Development and validation of a machine learning-based model for varices screening in compensated cirrhosis (CHESS2001): an international multicenter study.

BACKGROUND AND AIMS: The prevalence of high-risk varices (HRV) is low among compensated cirrhotic patients undergoing EGD. Our study aimed to identify a novel machine learning (ML)-based model, named ML EGD, for ruling out HRV and avoiding unnecessary EGDs in patients with compensated cirrhosis. METHODS: An international cohort from 17 institutions from China, Singapore, and India were enrolled (CHESS2001). The variables with the top 3 importance scores (liver stiffness, platelet count, and total bilirubin) were selected by the Shapley additive explanation and input into a light gradient-boosting machine algorithm to develop ML EGD for identification of HRV. Furthermore, we built a web-based calculator for ML EGD, which is free with open access (http://www.pan-chess.cn/calculator/MLEGD_score). Unnecessary EGDs that were not performed and the rates of missed HRV were used to assess the efficacy and safety for varices screening. RESULTS: Of 2794 enrolled patients, 1283 patients formed a real-world cohort from 1 university hospital in China used to develop and internally validate the performance of ML EGD for varices screening. They were randomly assigned into the training (n = 1154) and validation (n = 129) cohorts with a ratio of 9:1. In the training cohort, ML EGD spared 607 (52.6%) unnecessary EGDs with a missed HRV rate of 3.6%. In the validation cohort, ML EGD spared 75 (58.1%) EGDs with a missed HRV rate of 1.4%. To externally test the performance of ML EGD, 966 patients from 14 university hospitals in China (test cohort 1) and 545 from 2 hospitals in Singapore and India (test cohort 2) comprised the 2 test cohorts. In test cohort 1, ML EGD spared 506 (52.4%) EGDs with a missed HRV rate of 2.8%. In test cohort 2, ML EGD spared 224 (41.1%) EGDs with a missed HRV rate of 3.1%. When compared with the Baveno VI criteria, ML EGD spared more screening EGDs in all cohorts (training cohort, 52.6% vs 29.4%; validation cohort, 58.1% vs 44.2%; test cohort 1, 52.4% vs 26.5%; test cohort 2, 41.1% vs 21.1%, respectively; P < .001). CONCLUSIONS: We identified a novel model based on liver stiffness, platelet count, and total bilirubin, named ML EGD, as a free web-based calculator. ML EGD could efficiently help rule out HRV and avoid unnecessary EGDs in patients with compensated cirrhosis. (Clinical trial registration number: NCT04307264.).

Safety and immunogenicity of COVID-19 vaccination in patients with non-alcoholic fatty liver disease (CHESS2101): A multicenter study.

BACKGROUND & AIMS: The development of COVID-19 vaccines has progressed with encouraging safety and efficacy data. Concerns have been raised about SARS-CoV-2 vaccine responses in the large population of patients with non-alcoholic fatty liver disease (NAFLD). The study aimed to explore the safety and immunogenicity of COVID-19 vaccination in NAFLD. METHODS: This multicenter study included patients with NAFLD without a history of SARS-CoV-2 infection. All patients were vaccinated with 2 doses of inactivated vaccine against SARS-CoV-2. The primary safety outcome was the incidence of adverse reactions within 7 days after each injection and overall incidence of adverse reactions within 28 days, and the primary immunogenicity outcome was neutralizing antibody response at least 14 days after the whole-course vaccination. RESULTS: A total of 381 patients with pre-existing NAFLD were included from 11 designated centers in China. The median age was 39.0 years (IQR 33.0-48.0 years) and 179 (47.0%) were male. The median BMI was 26.1 kg/m2 (IQR 23.8-28.1 kg/m2). The number of adverse reactions within 7 days after each injection and adverse reactions within 28 days totaled 95 (24.9%) and 112 (29.4%), respectively. The most common adverse reactions were injection site pain in 70 (18.4%), followed by muscle pain in 21 (5.5%), and headache in 20 (5.2%). All adverse reactions were mild and self-limiting, and no grade 3 adverse reactions were recorded. Notably, neutralizing antibodies against SARS-CoV-2 were detected in 364 (95.5%) patients with NAFLD. The median neutralizing antibody titer was 32 (IQR 8-64), and the neutralizing antibody titers were maintained. CONCLUSIONS: The inactivated COVID-19 vaccine appears to be safe with good immunogenicity in patients with NAFLD. LAY SUMMARY: The development of vaccines against coronavirus disease 2019 (COVID-19) has progressed rapidly, with encouraging safety and efficacy data. This study now shows that the inactivated COVID-19 vaccine appears to be safe with good immunogenicity in the large population of patients with non-alcoholic fatty liver disease.

Combination of physical activity and screen time on life satisfaction in adults: A cross-sectional survey.

Background: Sufficient physical activity (PA) and limited screen time (ST) have been shown to be positively associated with a variety of mental health outcomes. It has been known that PA and ST are independently associated with life satisfaction. Whereas, little is known about the association between combinations of PA and ST with life satisfaction in adults. This study aimed to explore the associations between PA and ST (in insolation or combination) and life satisfaction in adults. Methods: Data from the 2014 European Social Survey (ESS) round 7 consisting of 22 countries were analyzed in this study. In total, self-reported data from 40,185 adults were included in the final analysis. The self-administered method was used to collect demographic information, PA, ST, and life satisfaction. The prevalence of meeting PA guidelines (at least 150 min per week) and ST guidelines (no more than 3 h per day) was calculated according to Canadian 24-h Movement Guidelines for Adults. Results: Adults who were engaged in sufficient PA and limited ST were more likely to report a higher level of life satisfaction. Meeting PA or ST guidelines was more likely to report higher life satisfaction scores [odds ratio (OR) = 1.31, 95% CI: 1.16-1.47]. Compared with not meeting any guidelines, those who met both PA and ST guidelines had a higher OR (OR = 1.55, 95% CI: 1.37-1.76). Conclusion: This study found that participating PA while limiting ST concurrently was linked with better life satisfaction. Creating an active lifestyle is important to population's well-being.

