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1.
Medicine (Baltimore) ; 103(17): e37899, 2024 Apr 26.
Artículo en Inglés | MEDLINE | ID: mdl-38669377

RESUMEN

To investigate the clinical value of contrast-enhanced ultrasound in the prediction of hepatic encephalopathy (HE) in patients with hepatitis B cirrhosis after intrahepatic portal-systemic shunt via jugular vein. In this retrospective study, we collected data from 75 patients with hepatitis B, cirrhosis, and portal hypertension who underwent jugular intrahepatic portosystemic shunt from February 2019 to February 2022. The diagnostic instrument used was the TOSHIBA Aplio500 color Doppler ultrasound with contrast-enhanced ultrasound capabilities. The trial group comprised 20 patients with HE within 3 months postsurgery, while the control group (CG) included 55 patients without HE within the same postoperative period. All patients underwent various examinations before and within 48 hours after surgery, including observation of liver and spleen size and stent position, as well as assessment of blood flow direction in portal and hepatic veins. Subsequently, contrast-enhanced ultrasound was employed to examine and observe perfusion changes of contrast agents in hepatic veins, hepatic arteries, and portal veins (PV). Changes in PV pressure gradient, intrahepatic, and stent blood flow perfusion (BFP) were explored in both postoperative trials and CGs. The trial group exhibited higher BFP volume, PV pressure gradient difference, and percentage decrease compared to the CG. A weak positive correlation was observed between blood flow within the liver stent and PV pressure gradient difference, as well as the percentage decrease in PV pressure gradient. The correlation coefficient between blood flowing perfusion volume within the stent and the difference in PV pressure gradient was R = 0.415 (P = .000). The correlating coefficient between BFP amount within the stent and the percentage decrease in PV pressure gradient was R = 0.261 (P = .027). The area under the receiver operating characteristic curve for stent perfusion volume, difference in PV pressure gradient, and percentage decrease in PV pressure gradient was 0.691, 0.759, and 0.742, respectively. An increase in PV pressure gradient accelerates blood flow within the stent, predisposing to HE. Changes in hepatic BFP following transjugular intrahepatic portosystemic shunt can effectively predict the occurrence of HE, demonstrating significant clinical relevance.


Asunto(s)
Medios de Contraste , Derivación Portosistémica Intrahepática Transyugular , Humanos , Masculino , Derivación Portosistémica Intrahepática Transyugular/métodos , Femenino , Persona de Mediana Edad , Estudios Retrospectivos , Hipertensión Portal/cirugía , Hipertensión Portal/fisiopatología , Hipertensión Portal/diagnóstico por imagen , Hígado/irrigación sanguínea , Hígado/diagnóstico por imagen , Hígado/cirugía , Ultrasonografía Doppler en Color/métodos , Adulto , Cirrosis Hepática/cirugía , Cirrosis Hepática/fisiopatología , Cirrosis Hepática/diagnóstico por imagen , Circulación Hepática/fisiología , Anciano , Vena Porta/diagnóstico por imagen , Vena Porta/fisiopatología , Relevancia Clínica
2.
Future Oncol ; 18(2): 215-230, 2022 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-34854737

RESUMEN

Aims: This study presents a survival stratification model based on multi-omics integration using bidirectional deep neural networks (BiDNNs) in gastric cancer. Methods: Based on the survival-related representation features yielded by BiDNNs through integrating transcriptomics and epigenomics data, K-means clustering analysis was performed to cluster tumor samples into different survival subgroups. The BiDNNs-based model was validated using tenfold cross-validation and in two independent confirmation cohorts. Results: Using the BiDNNs-based survival stratification model, patients were grouped into two survival subgroups with log-rank p-value = 9.05E-05. The subgroups classification was robustly validated in tenfold cross-validation (C-index = 0.65 ± 0.02) and in two confirmation cohorts (E-GEOD-26253, C-index = 0.609; E-GEOD-62254, C-index = 0.706). Conclusion: We propose and validate a robust and stable BiDNN-based survival stratification model in gastric cancer.


Asunto(s)
Biomarcadores de Tumor/genética , Neoplasias Gástricas/mortalidad , Aprendizaje Automático no Supervisado , Anciano , Análisis por Conglomerados , Metilación de ADN , Conjuntos de Datos como Asunto , Epigenómica/métodos , Femenino , Estudios de Seguimiento , Humanos , Estimación de Kaplan-Meier , Masculino , Persona de Mediana Edad , RNA-Seq/métodos , Medición de Riesgo/métodos , Neoplasias Gástricas/genética
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