BACKGROUND: Metabolic-associated fatty liver disease (MAFLD) is a common liver disease and may become the leading cause of severe liver disease in the future. The Global Burden of Disease (GBD) study assesses MAFLD's impact in countries and regions worldwide, providing insights into its prevalence. METHODS: Prevalence data for MAFLD from 1990 to 2021 by country and region in all sex and age groups were collected from the Global Health Data Exchange. The categorization of countries and geographic areas by development was performed using the Sociodemographic Index (SDI). RESULTS: Between 1990 and 2021, the global crude prevalence rate of MAFLD increased from 10.6% to 16.1% (beta-coefficient: 0.2%, 95% confidence interval [CI]: 0.2-0.2%, P  <0.001), and the age-standardized prevalence rate was increased from 12.1% to 15.0% (beta-coefficient: 0.1%, 95% CI: 0.1-0.1%, P  <0.001). In 2021, MAFLD was estimated to have affected 1.3 billion people worldwide. Significant uptrends were observed in all regions, super regions, and SDI categories. The fastest increase from 1990 to 2021 and the highest prevalence rate in 2021 were experienced by countries and territories with high-middle and middle SDI. An increase in the prevalence of MAFLD from 1990 to 2021 was demonstrated in all but six countries. CONCLUSIONS In 2021, the number of patients affected by MAFLD was doubled compared to 1990, and the prevalence rate increased by over 50%. The burden of MAFLD, as measured by prevalence, was more prominent in countries and territories with middle SDI and in those located in North African and Middle Eastern, possibly due to changes in lifestyle in these areas over the past 30 years.
Humans ; Global Burden of Disease ; Prevalence ; Male ; Female ; Middle Aged ; Adult ; Global Health ; Fatty Liver/epidemiology* ; Aged

Objective: To explore the facilitating and hindering factors of mental health promotion activities in junior and senior high schools from teachers perspectives, as well as coping strategies, so as to provide evidence for implementing teacher led mental health promotion programs. Methods: From September 2023 to September 2024, by using purposive sampling method, 5 junior high schools, 5 regular high schools, 2 vocational high schools in four provinces and municipalities (Tianjin, Shanxi, Shandong, and Jiangxi) were selected. A total of 92 teachers (78 homeroom teachers and 14 full time or part time psychological counselors) were interviewed using semi structured focus group discussions (one session per school, totaling 12 sessions). Thematic analysis was applied to code and analyze the interview transcripts. Results: The implementation of mental health promotion activities in middle schools was influenced by three levels: teachers, schools and society. Specifically, teachers exhibited a high support low capability phenomenon (81 participants supported conducting such activities, but 71 felt lacking in professional capacity); activity effectiveness and support systems were imbalanced (42 mentioned significant effects, while 78 reported insufficient support); there was a mismatch between student demand and activity content (9 mentioned students had psychological needs, but 11 indicated existing activities failed to meet these needs); administrative support and sustainability showed disparities (14 believed sufficient administrative support existed, while 37 noted sustainability issues); parental awareness and participation remained inadequate (11 highlighted parents need for mental health knowledge, and 37 perceived insufficient understanding of psychological issues among parents). Effective strategies included enhancing teachers effectiveness, providing essential skill training, focusing on the needs of teenagers,enhancing program sustainability, and eliminating misconceptions about mental health among parents. Conclusion Mental health promotion activities in junior and senior high schools should focus on enhancing teachers skills, improving activity sustainability, reducing stigma among parents, and establishing a collaborative network for school based mental health promotion.

Objective:To construct and validate an artificial intelligence diagnostic system based on multi-feature integration for diagnosing gastric whitish neoplastic lesions under white-light endoscopy.Methods:Gastroscopic images from Renmin Hospital of Wuhan University and the Seventh Medical Center of Chinese PLA General Hospital were collected from November 2012 to July 2021. A total of 823 images of gastric whitish lesions from 267 patients were finally selected. Five white-light endoscopic features associated with gastric whitish lesions were selected through a literature search, including lesion location, boundary clarity, surface texture, roundness, and depression status. Images with manually annotated features were used to train machine learning models, with the optimal model selected as the multi-feature fitting diagnostic system, which assigned diagnostic weights to each feature. A conventional deep learning model was trained with the same dataset. The diagnostic performance of the two models were compared, and eight endoscopists of varying expertise were invited to participate in human-machine comparisons.Results:Accuracy, sensitivity, and specificity of the multi-feature fitting diagnostic system were 82.11% (101/123), 78.43% (40/51), and 84.72% (61/72), respectively. Feature weights in descending order were depression (0.71), lesion location (0.11), surface roughness (0.08), boundary clarity (0.06), and subcircular shape (0.04). The diagnostic accuracy of the system was significantly higher than that of non-expert endoscopists (82.11% VS 74.31%, Z=-2.785, P=0.008) and comparable to that of expert endoscopists (82.11% VS 83.20%, Z=-0.696, P=0.700). There was no significant difference in accuracy between the multi-feature fitting diagnostic system and the traditional deep learning model [82.11% (101/123) VS 82.93% (102/123), P=1.000]. Conclusion:The feature-weighted artificial intelligence diagnostic system for gastric whitish neoplastic lesions demonstrates clinically relevant diagnostic accuracy under white-light endoscopy.

