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J Clin Lipidol ; 10(5): 1223-9, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-27678440

RESUMO

BACKGROUND: In the US familial hypercholesterolemia (FH), patients are underidentified, despite an estimated prevalence of 1:200 to 1:500. Criteria to identify FH patients include Simon Broome, Dutch Lipid Clinic Network (DLCN), or Make Early Diagnosis to Prevent Early Deaths (MEDPED). The use of these criteria in US clinical practices remains unclear. OBJECTIVE: To characterize the FH diagnostic criteria applied by US lipid specialists participating in the FH Foundation's CASCADE FH (CAscade SCreening for Awareness and DEtection of Familial Hypercholesterolemia) patient registry. METHODS: We performed an observational, cross-sectional analysis of diagnostic criteria chosen for each adult patient, both overall and by baseline patient characteristics, at 15 clinical sites that had contributed data to the registry as of September 8, 2015. A sample of 1867 FH adults was analyzed. The median age at FH diagnosis was 50 years, and the median pretreatment low-density lipoprotein cholesterol (LDL-C) value was 238 mg/dL. The main outcome was the diagnostic criteria chosen. Diagnostic criteria were divided into five nonexclusive categories: "clinical diagnosis," MEDPED, Simon Broome, DLCN, and other. RESULTS: Most adults enrolled in CASCADE FH (55.0%) received a "clinical diagnosis." The most commonly used formal criteria was Simon-Broome only (21%), followed by multiple diagnostic criteria (16%), MEDPED only (7%), DLCN only (1%), and other (0.5%), P < .0001. Of the patients with only a "clinical diagnosis," 93% would have met criteria for Simon Broome, DLCN, or MEDPED based on the data available in the registry. CONCLUSIONS: Our findings demonstrate heterogeneity in the application of FH diagnostic criteria in the United States. A nationwide consensus definition may lead to better identification, earlier treatment, and ultimately CHD prevention.


Assuntos
Hiperlipoproteinemia Tipo II/diagnóstico , Adulto , LDL-Colesterol/sangue , Estudos Transversais , Bases de Dados Factuais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Médicos , Sistema de Registros , Estados Unidos
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