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ea0099p60 | Diabetes, Obesity, Metabolism and Nutrition | ECE2024

Predicting liver fibrosis using artificial intelligence in obese patiens

Penso Rona , Perez Natalia , Matias Pilar , Torres Antonio , Sanchez-Pernaute Andres , Garcia Candela , Crespo Irene , Herraiz Lorea , Elena Mendoza Maria , Angel Rubio Miguel

Introduction: The prevalence of hepatic steatosis in people with obesity is very high. However, what is relevant is to detect those patients with associated fibrosis. The aim of the present study was to predict by artificial intelligence (AI) using clinical-analytical parameters, the presence of liver fibrosis in the biopsy performed during bariatric surgery (BS) of patients with obesity.Subjects and methodology: Cross-sectional study of patients with ob...

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ea0037ep677 | Pituitary: basic and neuroendocrinology | ECE2015

The impact of correcting the serum sodium level for total proteins in patients receiving parenteral nutrition

Hoyos Emilia Gomez , Martin Pilar Matia , Hernandez Martin Cuesta , Gracia Teresa Ruiz , Ferre Natalia Perez , Garcia Lucio Cabrerizo , Herrera Miguel Angel Rubio , De Luis Roman Daniel , Pascual Alfonso Calle , de la Vega Isabelle Runkle

Introduction: In a majority of Spanish hospitals, serum sodium levels (SNa) are determined by indirect electrode methodology (sodium in the liquid fraction of serum) divided by the total serum volume (mmol/l). To avoid over/underestimating SNa, a formula can be applied: SNa corrected for total proteins (TP)=SNa×93 divided by (99.1−(0.7×TP)). Hypoproteinaemia is frequent in patients receiving parenteral nutrition (PN), and is probably related to surgery, acute d...

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Endocrine Abstracts

Predicting liver fibrosis using artificial intelligence in obese patiens

The impact of correcting the serum sodium level for total proteins in patients receiving parenteral nutrition

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