scholarly journals Current and Next Visit Prediction for Fatty Liver Disease with a Large-Scale Dataset: Model Development and Performance Comparison (Preprint)

10.2196/26398 ◽  
2020 ◽  
Author(s):  
ChengTse Wu ◽  
Ta-Wei Chu ◽  
Jyh-Shing Roger Jang
Keyword(s):  
Liver Disease ◽  
Fatty Liver ◽  
Fatty Liver Disease ◽  
Large Scale ◽  
Model Development ◽  
Performance Comparison ◽  
Large Scale Dataset ◽  
And Performance

scholarly journals Inverse Association between Hepatitis B Virus Infection and Fatty Liver Disease: A Large-Scale Study in Populations Seeking for Check-Up

PLoS ONE ◽  
2013 ◽  
Vol 8 (8) ◽  
pp. e72049 ◽  
Author(s):  
Yuan-Lung Cheng ◽  
Yuan-Jen Wang ◽  
Wei-Yu Kao ◽  
Ping-Hsien Chen ◽  
Teh-Ia Huo ◽  
...  
Keyword(s):  
Liver Disease ◽  
Hepatitis B Virus ◽  
Virus Infection ◽  
Hepatitis B ◽  
Fatty Liver ◽  
Fatty Liver Disease ◽  
Large Scale ◽  
Inverse Association ◽  
Hepatitis B Virus Infection ◽  
B Virus

scholarly journals Pediatric Fatty Liver and Obesity: Not Always Justa Matter of Non-Alcoholic Fatty Liver Disease

Children ◽  
2018 ◽  
Vol 5 (12) ◽  
pp. 169
Author(s):  
Renata Alfani ◽  
Edoardo Vassallo ◽  
Anna De Anseris ◽  
Lucia Nazzaro ◽  
Ida D'Acunzo ◽  
...  
Keyword(s):  
Liver Disease ◽  
Fatty Liver ◽  
Fatty Liver Disease ◽  
Large Scale ◽  
Correct Diagnosis ◽  
Diagnostic Algorithm ◽  
Liver Imaging ◽  
Dietary Counseling ◽  
Alcoholic Fatty Liver ◽  
Alcoholic Fatty Liver Disease

Obesity-related non-alcoholic fatty liver disease (NAFLD) represents the most common cause of pediatric liver disease due to overweight/obesity large-scale epidemics. In clinical practice, diagnosis is usually based on clinical features, blood tests, and liver imaging. Here, we underline the need to make a correct differential diagnosis for a number of genetic, metabolic, gastrointestinal, nutritional, endocrine, muscular, and systemic disorders, and for iatrogenic/viral/autoimmune hepatitis as well. This is all the more important for patients who are not in the NAFLD classical age range and for those for whom a satisfactory response of liver test abnormalities to weight loss after dietary counseling and physical activity measures cannot be obtained or verified due to poor compliance. A correct diagnosis may be life-saving, as some of these conditions which appear similar to NAFLD have a specific therapy. In this study, the characteristics of the main conditions which require consideration are summarized, and a practical diagnostic algorithm is discussed.

scholarly journals Hepatic Unsaturated Fatty Acids Are Linked to Lower Degree of Fibrosis in Non-alcoholic Fatty Liver Disease

2022 ◽  
Vol 8 ◽  
Author(s):  
Michael Fridén ◽  
Fredrik Rosqvist ◽  
Håkan Ahlström ◽  
Heiko G. Niessen ◽  
Christian Schultheis ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Liver Disease ◽  
Liver Fibrosis ◽  
Fatty Liver ◽  
Fatty Liver Disease ◽  
Large Scale ◽  
Unsaturated Fatty Acids ◽  
Vaccenic Acid ◽  
Alcoholic Fatty Liver ◽  
Alcoholic Fatty Liver Disease