Objective:To analyze the application of Sengstaken-Blakemore tubes combined with endoscopic intervention on the prognosis of patients with acute esophageal and gastric variceal rupture and bleeding due to portal hypertension in liver cirrhosis, and to explore the impact of Sengstaken-Blakemore tubes combined with endoscopic intervention on the prognosis of patients.Methods:A retrospective study included patients with liver cirrhosis who visited the Zhongshan Hospital, Fudan University from January 2023 to July 2024 due to acute upper gastrointestinal bleeding, had no response to drug treatment and unstable hemodynamics, and received the Sengstaken-Blakemore tubes compression hemostasis. According to whether endoscopic intervention was received or not, the patients were divided into the endoscopic intervention group and the non-endoscopic intervention group. The medication and subsequent treatment of the patients were analyzed, and the survival of the patients 28 days after bleeding was followed up. Kaplan-Meier survival analysis and Cox regression analysis were used to evaluate the effect of endoscopic intervention on the 28-day mortality rate of patients.Results:A total of 31 cases successfully had three-lumen two-cystic tubes indwelled. Among them, 8 cases further received endoscopic examination and intervention, and 23 cases did not receive endoscopic examination. During the 28-day follow-up after bleeding, a total of 20 cases died. The Kaplan-Meier survival analysis showed that the 28-day mortality rate in the endoscopic intervention group was significantly lower than that in the non-endoscopic intervention group (25.0% vs 78.3%, P=0.007). Multivariate Cox regression analysis showed that endoscopic intervention was an independent protective factor for 28-day mortality ( HR: 0.14, 95% CI: 0.03-0.63, P=0.01). In addition, the severity of bleeding and prothrombin time were also important factors affecting the prognosis of patients. Conclusions:The Sengstaken-Blakemore tubes, as an important hemostasis method for acute esophageal and gastric variceal rupture and bleeding, can buy time for subsequent endoscopic treatment, but the risk of complications is relatively high. Creating conditions for early endoscopic intervention as early as possible can significantly reduce the mortality rate of patients and improve the prognosis of patients with liver cirrhosis.

Portal hypertension, as a clinical manifestation of the progression of various liver diseases, its concurrent rupture and bleeding of esophageal and gastric varices, ascites and hepatic encephalopathy, etc., seriously affect the prognosis of patients and have always been a key concern in clinical diagnosis and treatment. Although traditional imaging techniques play a key role in the diagnosis and evaluation of portal hypertension, their diagnostic efficacy is limited by subjective film reading, making it difficult to accurately quantify and deeply analyze the pathophysiological characteristics. In recent years, radiomics has gradually demonstrated its potential in the diagnosis and management of portal hypertension by extracting a large number of quantitative features from medical images and constructing predictive models in combination with artificial intelligence algorithms such as machine learning. This article systematically reviews the research progress of radiomics in portal hypertension, with a focus on discussing the current application status of radiomics characteristics in risk assessment, hemodynamic analysis, and prognosis prediction of portal hypertension, in order to promote the progress of radiomics from technical verification to clinical transformation.