The Effect of Subjective Exercise Experience on Exercise Behavior and Amount of Exercise in Children and Adolescents: The Mediating Effect of Exercise Commitment.

PURPOSE: To explore the influencing factors that restrict the exercise behavior of children and adolescents, investigate the effect of subjective exercise experience on exercise behavior, and reveal the mediating effect of exercise commitment between subjective exercise experience and exercise behavior so as to promote children and adolescents to maintain good health exercise habits and improve their physical and mental health. METHODS: The Subjective Exercise Experience Scale (SEES), Exercise Commitment Scale (ECC), and Physical Exercise Rating Scale (PARS-3) were used to conduct a questionnaire survey on 600 children and adolescents in Chongqing, China, and SPSS21.0 and AMOS21.0 statistical analysis software was used to carry out statistics and analyses on the questionnaires. RESULTS: (1) Among children and adolescents, boys' exercise commitment and exercise behavior were significantly higher than girls', and there was no significant gender difference in subjective exercise experience. The exercise behavior of children and adolescents aged 9-12 was significantly higher than that of children and adolescents aged 13-15, and there was no significant age difference in subjective exercise experience and exercise commitment. (2) There was a significant correlation between the subjective exercise experience, exercise commitment, and exercise behavior of children and adolescents, and subjective exercise experience could directly and positively predict exercise commitment (ß = 0.63) and exercise behavior (ß = 0.57)-exercise commitment could also directly and positively predict exercise behavior (ß = 0.52). (3) The exercise commitment of children and adolescents has a partial mediating effect between subjective exercise experience and exercise behavior (accounting for 37.50% of the total effect), and has a mediating effect between different exercise amounts, with the strongest mediating effect being on high exercise amount (32.10% of the total effect). CONCLUSIONS: The exercise behavior of children and adolescents was not only directly affected by subjective exercise experience, but also affected by the mediating effect of exercise commitment, and maintaining a good exercise experience and commitment was an effective way to effectively improve exercise behavior and amount of exercise in children and adolescents.

The Combinations of Physical Activity, Screen Time, and Sleep, and Their Associations with Self-Reported Physical Fitness in Children and Adolescents.

Much evidence has indicated that adherence to the 24 h movement guidelines (physical activity, screen time and sleep) is associated with physical health, while little is known about the adherence to the 24 h movement guidelines and self-reported physical fitness in adolescents. This study, therefore, aims to explore the association between the 24 h movement guidelines (in isolation or combination) and self-reported physical fitness in a sample of Chinese adolescents in an age range of 10-17. METHODS: A convenient sample of 3807 children and adolescents from 12 schools was adopted in the present study. A questionnaire based on the Health Behaviour in School-aged Children was used to assess physical activity and screen time, and the Pittsburgh Sleep Scale was utilized to measure sleep duration. The International Fitness Scale was used to assess physical fitness in study participants. Ordinal logistic regression was performed to estimate the association between adherence to the 24 h movement guidelines and self-reported physical fitness. RESULTS: Of all study participants, 0.9% of them met the 24 h movement guidelines, and meeting the guidelines was significantly associated with higher levels of self-reported physical fitness. The analysis for the association between specific combinations of 24 h movement guidelines and self-reported physical fitness underscored the importance of meeting the physical activity recommendations. CONCLUSION: Adherence to more recommendations contained in the 24 h movement guidelines was associated with higher self-reported physical fitness, especially cardiorespiratory fitness and muscular strength. Our study also stressed the importance of promoting moderate to vigorous physical activity in children and adolescents. Further works should focus on the association of a recommendation of adherence with other health indicators and replicate this study on larger samples among Chinese children and adolescents. Additionally, longitudinal or interventional studies that include more socio-demographic factors are needed to explore the association between 24 h movement guidelines and self-reported physical fitness, and the 24 h movement guidelines also should be promoted on a large scale in Chinese children and adolescents. Moreover, it is also needed to gain better insights into the directionality of the relationship between compliance with 24 h movement guidelines and self-reported physical fitness, as well as the mechanisms underlying the associations in Chinese children and adolescents.

Data Mining Algorithm for Physical Health Monitoring of Young Students Based on Big Data.

With the continuous improvement of living standards, the level of physical development of adolescents has improved significantly. The physical functions and healthy development of adolescents are relatively slow and even appear to decline. This paper proposes a novel data mining algorithm based on big data for monitoring of adolescent student's physical health to overcome this problem and enhance young people's physical fitness and mental health. Since big data technology has positive practical significance in promoting young people's healthy development and promoting individual health rights, this article will implement commonly used data mining algorithms and Hadoop/Spark big data processing. The algorithm on different platforms verified that the big data platform has good computing performance for the data mining algorithm by comparing the running time. The current work will prove to be a complete physical health data management system and effectively save, process, and analyze adolescents' physical test data.