A simple algorithm for selecting cases to investigate acute and early HIV infections in low- and middle-income countries.
Elaine Monteiro MatsudaCintia Mayumi AhagonLuana Portes Ozório CoelhoIvana Barros de CamposDaniela Rodrigues ColpasNorberto Camilo CamposGiselle Ibete Silva López-LopesValéria Oliveira SilvaIsabela Penteriche de OliveiraLuís Fernando de Macedo BrígidoPublished in: Journal of medical virology (2021)
We documented the outcome of an over 10-year (2011-2021) effort to diagnose acute and early HIV infections (AEHI) in an Infectious Diseases Outpatient Clinic with limited resources. Of a total of 132, 119 HIV-RNA tests were performed from 2017 to 2020, 12 cases were identified, using a simple algorithm: risk exposure of 6 weeks or less before the visit and/or symptoms compatible with acute retroviral syndrome 7-30 days after exposure and/or undetermined 3rd generation rapid diagnostic test or serology. AEHI diagnoses varied from 2.4% among asymptomatic to 25% for undetermined serology cases using this simple screening applicable to different settings.
Keyphrases
- antiretroviral therapy
- liver failure
- hiv positive
- hiv infected
- hiv testing
- human immunodeficiency virus
- respiratory failure
- hepatitis c virus
- hiv aids
- men who have sex with men
- infectious diseases
- machine learning
- drug induced
- aortic dissection
- hepatitis b virus
- south africa
- primary care
- neural network
- gestational age
- sleep quality
- nucleic acid
- acute respiratory distress syndrome
- mechanical ventilation
- loop mediated isothermal amplification