Yuhao He1, Yujia Yan2, Sunfu Zhang1. 1. Department of Neurosurgery, Chengdu Third People's Hospital, Chengdu, Sichuan Province, 610031. 2. Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin, 300000, China.
Abstract
BACKGROUND: Early stage of cirrhosis is of great value in the diagnosis and management in patients with chronic liver disease (CLD). Recent studies have shown that quantitative liver surface nodularity (LSN) score based on imaging techniques can be used to predict the early cirrhosis stage noninvasively, with varied diagnostic accuracy and limited sample size. Hence, this study will evaluate the diagnostic accuracy of LSN in the prediction of early cirrhosis. METHODS: We will conduct a comprehensive search in PubMed, Web of Science, Cochrane Library, and Chinese biomedical databases to identify eligible studies. The literature screening, data extraction, data analysis, and quality assessment will then be carried out. The summary receiver-operating-characteristic (ROC) and pooled sensitivity, specificity will be calculated to summarize the diagnostic performance of LSN using a random-effect model. A meta-regression analysis will be performed to investigate the underlying cause of the heterogeneity. RESULTS: This study will evaluate the diagnostic accuracy of LSN score in the identification of early cirrhosis, which may further determine whether this method can be used as an alternative in the assessment of CLD patients. CONCLUSIONS: This study will help to determine the diagnostic accuracy and summarize the recent evidence on this issue. STUDY REGISTRATION: INPLASY2020100096.
BACKGROUND: Early stage of cirrhosis is of great value in the diagnosis and management in patients with chronic liver disease (CLD). Recent studies have shown that quantitative liver surface nodularity (LSN) score based on imaging techniques can be used to predict the early cirrhosis stage noninvasively, with varied diagnostic accuracy and limited sample size. Hence, this study will evaluate the diagnostic accuracy of LSN in the prediction of early cirrhosis. METHODS: We will conduct a comprehensive search in PubMed, Web of Science, Cochrane Library, and Chinese biomedical databases to identify eligible studies. The literature screening, data extraction, data analysis, and quality assessment will then be carried out. The summary receiver-operating-characteristic (ROC) and pooled sensitivity, specificity will be calculated to summarize the diagnostic performance of LSN using a random-effect model. A meta-regression analysis will be performed to investigate the underlying cause of the heterogeneity. RESULTS: This study will evaluate the diagnostic accuracy of LSN score in the identification of early cirrhosis, which may further determine whether this method can be used as an alternative in the assessment of CLD patients. CONCLUSIONS: This study will help to determine the diagnostic accuracy and summarize the recent evidence on this issue. STUDY REGISTRATION: INPLASY2020100096.
Authors: Larissa Shamseer; David Moher; Mike Clarke; Davina Ghersi; Alessandro Liberati; Mark Petticrew; Paul Shekelle; Lesley A Stewart Journal: BMJ Date: 2015-01-02
Authors: Grace C Lo; Cecilia Besa; Michael J King; Martin Kang; Ashley Stueck; Swan Thung; Mathilde Wagner; Andrew D Smith; Bachir Taouli Journal: Eur J Radiol Open Date: 2017-07-21