Publications by authors named "Yi-Shan He"
Article Synopsis
- Hepatic encephalopathy (HE) is a serious complication of liver failure that often leads to poor outcomes; this study evaluates D-dimer as a predictor of mortality in HE patients.
- About 39.2% of patients with chronic liver failure and HE died within a year, with higher D-dimer levels in those who did not survive, indicating its potential as a risk factor for mortality.
- A new predictive model combining age, D-dimer, ALT, and sodium showed better accuracy for 1-year mortality than traditional scoring systems like MELD and Child-Pugh.
Article Synopsis
- The study investigated the impact of the triglyceride-glucose (TyG) index on the risk of developing hepatocellular carcinoma (HCC) in patients with liver cirrhosis caused by hepatitis B virus (HBV).
- Out of 242 patients followed for about 37 months, a significant number developed HCC, with the TyG index being notably higher in these patients compared to those who did not develop HCC.
- Age, type of cirrhosis (decompensated), TyG index, and HBV DNA positivity were found to be independent risk factors for HCC, leading to the development of a predictive model to assess HCC risk among these patients.
Background: Decrease in estimated glomerular filtration rate (eGFR) during Tenofovir disoproxil fumarate (TDF) treatment remains a concern, and few patients experience partial recovery of eGFR. This study aimed to investigate the risk factors for eGFR recovery in patients with and without hypertriglyceridemia.
Methods: A total of 203 patients with chronic HBV infection were prospectively recruited and followed up for three years.
Background: Correlation between Triglyceride (TG) and estimated glomerular filtration rate (eGFR) remains largely unknown in overweight and non-overweight patients.
Aim: To investigated the dynamic changes of eGFR and lipid profiles during 3-year tenofovir disoproxil fumarate (TDF) treatment in patients with chronic hepatitis B (CHB) and overweight.
Methods: A total of 202 CHB patients who received TDF treatment at the Third People's Hospital of Changzhou (Changzhou, China) and Nanjing Drum Tower Hospital (Nanjing, China) between January 2016 and May 2018 were retrospectively enrolled.
With recent significant improvements in artificial intelligence (AI), especially in the field of deep learning, an increasing number of studies have evaluated the use of AI in endoscopy to detect and diagnose gastrointestinal (GI) lesions. The present review summarizes current publications on the use of AI in GI endoscopy and focuses on the challenges and future of AI-aided systems. We expect AI to provide an effective and practical method for endoscopists in lesion detection and characterization as well as in quality control in endoscopy.
View Article and Find Full Text PDFBackground And Aims: Quality control can decrease variations in the performance of colonoscopists and improve the effectiveness of colonoscopy to prevent colorectal cancers. Unfortunately, routine quality control is difficult to carry out because a practical method is lacking. The aim of this study was to develop an automatic quality control system (AQCS) and assess whether it could improve polyp and adenoma detection in clinical practice.
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