Prevalence and Associated Factors of Cryptococcal Antigenemia in HIV-Infected Patients with CD4 < 200 Cells/µL in São Paulo, Brazil: A Bayesian Analysis.
Evanthia Vetos MimicosVictor FossaluzaCamila de Melo PiconeCamila Caroline de SenaHélio Rodrigues GomesCarolina Dos Santos LázariFernanda Ferreira da SilvaErika Shimoda NakanishiIsabelle Vichr NisidaAngela Carvalho FreitasRonaldo Borges GryschekEduardo Ronner LagonegroMárcia LazéraMaria Aparecida Shikanai YasudaPublished in: Journal of fungi (Basel, Switzerland) (2022)
Cryptococcosis is a severe life-threatening disease and a major cause of mortality in people with advanced AIDS and CD4 ≤ 100 cells/µL. Considering the knowledge gap regarding the benefits of routine application of antigenemia tests in HIV-infected patients with 100-200 CD4 cells/µL for the prevention of cryptococcal meningitis (CM), we aimed to evaluate the prevalence of positive antigenemia through lateral flow assay (LFA) and associated factors in HIV-infected patients with CD4 < 200 cells/µL. Our findings of 3.49% of positive LFA (LFA+) patients with CD4 < 100 cells/µL and 2.24% with CD4 between 100-200 cells/µL have been included in a Bayesian analysis with 12 other studies containing similar samples worldwide. This analysis showed a proportion of 3.6% LFA+ patients (95% credible interval-Ci [2.5-5.7%]) with CD4 < 100 cells/µL and 1.1% (95%Ci [0.5-4.3%]) with CD4 between 100-200 cells/µL, without statistical difference between these groups. The difference between mortality rates in LFA+ and negative LFA groups was e = 0.05013. Cryptococcoma and CM were observed in the LFA+ group with 100-200 and <100 CD4 cells/µL, respectively. Considering the benefits of antifungal therapy for LFA+ patients, our data reinforced the recommendation to apply LFA as a routine test in patients with 100-200 CD4 cells/µL aiming to expand cost-effectiveness studies in this group.
Keyphrases
- induced apoptosis
- cell cycle arrest
- hiv infected
- healthcare
- signaling pathway
- risk factors
- type diabetes
- machine learning
- end stage renal disease
- chronic kidney disease
- cardiovascular disease
- ejection fraction
- cardiovascular events
- prognostic factors
- pi k akt
- cell proliferation
- clinical practice
- nk cells
- hepatitis c virus
- deep learning