Objective:To analyze the application of Sengstaken-Blakemore tubes combined with endoscopic intervention on the prognosis of patients with acute esophageal and gastric variceal rupture and bleeding due to portal hypertension in liver cirrhosis, and to explore the impact of Sengstaken-Blakemore tubes combined with endoscopic intervention on the prognosis of patients.Methods:A retrospective study included patients with liver cirrhosis who visited the Zhongshan Hospital, Fudan University from January 2023 to July 2024 due to acute upper gastrointestinal bleeding, had no response to drug treatment and unstable hemodynamics, and received the Sengstaken-Blakemore tubes compression hemostasis. According to whether endoscopic intervention was received or not, the patients were divided into the endoscopic intervention group and the non-endoscopic intervention group. The medication and subsequent treatment of the patients were analyzed, and the survival of the patients 28 days after bleeding was followed up. Kaplan-Meier survival analysis and Cox regression analysis were used to evaluate the effect of endoscopic intervention on the 28-day mortality rate of patients.Results:A total of 31 cases successfully had three-lumen two-cystic tubes indwelled. Among them, 8 cases further received endoscopic examination and intervention, and 23 cases did not receive endoscopic examination. During the 28-day follow-up after bleeding, a total of 20 cases died. The Kaplan-Meier survival analysis showed that the 28-day mortality rate in the endoscopic intervention group was significantly lower than that in the non-endoscopic intervention group (25.0% vs 78.3%, P=0.007). Multivariate Cox regression analysis showed that endoscopic intervention was an independent protective factor for 28-day mortality ( HR: 0.14, 95% CI: 0.03-0.63, P=0.01). In addition, the severity of bleeding and prothrombin time were also important factors affecting the prognosis of patients. Conclusions:The Sengstaken-Blakemore tubes, as an important hemostasis method for acute esophageal and gastric variceal rupture and bleeding, can buy time for subsequent endoscopic treatment, but the risk of complications is relatively high. Creating conditions for early endoscopic intervention as early as possible can significantly reduce the mortality rate of patients and improve the prognosis of patients with liver cirrhosis.

Portal hypertension, as a clinical manifestation of the progression of various liver diseases, its concurrent rupture and bleeding of esophageal and gastric varices, ascites and hepatic encephalopathy, etc., seriously affect the prognosis of patients and have always been a key concern in clinical diagnosis and treatment. Although traditional imaging techniques play a key role in the diagnosis and evaluation of portal hypertension, their diagnostic efficacy is limited by subjective film reading, making it difficult to accurately quantify and deeply analyze the pathophysiological characteristics. In recent years, radiomics has gradually demonstrated its potential in the diagnosis and management of portal hypertension by extracting a large number of quantitative features from medical images and constructing predictive models in combination with artificial intelligence algorithms such as machine learning. This article systematically reviews the research progress of radiomics in portal hypertension, with a focus on discussing the current application status of radiomics characteristics in risk assessment, hemodynamic analysis, and prognosis prediction of portal hypertension, in order to promote the progress of radiomics from technical verification to clinical transformation.

Objective:To construct and validate an artificial intelligence diagnostic system based on multi-feature integration for diagnosing gastric whitish neoplastic lesions under white-light endoscopy.Methods:Gastroscopic images from Renmin Hospital of Wuhan University and the Seventh Medical Center of Chinese PLA General Hospital were collected from November 2012 to July 2021. A total of 823 images of gastric whitish lesions from 267 patients were finally selected. Five white-light endoscopic features associated with gastric whitish lesions were selected through a literature search, including lesion location, boundary clarity, surface texture, roundness, and depression status. Images with manually annotated features were used to train machine learning models, with the optimal model selected as the multi-feature fitting diagnostic system, which assigned diagnostic weights to each feature. A conventional deep learning model was trained with the same dataset. The diagnostic performance of the two models were compared, and eight endoscopists of varying expertise were invited to participate in human-machine comparisons.Results:Accuracy, sensitivity, and specificity of the multi-feature fitting diagnostic system were 82.11% (101/123), 78.43% (40/51), and 84.72% (61/72), respectively. Feature weights in descending order were depression (0.71), lesion location (0.11), surface roughness (0.08), boundary clarity (0.06), and subcircular shape (0.04). The diagnostic accuracy of the system was significantly higher than that of non-expert endoscopists (82.11% VS 74.31%, Z=-2.785, P=0.008) and comparable to that of expert endoscopists (82.11% VS 83.20%, Z=-0.696, P=0.700). There was no significant difference in accuracy between the multi-feature fitting diagnostic system and the traditional deep learning model [82.11% (101/123) VS 82.93% (102/123), P=1.000]. Conclusion:The feature-weighted artificial intelligence diagnostic system for gastric whitish neoplastic lesions demonstrates clinically relevant diagnostic accuracy under white-light endoscopy.

