Searchable abstracts of presentations at key conferences in endocrinology

ea0063p56 | Adrenal and Neuroendocrine Tumours 1 | ECE2019

A difficult diagnosis: pheochromocytoma or methamphetamine abuse?

Constantinescu Georgiana , Leike Steffen , Kunath Carola , Langton Katharina , Gruber Matthias , Peitzsch Mirko , Deinum Jaap , Lenders Jacques , Eisenhofer Graeme

Introduction: Pheochromocytomas represent rare but potential lethal tumors arising from the adrenal medulla. Early recognition and diagnosis represent a challenge due to the non-specific character of signs and symptoms. The classic presentation includes headache, sweating, palpitations and other signs and symptoms of apparent catecholamine excess occurring in paroxysms. Sympathomimetics may result in a similar presentation, potentially complicating the diagnosis.<p class="...

ea0081oc13.6 | Oral Communications 13: Adrenal and Cardiovascular Endocrinology 2 | ECE2022

Machine Learning models for the accurate prediction of malignant pheochromocytomas and paragangliomas

Pamporaki Christina , Berends Annika MA , Filippatos Angelos , Prodanov Tamara , Meuter Leah , Prejbisz Aleksander , Beuschlein Felix , Fassnacht Martin , Timmers Henri , Noelting Svenja , Abhyankar Kaushik Ganesh , Contsantinescu Georgiana , Kunath Carola , Wang Katharina , Remde Hanna , Januszewicz Andrzej , Robledo Mercedes , Lenders Jacques , Kerstens Michiel , Pacak Karel , Eisenhofer Graeme

Introduction: Pheochromocytomas and paragangliomas (PPGLs) exhibit an up to 20% malignancy rate. Various clinical, genetic, and pathological features have been proposed as predictors of malignancy. However, until present there are no robust indices to reliably predict metastatic PPGLs.Aim: The aim of the present study was to prospectively validate the value of methoxytyramine as risk marker of metastatic disease and establish a machine learning (ML) mode...