Search

Your search keyword '"Fu, Sirui"' showing total 4 results
Start Over Author "Fu, Sirui" Topic transjugular intrahepatic portosystemic shunt
4 results on '"Fu, Sirui"'

3. Prediction of overt hepatic encephalopathy after transjugular intrahepatic portosystemic shunt treatment: a cohort study

Author

Kai Tang, Fu Sirui, Ligong Lu, Chongyang Duan, Yang Yang, Bin Cao, Jianwen Huang, Wenfeng Shi, Kenan Hao, Xiaofeng He, Shirui Yang, Xiao Bai, and Yong Li

Subjects
Adult, Liver Cirrhosis, Male, medicine.medical_specialty, Adolescent, medicine.medical_treatment, Decision curve, Nervous system toxicity, Subgroup analysis, Logistic regression, Combined model, Clinical factor, Cohort Studies, Young Adult, Risk Factors, Preoperative prediction, Internal medicine, Discrimination, medicine, Humans, Hepatic encephalopathy, Risk stratification, Aged, Retrospective Studies, Framingham Risk Score, Hepatology, business.industry, Middle Aged, Imaging characteristics, medicine.disease, Colorectal surgery, Treatment Outcome, Hepatic Encephalopathy, Calibration, TIPS, Female, Original Article, Radiology, Portasystemic Shunt, Transjugular Intrahepatic, business, Transjugular intrahepatic portosystemic shunt, Cohort study
Abstract

Background/purpose Overt hepatic encephalopathy (HE) risk should be preoperatively predicted to identify patients suitable for curative transjugular intrahepatic portosystemic shunt (TIPS) instead of palliative treatments. Methods A total of 185 patients who underwent TIPS procedure were randomised (130 in the training dataset and 55 in the validation dataset). Clinical factors and imaging characteristics were assessed. Three different models were established by logistic regression analyses based on clinical factors (ModelC), imaging characteristics (ModelI), and a combination of both (ModelCI). Their discrimination, calibration, and decision curves were compared, to identify the best model. Subgroup analysis was performed for the best model. Results ModelCI, which contained two clinical factors and two imaging characteristics, was identified as the best model. The areas under the curve of ModelC, ModelI, and ModelCI were 0.870, 0.963, and 0.978 for the training dataset and 0.831, 0.971, and 0.969 for the validation dataset. The combined model outperformed the clinical and imaging models in terms of calibration and decision curves. The performance of ModelCI was not influenced by total bilirubin, Child–Pugh stages, model of end-stage liver disease score, or ammonia. The subgroup with a risk score ≥ 0.88 exhibited a higher proportion of overt HE (training dataset: 13.3% vs. 97.4%, p p Conclusion Our combination model can successfully predict the risk of overt HE post-TIPS. For the low-risk subgroup, TIPS can be performed safely; however, for the high-risk subgroup, it should be considered more carefully. Graphic abstract

Published
2020

4. Preoperative prediction of overt hepatic encephalopathy caused by transjugular intrahepatic portosystemic shunt.

Author

Yang, Yang, Liang, Xueqing, Yang, Shirui, He, Xiaofeng, Huang, Mingsheng, Shi, Wenfeng, Luo, Junyang, Duan, Chongyang, Feng, Xinghui, Fu, Sirui, and Lu, Ligong

Subjects
*HEPATIC encephalopathy, *RECEIVER operating characteristic curves, *CEREBROSPINAL fluid shunts
Abstract

Purpose: Preoperative prediction of overt hepatic encephalopathy (OHE) should be performed in patients with variceal bleeding treated using the transjugular intrahepatic portosystemic shunt (TIPS) procedure. A reliable prediction tool is therefore required.Method: Patients with cirrhosis-related variceal bleeding treated using the TIPS procedure were screened at two hospitals. Patients classified as Child-Pugh Class B were identified. The least absolute shrinkage and selection operator method and the backward stepwise selection method were used to screen the clinical and radiological characteristics of participants. Then, models were constructed accordingly to predict OHE. Area under the receiver operating characteristic curves, calibration curves, and decision curves were performed to discover the optimal model. Finally, whether clinical factors influenced the performance of our optimal model was tested.Results: A total of 191 patients were included (training cohort: 127 cases; validation cohort: 64 cases). Three novel radiological independent risk factors were found. The combined model outperformed the models containing clinical factors or radiological characteristics alone. The areas under the curve for the training and validation cohorts were 0.901 and 0.903, respectively, with satisfactory calibration and decision curves. The Model for End-Stage Liver Disease score, serum sodium, albumin, total bilirubin, and age exhibited limited influence on the performance of the combined model.Conclusions: These radiological characteristics are also independent risk factors for post-TIPS OHE. Combining clinical factors and radiological characteristics was an effective means of predicting OHE. This study's model could be used for preoperative selection of appropriate patients before the TIPS procedure is performed. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results