RT info:eu-repo/semantics/article
T1 Gene Expression Patterns Distinguish Mortality Risk in Patients with Postsurgical Shock
A1 Martínez de Paz, Pedro José
A1 Aragón Camino, Marta
A1 Gómez Sánchez, Esther
A1 Lorenzo López, Mario
A1 Gómez Pesquera, Estefanía
A1 López Herrero, Rocio
A1 Sánchez Quirós, Belén
A1 Varga Martínez, Olga de la
A1 Tamayo Velasco, Álvaro
A1 Ortega Loubon, Christian Joseph
A1 García Morán, Emilio
A1 Gonzalo Benito, Hugo
A1 Heredia Rodríguez, María
A1 Tamayo Gómez, Eduardo
K1 Mortality
K1 Mortalidad
K1 Postsurgical shock
K1 Shock posquirúrgico
K1 Sepsis
K1 Biomarkers
K1 Biomarcadores
AB Nowadays, mortality rates in intensive care units are the highest of all hospital units. However, there is not a reliable prognostic system to predict the likelihood of death in patients with postsurgical shock. Thus, the aim of the present work is to obtain a gene expression signature to distinguish the low and high risk of death in postsurgical shock patients. In this sense, mRNA levels were evaluated by microarray on a discovery cohort to select the most differentially expressed genes between surviving and non-surviving groups 30 days after the operation. Selected genes were evaluated by quantitative real-time polymerase chain reaction (qPCR) in a validation cohort to validate the reliability of data. A receiver-operating characteristic analysis with the area under the curve was performed to quantify the sensitivity and specificity for gene expression levels, which were compared with predictions by established risk scales, such as acute physiology and chronic health evaluation (APACHE) and sequential organ failure assessment (SOFA). IL1R2, CD177, RETN, and OLFM4 genes were upregulated in the non-surviving group of the discovery cohort, and their predictive power was confirmed in the validation cohort. This work offers new biomarkers based on transcriptional patterns to classify the postsurgical shock patients according to low and high risk of death. The results present more accuracy than other mortality risk scores.
PB MDPI
SN 2077-0383
YR 2020
FD 2020
LK https://uvadoc.uva.es/handle/10324/52333
UL https://uvadoc.uva.es/handle/10324/52333
LA eng
NO Journal of Clinical Medicine, 2020, vol. 9, n. 5, 1276
NO Producción Científica
DS UVaDOC
RD 23-nov-2024