Title:Alcoholic/Nonalcoholic Fatty Liver Disease Detection with Transient
Elastography: A Detailed Review and Meta-analysis
Volume: 20
Author(s): Yinyou Fang, Xiaofei Li, Fang Zong and Tianan Jiang*
Affiliation:
- Department of Ultrasound Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310003, China
- Zhejiang Provincial Key Laboratory of Pulsed Electric Field Technology for Medical Transformation, Hangzhou, Zhejiang 310003, China
Keywords:
Liver, Fatty liver disease, Transient elastography, Controlled attenuation parameter, Liver stiffness measurement, Assessment.
Abstract:
Background:
The liver plays a significant role in the digestive system, and disease in the liver initiates various other problems. The liver is severely affected due
to alcohol use, and it initiates various chronic diseases, including Alcohol-Related Liver Disease (ARLD). Alcoholic/Nonalcoholic Fatty Liver
Disease (AFLD/NFLD) is a severe medical emergency, and early screening and treatment are necessary to cure the patient. The untreated
AFLD/NFLD will cause various problems, including fatigue, weight loss, and discomfort in the abdomen.
Objective:
This study aims to present a detailed review and investigation of schemes considered in medical clinics to identify the AFLD/NFLD coupled
problems and present the merit of the Transient Elastography (TE) combined with Fibroscan® practice to identify liver abnormality.
Methods:
This research aims to study the clinical significance and the accuracy of TE-supported liver illness screening.
Results:
This work aims to collect the recent research works and clinical reports published from 2011 to 2021 from the chosen databases and provide a
detailed review using the clinical information discussed in the selected articles.
Conclusion:
The essential statistical investigation of the collected data is executed with Review Manager (RevMan®) software, and the significance of the TE is
confirmed using the articles supporting a 2x2 contingency table, and each case is evaluated using a p-score and the Region of Convergence (RoC)
curve for 95% confidence intervals.
