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2022-09-06

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cc by (c) Micó, Víctor et al ., 2022
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/191808

Morbid liver manifestations are intrinsically bound to metabolic syndrome and nutrient intake based on a machine-learning cluster analysis

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Metabolic syndrome (MetS) is one of the most important medical problems around the world. Identification of patient ' s singular characteristic could help to reduce the clinical impact and facilitate individualized management. This study aimed to categorize MetS patients using phenotypical and clinical variables habitually collected during health check-ups of individuals considered to have high cardiovascular risk. The selected markers to categorize MetS participants included anthropometric variables as well as clinical data, biochemical parameters and prescribed pharmacological treatment. An exploratory factor analysis was carried out with a subsequent hierarchical cluster analysis using the z-scores from factor analysis. The first step identified three different factors. The first was determined by hypercholesterolemia and associated treatments, the second factor exhibited glycemic disorders and accompanying treatments and the third factor was characterized by hepatic enzymes. Subsequently four clusters of patients were identified, where cluster 1 was characterized by glucose disorders and treatments, cluster 2 presented mild MetS, cluster 3 presented exacerbated levels of hepatic enzymes and cluster 4 highlighted cholesterol and its associated treatments Interestingly, the liver status related cluster was characterized by higher protein consumption and cluster 4 with low polyunsaturated fatty acid intake. This research emphasized the potential clinical relevance of hepatic impairments in addition to MetS traditional characterization for precision and personalized management of MetS patients.

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Matèries

Marcadors bioquímics, Síndrome metabòlica, Anàlisi de conglomerats

Matèries (anglès)

Biochemical markers, Metabolic syndrome, Cluster analysis

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Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))
<b>Publicacions de projectes de recerca finançats per la UE</b>
Articles publicats en revistes (IDIBAPS: Institut d'investigacions Biomèdiques August Pi i Sunyer)

Citació

MICÓ, Víctor, SAN CRISTOBAL, Rodrigo, MARTÍN, Roberto, MARTÍNEZ-GONZÁLEZ, Miguel ángel, SALAS SALVADÓ, Jordi, CORELLA PIQUER, Dolores, FITÓ COLOMER, Montserrat, ALONSO GÓMEZ, Ángel m., WÄRNBERG, Julia, VIOQUE, Jesús, ROMAGUERA, Dora, LÓPEZ MIRANDA, José, ESTRUCH RIBA, Ramon, TINAHONES, Francisco j., LAPETRA, José, SERRA MAJEM, Lluís, BUENO CAVANILLAS, Aurora, TUR, Josep a., MARTÍN SÁNCHEZ, Vicente, PINTÓ SALA, Xavier, DELGADO RODRÍGUEZ, Miguel, MATÍA MARTÍN, Pilar, VIDAL I CORTADA, Josep, VÁZQUEZ, Clotilde, GARCÍA ARELLANO, Ana, PERTUSA MARTINEZ, Salvador, CHAPLIN, Alice, GARCÍA RÍOS, Antonio, MUÑOZ BRAVO, Carlos, SCHRÖDER, Helmut, BABIO, Nancy, SORLÍ, José v., GONZALEZ, Jose i., MARTINEZ URBISTONDO, Diego, TOLEDO ATUCHA, Estefanía, BULLÓN, Vanessa, RUIZ CANELA, Miguel, PORTILLO, María puy, MACÍAS GONZÁLEZ, Manuel, PEREZ DIAZ DEL CAMPO, Nuria, GARCÍA GAVILÁN, Jesús, DAIMIEL, Lidia, MARTÍNEZ, J. alfredo. Morbid liver manifestations are intrinsically bound to metabolic syndrome and nutrient intake based on a machine-learning cluster analysis. _Frontiers in Endocrinology_. 2022. Vol. 13. [consulta: 24 de novembre de 2025]. ISSN: 1664-2392. [Disponible a: https://hdl.handle.net/2445/191808]

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