Background: The hepatic lipidome of patients with early stages of non-alcoholic fatty liver disease (NAFLD) has been fairly well-explored. However, studies on more progressive forms of NAFLD, i.e., liver fibrosis, are limited.Materials and methods: Liver fatty acids were determined in cholesteryl esters (CE), phospholipids (PL), and triacylglycerols (TAG) by gas chromatography. Cross-sectional associations between fatty acids and biopsy-proven NAFLD fibrosis (n = 60) were assessed using multivariable logistic regression models. Stages of fibrosis were dichotomized into none-mild (F0–1) or significant fibrosis (F2–4). Models were adjusted for body-mass index (BMI), age and patatin-like phospholipase domain-containing protein 3 (PNPLA3 rs738409) (I148M) genotype. A secondary analysis examined whether associations from the primary analysis could be confirmed in the corresponding plasma lipid fractions.Results: PL behenic acid (22:0) was directly associated [OR (95% CI): 1.86 (1.00, 3.45)] whereas PL docosahexaenoic acid (22:6n-3) [OR (95% CI): 0.45 (0.23, 0.89)], TAG oleic acid (18:1n-9) [OR (95% CI): 0.52 (0.28, 0.95)] and 18:1n-9 and vaccenic acid (18:1n-7) (18:1) [OR (95% CI): 0.52 (0.28, 0.96)] were inversely associated with liver fibrosis. In plasma, TAG 18:1n-9 [OR (95% CI): 0.55 (0.31, 0.99)], TAG 18:1 [OR (95% CI): 0.54 (0.30, 0.97)] and PL 22:0 [OR (95% CI): 0.46 (0.25, 0.86)] were inversely associated with liver fibrosis.Conclusion: Higher TAG 18:1n-9 levels were linked to lower fibrosis in both liver and plasma, possibly reflecting an altered fatty acid metabolism. Whether PL 22:6n-3 has a protective role, together with a potentially adverse effect of hepatic 22:0, on liver fibrosis warrants large-scale studies.

scholarly journals Current and Next Visit Prediction for Fatty Liver Disease with a Large-Scale Dataset (Preprint)

2020 ◽  
Author(s):  
ChengTse Wu ◽  
Ta-Wei Chu ◽  
Jyh-Shing Roger Jang
Keyword(s):  
Feature Selection ◽  
Liver Disease ◽  
Fatty Liver ◽  
Fatty Liver Disease ◽  
Large Scale ◽  
Prediction Models ◽  
Short Term Memory ◽  
Support Vector ◽  
Test Accuracy ◽  
Forward Selection

BACKGROUND Fatty liver disease (FLD) arises from the accumulation of fat in the liver and may cause liver inflammation which, according to past research it is shown that if not actively well-controlled, may develop into liver fibrosis, cirrhosis, or even hepatocellular carcinoma in the future. OBJECTIVE We describe the construction of machine-learning models for current-visit prediction (CVP) which can help physicians obtain more information for accurate diagnosis, and next-visit prediction (NVP) which can help physicians deal provide potential high-risk patients with advice to effectively prevent or delay health deterioration. METHODS The large-scale and high-dimensional dataset used in this study comes from the MJ Health Research Foundation in Taipei. The models we created use sequence forward selection (SFS) and one-pass ranking (OPR) for feature selection. For current-visit prediction (CVP), we explored multiple models including Adaboost, support vector machine (SVM), logistic regression (LR), random forest (RF), Gaussian Naïve Bayes (GNB), decision trees C4.5 (C4.5), and classification & regression trees (CART). For next-visit prediction (NVP), we used long short-term memory (LSTM) as a sequence classifier that uses various input sets for prediction. Model performance is evaluated based on two criteria: the accuracy of the test set, and the IoU and coverage between the features selected by OPR/SFS and by domain experts. RESULTS The dataset respectively includes 34,856 and 31,394 unique visits by male and female patients during 2009∼2016. The test accuracy results of CVP for Adaboost, SVM, LR, RF, GNB, C4.5, and CART were respectively 84.28, 83.84, 82.22, 82.21, 76.03, 75.78, and 75.53%. The test accuracy results of NVP of LSTM with fixed and variable intervals were respectively 78.20% and 76.79%. The proposed two paradigms of LSTM respectively achieved 39.29% and 41.21% error reduction when compared with a baseline model of simple induction. CONCLUSIONS This study explores a large fatty liver disease (FLD) dataset with high dimensionality. We have developed prediction models that can use for CVP and NVP for FLD prediction. We have also implemented efficient feature selection schemes for CVP and NVP to compare the automatically selected features with expert-selected features.

Association between consumption frequency of honey and non-alcoholic fatty liver disease: results from a cross-sectional analysis based on the Tianjin Chronic Low-grade Systemic Inflammation and Health (TCLSIH) Cohort Study

2020 ◽  
pp. 1-9 ◽  
Author(s):  
Shunming Zhang ◽  
Xiaohui Wu ◽  
Shanshan Bian ◽  
Qing Zhang ◽  
Li Liu ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Liver Disease ◽  
Fatty Liver ◽  
Fatty Liver Disease ◽  
Large Scale ◽  
Cross Sectional ◽  
Alcoholic Fatty Liver ◽  
The Metabolic Syndrome ◽  
Consumption Frequency ◽  
Alcoholic Fatty Liver Disease