Objective:To explore the changes of iron metabolism in patients with hepatitis B cirrhosis and esophageal and gastric varices complicated with portal vein thrombosis.Methods:This study was a cross-sectional study. 253 patients with hepatitis B cirrhosis with esophageal and gastric varices who were hospitalized in the Zhongshan Hospital, Fudan University from January 1, 2020 to December 31, 2021 were included in this study. They were divided into portal vein thrombosis group ( n=57) and non portal vein thrombosis group ( n=196) according to the presence or absence of portal vein thrombosis. The iron metabolism characteristics of the two groups were compared, and subgroups were analyzed according to the presence or absence of ascites, platelet count level, D-dimer level, and Child grade. The factors related to portal vein thrombosis were screened through multivariate logistic regression analysis. Results:The ratio of Child pugh B/C, ascites, D-dimer and platelet count in patients with hepatitis B cirrhosis and esophageal and gastric varices complicated with portal vein thrombosis was higher (all P<0.05). Patients with portal vein thrombosis had higher levels of soluble transferrin receptor [2.4(1.8, 3.6)mg/L vs 1.8(1.3, 2.7)mg/L, P=0.006], and lower levels of ferritin [33.1(18.9, 63.3)ng/ml vs 57.7(19.4, 142.5)ng/ml, P=0.038]. Layered analysis showed that ascites, platelet count levels, D-dimer levels, and Child-pugh grade did not affect the negative correlation trend between ferritin and portal vein thrombosis, and the positive correlation trend between soluble transferrin receptors and portal vein thrombosis. Moreover, soluble transferrin receptors showed a statistically significant positive correlation with portal vein thrombosis in the absence of ascites, low D-dimer levels, and Child-pugh grade A. Multivariate analysis suggested that after weighing Child-pugh grading, platelet count, and D-dimer levels, ferritin ( OR=0.943, 95% CI: 0.904-0.983, P=0.006) and soluble transferrin receptor ( OR=1.034, 95% CI: 0.001-1.067, P=0.044) were independently associated with portal vein thrombosis. Conclusions:In patients with hepatitis B cirrhosis with esophageal and gastric varices, the characteristics of iron metabolism in patients with portal vein thrombosis are different from those in patients without thrombosis, with higher levels of soluble transferrin receptor and lower levels of ferritin.

Objective:To construct an intelligent endoscopic image analysis system that could monitor the blind spot of the upper gastrointestinal tract, and to test its performance.Methods:A total of 87 167 upper gastrointestinal endoscopy images (dataset 1) including 75 551 for training and 11 616 for testing, and a total of 2 414 pharyngeal images (dataset 2) including 2 233 for training and 181 for testing were retrospectively collected from the Digestive Endoscopy Center of Renmin Hospital of Wuhan University between 2016 to 2020. A 27-category-classification model for blind spot monitoring in the upper gastrointestinal tract (model 1, which distinguished 27 anatomical sites such as the pharynx, esophagus, and stomach) and a 5-category-classification model for blind spot monitoring in the pharynx (model 2, which distinguished palate, posterior pharyngeal wall, larynx, left and right pyriform sinuses) were constructed. The above models were trained and tested based on dataset 1 and 2, respectively, and trained based on the EfficientNet-B4, ResNet50 and VGG16 models of the keras framework. Thirty complete upper gastrointestinal endoscopy videos were retrospectively collected from the Digestive Endoscopy Center of Renmin Hospital of Wuhan University in 2021 to test model 2 blind spot monitoring performance.Results:The cross-sectional comparison results of the accuracy of model 1 in identifying 27 anatomical sites of the upper gastrointestinal tract in images showed that the mean accuracy of EfficientNet-B4, ResNet50, and VGG16 were 90.90%, 90.24%, and 89.22%, respectively, with the EfficientNet-B4 model performance the best, and the accuracy of EfficientNet-B4 model for each site ranged from 80.49% to 97.80%. The cross-sectional comparison results of the accuracy of model 2 in identifying the 5 anatomical sites of the pharynx in the images showed that the mean accuracy of EfficientNet-B4, ResNet50, and VGG16 were 99.40%, 98.56%, and 97.01%, respectively, in which the EfficientNet-B4 model had the best performance, and the accuracy of EfficientNet-B4 model for each site ranged from 96.15% to 100.00%. The overall accuracy of model 2 in identifying the 5 anatomical sites of the pharynx in the video was 97.33% (146/150).Conclusion:The intelligent endoscopic image analysis system based on deep learning can monitor blind spots in the upper gastrointestinal tract, coupled with pharyngeal blind spot monitoring and esophagogastroduodenal blind spot monitoring functions. The system shows high accuracy in both images and videos, which is expected to have a potential role in clinical practice and assisting endoscopists to achieve full observation of the upper gastrointestinal tract.