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1.
Ann Agric Environ Med ; 29(2): 190-200, 2022 Jun 24.
Artigo em Inglês | MEDLINE | ID: mdl-35767750

RESUMO

INTRODUCTION: Susac's syndrome (SS) is a rare, autoimmune-mediated endoteliopathy characterized by a clinical triad of encephalopathy, branch retinal artery occlusion, and sensorineural hearing loss. SS is also characterized by a neuroimaging triad consisting of white matter lesions, grey matter lesions, and leptomeningeal enhancement on magnetic resonance imaging (MRI). Considering the rarity of SS, as well as certain similarity to other, more frequent neurological diseases, such as multiple sclerosis (MS), this syndrome is sometimes incorrectly diagnosed and treated. OBJECTIVE: The aim of the study is to present the current state of knowledge on SS, with particular consideration for the differential diagnostics between SS and MS, using the latest available imaging techniques, such as brain MRI, optical coherence tomography (OCT), OCT angiography (OCTA) and fluorescein angiography (FA). REVIEW METHODS: The major electronic databases (PubMed, Google Scholar) were searched manually in order to identify the relevant studies published on SS. BRIEF DESCRIPTION OF THE STATE OF KNOWLEDGE: Distinguishing SS from MS is a diagnostic challenge. In the majority of cases, patients with SS do not present the complete clinical or neuroimaging triad, and a delay in making the correct diagnosis exposes the patient to the occurrence of complications, resulting from the development of the underlying disease, or/and the application of improper treatment. In the case of SS the results of brain MRI and FA are essential for making the correct diagnosis as they may reveal pathognomonic changes. SUMMARY: Imaging examinations, such as brain MRI, FA, and OCT complement each other, due to which the diagnosis of SS may be simpler, irrespective of the stage of the disease.


Assuntos
Oclusão da Artéria Retiniana , Síndrome de Susac , Encéfalo/diagnóstico por imagem , Angiofluoresceinografia/métodos , Humanos , Imageamento por Ressonância Magnética/métodos , Oclusão da Artéria Retiniana/complicações , Oclusão da Artéria Retiniana/diagnóstico , Oclusão da Artéria Retiniana/patologia , Síndrome de Susac/complicações , Síndrome de Susac/diagnóstico por imagem
2.
PLoS One ; 15(6): e0235121, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32569336

RESUMO

OBJECTIVE: Identifying metabolic disorders at the earliest phase of their development allows for an early intervention and the prevention of serious consequences of diseases. However, it is difficult to determine which of the anthropometric indices of obesity is the best tool for diagnosing metabolic disorders. The aims of this study were to evaluate the usefulness of selected anthropometric indices and to determine optimal cut-off points for the identification of single metabolic disorders that are components of metabolic syndrome (MetS). DESIGN: Cross-sectional study. PARTICIPANTS: We analyzed the data of 12,328 participants aged 55.7±5.4 years. All participants were of European descent. PRIMARY OUTCOME MEASURE: Four MetS components were included: high glucose concentration, high blood triglyceride concentration, low high-density lipoprotein cholesterol concentration, and elevated blood pressure. The following obesity indices were considered: waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), body fat percentage (%BF), Clínica Universidad de Navarra-body adiposity estimator (CUN-BAE), body roundness index (BRI), and a body shape index (ABSI). RESULTS: The following indices had the highest discriminatory power for the identification of at least one MetS component: CUN-BAE, BMI, and WC in men (AUC = 0.734, 0.728, and 0.728, respectively) and WHtR, CUN-BAE, and WC in women (AUC = 0.715, 0.714, and 0.712, respectively) (p<0.001 for all). The other indices were similarly useful, except for the ABSI. CONCLUSIONS: For the BMI, the optimal cut-off point for the identification of metabolic abnormalities was 27.2 kg/m2 for both sexes. For the WC, the optimal cut-off point was of 94 cm for men and 87 cm for women. Prospective studies are needed to identify those indices in which changes in value predict the occurrence of metabolic disorders best.


Assuntos
Antropometria , Doenças Metabólicas/diagnóstico , Área Sob a Curva , Feminino , Humanos , Masculino , Pessoa de Meia-Idade
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