Abstract Non-alcoholic fatty liver disease (NAFLD) is the hepatic manifestation of the metabolic syndrome. Recent evidence has suggested the protective effects of honey consumption against the metabolic syndrome, but the association between honey intake and NAFLD is still unclear. We investigated how the consumption frequency of honey was associated with NAFLD in the general population. This was a cross-sectional study of 21 979 adults aged 20–90 years. NAFLD was diagnosed based on the ultrasound-diagnosed fatty liver without significant alcohol intake and other liver diseases. Diet information, including consumption frequency of honey, was assessed by a validated 100-item FFQ. OR with 95 % CI were calculated by the binary logistic regression model, adjusting for confounding factors identified by the directed acyclic graph. Overall, 6513 adults (29·6 %) had NAFLD. Compared with participants consuming ≤1 time/week of honey, the multivariable OR of NAFLD were 0·86 (95 % CI 0·77, 0·97) for 2–6 times/week and 1·10 (95 % CI 0·95, 1·27) for ≥1 times/d (Pfor trend = 0·90). The results were generally similar in subgroups of BMI at a cut-point of 24·0 kg/m2 (Pfor interaction = 0·10). In this large-scale study, consuming honey 2–6 times/week was inversely associated with NAFLD, whereas consuming honey ≥1 times/d had no association with NAFLD. These results need replication in other large-scale prospective studies.

scholarly journals Potential Regulators Driving the Transition in Nonalcoholic Fatty Liver Disease: a Stage-Based View

2017 ◽  
Vol 41 (1) ◽  
pp. 239-251 ◽  
Author(s):  
Yi Lou ◽  
Yi-Dan Chen ◽  
Fu-Rong Sun ◽  
Jun-Ping Shi ◽  
Yu Song ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Liver Disease ◽  
Fatty Liver ◽  
Nonalcoholic Fatty Liver Disease ◽  
Regulatory Network ◽  
Fatty Liver Disease ◽  
Large Scale ◽  
Functional Organization ◽  
Transcriptional Regulators ◽  
Nonalcoholic Fatty Liver

Background and Aim: The incidence of nonalcoholic fatty liver disease (NAFLD), ranging from mild steatosis to hepatocellular injury and inflammation, increases with the rise of obesity. However, the implications of transcription factors network in progressive NAFLD remain to be determined. Methods: A co-regulatory network approach by combining gene expression and transcription influence was utilized to dissect transcriptional regulators in different NAFLD stages. In vivo, mice models of NAFLD were used to investigate whether dysregulated expression be undertaken by transcriptional regulators. Results: Through constructing a large-scale co-regulatory network, sample-specific regulator activity was estimated. The combinations of active regulators that drive the progression of NAFLD were identified. Next, top regulators in each stage of NAFLD were determined, and the results were validated using the different experiments and bariatric surgical samples. In particular, Adipocyte enhancer-binding protein 1 (AEBP1) showed increased transcription activity in nonalcoholic steatohepatitis (NASH). Further characterization of the AEBP1 related transcription program defined its co-regulators, targeted genes, and functional organization. The dynamics of AEBP1 and its potential targets were verified in an animal model of NAFLD. Conclusions: This study identifies putative functions for several transcription factors in the pathogenesis of NAFLD and may thus point to potential targets for therapeutic interventions.

scholarly journals Body weight variability and the risk of cardiovascular outcomes in patients with nonalcoholic fatty liver disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mi Na Kim ◽  
Kyungdo Han ◽  
Juhwan Yoo ◽  
Yeonjung Ha ◽  
Young Eun Chon ◽  
...  
Keyword(s):  
Body Weight ◽  
Liver Disease ◽  
Fatty Liver ◽  
Nonalcoholic Fatty Liver Disease ◽  
Fatty Liver Disease ◽  
Large Scale ◽  
Health Examination ◽  
Nonalcoholic Fatty Liver ◽  
Increased Risk ◽  
All Cause Mortality

AbstractWe investigated the association between body weight variability and the risks of cardiovascular disease and mortality in patients with nonalcoholic fatty liver disease (NAFLD) using large-scale, nationwide cohort data. We included 726,736 individuals with NAFLD who underwent a health examination between 2009 and 2010. NAFLD was defined as a fatty liver index ≥ 60, after excluding significant alcohol intake, viral hepatitis, and liver cirrhosis. Body weight variability was assessed using four indices, including variability independent of the mean (VIM). During a median 8.1-year follow-up, we documented 11,358, 14,714, and 22,164 cases of myocardial infarction (MI), stroke, and all-cause mortality, respectively. Body weight variability was associated with an increased risk of MI, stroke, and mortality after adjusting for confounding variables. The hazard ratios (HRs) (95% confidence intervals) for the highest quartile, compared with the lowest quartile, of VIM for body weight were 1.15 (1.10–1.20), 1.22 (1.18–1.26), and 1.56 (1.53–1.62) for MI, stroke, and all-cause mortality, respectively. Body weight variability was associated with increased risks of MI, stroke, and all-cause mortality in NAFLD patients. Appropriate interventions to maintain a stable weight could positively affect health outcomes in NAFLD patients.

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