Gestational syphilis in a tertiary health service in Paraná, Brazil: A case-control study.
Fernando Braz PauliValdir Spada JúniorRenan William MesquitaGuilherme Welter WendtPaulo Cezar Nunes FortesHarapan HarapanLirane Elize Defante FerretoPublished in: PloS one (2024)
Approximately 10-12 million new syphilis infections occur annually worldwide, including in pregnant women. This study identified the factors associated with syphilis in pregnant women admitted to a tertiary maternity ward in the State of Paraná, Brazil. This is an ambispective, paired case-control study (1:2 ratio) conducted from September 2020 to October 2021. Pregnant patients (n = 93) admitted to the maternity ward, who were tested with the Venereal Disease Research Laboratory (VDRL) and rapid reagent test, were compared with 186 controls, matched by age and period of hospital admission. Sociodemographic, behavioral, prenatal, and maternity healthcare information was collected through interviews. The data were analyzed using binary logistic regression. Results showed that race/skin color other than white (OR: 2.12; 95%CI: 1.19-3.80; p < 0.001), having more than one sexual partner (OR: 3.69; 95%CI: 1.70-8.00; p = 0.001), being a former smoker (OR: 2.07; 95%CI: 1.07-4.01; p = 0.030) and a current smoker (OR: 4.31; 95%CI: 1.55-11.98; p = 0.005), as well as having a history of sexually transmitted infections (OR: 10.87; 95%CI: 4.04-29.27; p < 0.0.01) were risk factors for gestational syphilis. In summary, the study indicated that sociodemographic, behavioral, and healthcare-related variables were associated with gestational syphilis. Therefore, practitioners could benefit from incorporating these factors to deliver evidence-based treatment for gestational syphilis.
Keyphrases
- pregnant women
- men who have sex with men
- human immunodeficiency virus
- healthcare
- weight gain
- hiv testing
- pregnancy outcomes
- hepatitis c virus
- primary care
- emergency department
- newly diagnosed
- end stage renal disease
- mental health
- ejection fraction
- birth weight
- health information
- chronic kidney disease
- physical activity
- big data
- hiv infected
- antiretroviral therapy
- quantum dots
- machine learning