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20th European Congress of Endocrinology

Barcelona, Spain
19 May 2018 - 22 May 2018

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ECE 2018, 19 - 22 May 2018; Barcelona, Spain

Symposia

Predicting events in autoimmune thyroid diseas

ea0056s1.1 | Predicting events in autoimmune thyroid diseas | ECE2018

The THEA score in familial thyroid dysfunction. Predictive factors of autoimmune thyroid disease

Effraimidis Grigorios

AutoImmune Thyroid Disease (AITD) is, nowadays, generally considered to be a complex multifactorial entity, in which the interplay between genetic and environmental factors results in the expression of the disease. Genetic predisposition plays a major role in the pathogenesis of AITD, as siblings and other family members of AITD patients are at increased risk for AITD. Then, how can we, as physicians, answer the question of our AITD patients ‘will my children also get the...

ea0056s1.2 | Predicting events in autoimmune thyroid diseas | ECE2018

IgG4 related thyroid autoimmune disease

Chiovato Luca

IgG4-related disease (IgG4-RD) is a fibro-inflammatory, immune-mediated, systemic disease usually presenting with tumefactive lesions and a subacute onset mimicking malignancy. A subset of autoimmune thyroid pathologic conditions can be incorporated in the spectrum of IgG4-RD. In some cases of Hashimoto’s Thyroiditis (HT) a rich IgG4-positive plasma cell infiltration has been described, and a marked storiform fibrosis is typical of the fibrotic variant of HT (FVHT) and of...

ea0056s1.3 | Predicting events in autoimmune thyroid diseas | ECE2018

New scores for the prediction of Graves’ disease

Zarkovis Milos

After treatment, hyperthyroidism will relapse in approximately half of the Graves’ diseases patients, and clinically relevant orbitopathy will develop in about 25% of the diseased. Therefore, predicting who will relapse or develop orbitopathy is both clinically important and contributes to understanding of the pathophysiology of the disease. To predict the risk of recurrence of hyperthyroidism, before the start of antithyroid drug therapy, GREAT (based on clinical markers...