In recent years, ultrasound attenuation imaging (ATI) has emerged as a new method to detect liver steatosis. However, thus far, no studies have confirmed the clinical utility of this technology. Using a retrospective database analysis of 28 patients with chronic liver disease who underwent ultrasound liver biopsy and ATI, we compared the presence and degree of steatosis measured by ATI with the results obtained through liver biopsy. The area under the receiver operating characteristic curve (AUROC) of the ATI for differentiating between normal and hepatic steatosis was 0.97 (95% confidence interval: 0.83–1.00). The AUROC of the ATI was 0.99 (95% confidence interval: 0.86–1.00) in grade ≥2 liver steatosis and 0.97 (95% confidence interval: 0.82–1.00) in grade 3. ATI showed good consistency and accuracy for the steatosis grading of liver biopsy. Therefore, ATI represents a novel diagnostic measurement to support the diagnosis of liver steatosis in non-invasive clinical practice.

The management of peptic ulcer bleeding is clinically challenging. For decades, the Forrest classification has been used for risk stratification for nonvariceal ulcer bleeding. The perception and interpretation of the Forrest classification vary among different endoscopists. The relationship between the bleeder and ulcer images and the different stages of the Forrest classification has not been studied yet. Endoscopic still images of 276 patients with peptic ulcer bleeding for the past 3 years were retrieved and reviewed. The intra-rater agreement and inter-rater agreement were compared. The obtained endoscopic images were manually drawn to delineate the extent of the ulcer and bleeding area. The areas of the region of interest were compared between the different stages of the Forrest classification. A total of 276 images were first classified by two experienced tutor endoscopists. The images were reviewed by six other endoscopists. A good intra-rater correlation was observed (0.92–0.98). A good inter-rater correlation was observed among the different levels of experience (0.639–0.859). The correlation was higher among tutor and junior endoscopists than among experienced endoscopists. Low-risk Forrest IIC and III lesions show distinct patterns compared to high-risk Forrest I, IIA, or IIB lesions. We found good agreement of the Forrest classification among different endoscopists in a single institution. This is the first study to quantitively analyze the obtained and explain the distinct patterns of bleeding ulcers from endoscopy images.

The rising incidence of fatty liver disease (FLD) poses a health challenge, and is expected to be the leading global cause of liver-related morbidity and mortality in the near future. Early case identification is crucial for disease intervention. A retrospective cross-sectional study was performed on 31,930 Taiwanese subjects (25,544 training and 6386 testing sets) who had received health check-ups and abdominal ultrasounds in Changhua Christian Hospital from January 2009 to January 2019. Clinical and laboratory factors were included for analysis by different machine-learning algorithms. In addition, the performance of the machine-learning algorithms was compared with that of the fatty liver index (FLI). Totally, 6658/25,544 (26.1%) and 1647/6386 (25.8%) subjects had moderate-to-severe liver disease in the training and testing sets, respectively. Five machine-learning models were examined and demonstrated exemplary performance in predicting FLD. Among these models, the xgBoost model revealed the highest area under the receiver operating characteristic (AUROC) (0.882), accuracy (0.833), F1 score (0.829), sensitivity (0.833), and specificity (0.683) compared with those of neural network, logistic regression, random forest, and support vector machine-learning models. The xgBoost, neural network, and logistic regression models had a significantly higher AUROC than that of FLI. Body mass index was the most important feature to predict FLD according to the feature ranking scores. The xgBoost model had the best overall prediction ability for diagnosing FLD in our study. Machine-learning algorithms provide considerable benefits for screening candidates with FLD.

The reported prevalence of non-alcoholic fatty liver disease in studies of lean individuals ranges from 7.6% to 19.3%. The aim of the study was to develop machine-learning models for the prediction of fatty liver disease in lean individuals. The present retrospective study included 12,191 lean subjects with a body mass index < 23 kg/m² who had undergone a health checkup from January 2009 to January 2019. Participants were divided into a training (70%, 8533 subjects) and a testing group (30%, 3568 subjects). A total of 27 clinical features were analyzed, except for medical history and history of alcohol or tobacco consumption. Among the 12,191 lean individuals included in the present study, 741 (6.1%) had fatty liver. The machine learning model comprising a two-class neural network using 10 features had the highest area under the receiver operating characteristic curve (AUROC) value (0.885) among all other algorithms. When applied to the testing group, we found the two-class neural network exhibited a slightly higher AUROC value for predicting fatty liver (0.868, 0.841–0.894) compared to the fatty liver index (FLI; 0.852, 0.824–0.81). In conclusion, the two-class neural network had greater predictive value for fatty liver than the FLI in lean individuals.

Hepatitis C virus (HCV) infection can induce insulin resistance, and patients with diabetes mellitus (DM) have a higher prevalence of HCV infection. Patient outcomes improve after HCV eradication in DM patients. However, HCV micro-elimination targeting this population has not been approached. Little is known about using electronic alert systems for HCV screening among patients with DM in a hospital-based setting. We implemented an electronic reminder system for HCV antibody screening and RNA testing in outpatient departments among patients with DM. The screening rates and treatment rates at different departments before and after system implementation were compared. The results indicated that the total HCV screening rate increased from 49.3% (9505/19,272) to 78.2% (15,073/19,272), and the HCV-RNA testing rate increased from 73.4% to 94.2%. The anti-HCV antibody seropositive rate was 5.7%, and the HCV viremia rate was 62.7% in our patient population. The rate of positive anti-HCV antibodies and HCV viremia increased with patient age. This study demonstrates the feasibility and usefulness of an electronic alert system for HCV screening and treatment among DM patients in a hospital-based setting.

The prevalence of inflammatory bowel disease (IBD) has increased worldwide. The prevalence of metabolic dysfunction associated fatty liver disease (MAFLD) has also risen. However, there is limited research on the connection between MAFLD and IBD in the Asian population. This study aims to analyze the prevalence and clinical significance of MAFLD in Taiwanese IBD patients with clinical remission. We retrospectively analyzed IBD patients who received transient elastography for liver fibrosis and controlled attenuation parameter evaluation for liver steatosis. This study enrolled 120 patients with IBD, including 45 Crohn’s disease (CD) and 75 ulcerative colitis (UC). MAFLD prevalence in IBD was 29.2%. Patients with MAFLD had a shorter disease duration (2.8 years vs. 5.3 years, p = 0.017), higher alanine aminotransferase levels (24 U/L vs. 17 U/L, p = 0.003), a lower estimated glomerular filtration rate (91.37 mL/min/1.73 m² vs. 103.92 mL/min/1.73 m², p = 0.004), and higher γ-glutamyl transferase (γ-GT) (24 mg/dL vs. 13 mg/dL, p < 0.001). The prevalence of significant fibrosis in IBD with MAFLD was 17.1%. Significant fibrosis was found in older age (58.5 years vs. 40 years, p = 0.004) and the high type 2 diabetes mellitus proportion (50.0% vs. 10.3%, p = 0.049). A trend of longer disease duration was found in significant fibrosis (4.9 years vs. 1.6 years, p = 0.051). The prevalence of MALFD in IBD was 29.2%. and 17.1% of them had significant fibrosis. In addition to the intestinal manifestation, the study findings remind clinicians that they should be aware of the possibility of hepatic complications for IBD patients.