfermagem e saúde
- Engenharia
- Genética e Biologia Molecular
- Gestão de negócios
- Imunologia e Microbiologia
- Neurociência e Psicologia
- Química
Abstrato
Multiple regression model to predict high cytomegalovirus immunoglobulin G avidity level in pregnant women with IgM positivity
Masatoki Kaneko
Aim: We established a model to predict highcytomegalovirus (CMV) immunoglobulin (Ig)G avidity index (AI) levels using clinical information to contribute to the mentalhealth of pregnant women with positive CMV IgM.
Method: This retrospective cohort study included 371 pregnantwomen with IgM positivity at <14 weeks of gestation.Information on women was obtained from medical charts.Congenital infection was confirmed by polymerase chainreaction using amniotic fluid or neonatal urine. The IgG AIcutoff value for diagnosing congenital infection was calculatedbased on receiver operating characteristic curve analysis.Between-group differences were assessed using Mann–WhitneyU-test or χ2analysis. Factors predicting high IgG AI weredetermined using multiple logistic regressions.