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Endocrine Abstracts

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ea0094oc5.1 | Adrenal and Cardiovascular | SFEBES2023

Urine steroid metabolomics as a diagnostic tool in endocrine hypertension

Prete Alessandro , Abdi Lida , Suntornlohanakul Onnicha , Lang Katharina , Riancho Julien , Lazkani Aida , Larsen Casper K. , Gimenez-Roqueplo Anne-Paule , Pecori Alessio , Tetti Martina , Monticone Silvia , Muller Lisa M. , Adolf Christian , Timmers Henri J.L.M. , Hampson Stephanie , Eisenhofer Graeme , Ceccato Filippo , Beuschlein Felix , Kabat Marek , Bertherat Jerome , Dennedy Conall , Davies Eleanor , Deinum Jaap , Reincke Martin , Paolo Rossi Gian , Mulatero Paolo , Amar Laurence , Zennaro Maria-Christina , Sitch Alice J. , Tino Peter , Biehl Michael , Taylor Angela E. , Arlt Wiebke

Background: Hypertension affects more than 30% of the adult population worldwide and is a major cardiovascular risk factor. Identifying secondary causes of hypertension is key to offering targeted treatment and mitigating adverse health outcomes. We tested the performance of urine steroid metabolomics (USM), the computational analysis of 24-hour urine steroid metabolome data by machine learning, for diagnosing endocrine hypertension.<str...
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ea0099rc11.4 | Rapid Communications 11: Adrenal and Cardiovascular Endocrinology | Part II | ECE2024

Urine steroid metabolomics to diagnose endocrine hypertension: results from the ENS@T-HT project

Prete Alessandro , Abdi Lida , Suntornlohanakul Onnicha , Lang Katharina , Veen Roland , Canducci Marco , Riancho Julien , Lazkani Aida , Larsen Casper K. , Gimenez-Roqueplo Anne-Paule , Pecori Alessio , Tetti Martina , Monticone Silvia , Muller Lisa M. , Adolf Christian , Timmers Henri JLM , Hampson Stephanie , Eisenhofer Graeme , Ceccato Filippo , Beuschlein Felix , Kabat Marek , Bertherat Jerome , Dennedy M. Conall , Davies Eleanor , Deinum Jaap , Reincke Martin , Rossi Gian Paolo , Mulatero Paolo , Amar Laurence , Zennaro Maria-Christina , Sitch Alice J. , Tino Peter , Biehl Michael , Taylor Angela E. , Arlt Wiebke

Background: Hypertension affects more than 30% of the adult population worldwide and is a major cardiovascular risk factor. Identifying secondary causes of hypertension is key to offering targeted treatments and mitigating adverse health outcomes. We tested the performance of urine steroid metabolomics (USM), the computational analysis of 24-hour urine steroid metabolome data by machine learning, for diagnosing endocrine forms of hypertension.Methods: 14...
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Endocrine Abstracts
ISSN 1470-3947 (print) | ISSN 1479-6848 (online)
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