Fasting plasma glucose (FPG) is an easily quantifiable and inexpensive metabolic marker, which is often used to assess cardiovascular disease and diabetes However, there have been limited studies on the association between FPG and nonalcoholic fatty liver disease (NAFLD) risk in nonobese people, especially in Chinese individuals The purpose of this study was to investigate the association between FPG and NAFLD in nonobese Chinese people with normal blood lipid levels In this prospective cohort study, 9767 nonobese participants with normal blood lipid levels without NAFLD were recruited and prospectively followed for 5 years The Cox proportional hazard model was used to evaluate the risk factors of NAFLD Moreover, a Cox model with cubic spline functions and smooth curve fitting (the cubic spline smoothing) were used to identify the nonlinear association between FPG and NAFLD During the 5-year follow-up, 841 (861%) participants were diagnosed with NAFLD The good functional results (without NAFLD) estimated by the Kaplan-Meier method for 1 year, 2 years, 3 years, 4 years, and 5 years were 9884, 9535, 9167%, 8757 and 7486%, respectively Additionally, through the Cox proportional hazard model, after adjusting for other covariates, there was an independent positive correlation between FPG and increased NAFLD risk (HR:121, 95% CI:115–128, P   554, the risk of NAFLD increased by 50% (HR:110, 95% CI:102–118, P = 00159) compared with the left side of the inflection point and gradually leveled off In a nonobese Chinese population with normal lipid levels, there is an independent nonlinear association between FPG and NAFLD, and the increase in FPG may indicate an increased risk of NAFLD Additionally, this independent association is more obvious in the short stature population

/pdf/association-between-fasting-plasma-glucose-and-nonalcoholic-t79kdnwac8.pdf

Association between fasting plasma glucose and nonalcoholic fatty liver disease in a nonobese Chinese population with normal blood lipid levels: a prospective cohort study

Two-dimensional shear wave elastography (2D-SWE), magnetic resonance elastography (MRE), aspartate transaminase-to-platelet ratio index (APRI), fibrosis index based on 4 factors (FIB-4), and King’s...

Comparison of two-dimensional shear wave elastography, magnetic resonance elastography, and three serum markers for diagnosing fibrosis in patients with chronic hepatitis B: a meta-analysis

The role of low frequency variants associated with telomere length homeostasis in chronic diseases and mortalities is relatively understudied in the East-Asian population. Here we evaluated low frequency variants, including 1,915,154 Asian specific variants, for leukocyte telomere length (LTL) associations among 25,533 Singapore Chinese samples. Three East Asian specific variants in/near POT1, TERF1 and STN1 genes are associated with LTL (Meta-analysis P 2.49×10−14–6.94×10−10). Rs79314063, a missense variant (p.Asp410His) at POT1, shows effect 5.3 fold higher and independent of a previous common index SNP. TERF1 (rs79617270) and STN1 (rs139620151) are linked to LTL-associated common index SNPs at these loci. Rs79617270 is associated with cancer mortality [HR95%CI = 1.544 (1.173, 2.032), PAdj = 0.018] and 4.76% of the association between the rs79617270 and colon cancer is mediated through LTL. Overall, genetically determined LTL is particularly associated with lung adenocarcinoma [HR95%CI = 1.123 (1.051, 1.201), Padj = 0.007]. Ethnicity-specific low frequency variants may affect LTL homeostasis and associate with certain cancers. Xuling Chang et al. study whether low frequency variants are associated with leukocyte telomere length and whether these variants predispose to incident cancers and mortalities among East Asians. They find that three East Asian specific variants at POT1, TERF1 and STN1 loci are associated with leukocyte telomere length and report a mechanistic pathway linking TERF1, leukocyte telomere length and incident colon cancer.

/pdf/low-frequency-variants-associated-with-leukocyte-telomere-r6w4ttw94n.pdf

Low frequency variants associated with leukocyte telomere length in the Singapore Chinese population.

BACKGROUND AND AIMS
Transient elastography (TE), shear-wave elastography (SWE), and/or magnetic resonance elastography (MRE), each providing liver stiffness measurement (LSM), are the most studied imaging-based noninvasive liver disease assessment (NILDA) techniques. To support the American Association for the Study of Liver Diseases guidelines on NILDA, we summarized the evidence on the accuracy of these LSM methods to stage liver fibrosis (F).


APPROACH AND RESULTS
A comprehensive search for studies assessing LSM by TE, SWE, or MRE for the identification of significant fibrosis (F2-4), advanced fibrosis (F3-4), or cirrhosis (F4), utilizing histopathology as standard of reference by liver disease etiology in adults or children from inception to April 2022 was performed. We excluded studies with <50 patients with a single disease entity and mixed liver disease etiologies (with the exception of HCV/HIV co-infection). Out of 9447 studies, 240 with 61,193 patients were included in this systematic review. In adults, sensitivities for the identification of F2-4 ranged from 51% to 95%, for F3-4 from 70% to 100%, and for F4 from 60% to 100% across all techniques/diseases, whereas specificities ranged from 36% to 100%, 74% to 100%, and 67% to 99%, respectively. The largest body of evidence available was for TE; MRE appeared to be the most accurate method. Imaging-based NILDA outperformed blood-based NILDA in most comparisons, particularly for the identification of F3-4/F4. In the pediatric population, imaging-based NILDA is likely as accurate as in adults.


CONCLUSION
LSM from TE, SWE, and MRE show acceptable to outstanding accuracy for the detection of liver fibrosis across various liver disease etiologies. Accuracy increased from F2-4 to F3-4 and was the highest for F4. Further research is needed to better standardize the use of imaging-based NILDA, particularly in pediatric liver diseases.

Imaging-based non-invasive liver disease assessment for staging liver fibrosis in chronic liver disease: A systematic review supporting the AASLD Practice Guideline.

Artificial intelligence (AI) is of keen interest for global health development as potential support for current human shortcomings. Gastrointestinal (GI) endoscopy is an excellent substrate for AI, since it holds the genuine potential to improve quality in GI endoscopy and overall patient care by improving detection and diagnosis guiding the endoscopists in performing endoscopy to the highest quality standards. The possibility of large data acquisitioning to refine algorithms makes implementation of AI into daily practice a potential reality. With the start of a new era adopting deep learning, large amounts of data can easily be processed, resulting in better diagnostic performances. In the upper gastrointestinal tract, research currently focusses on the detection and characterization of neoplasia, including Barrett's, squamous cell and gastric carcinoma, with an increasing amount of AI studies demonstrating the potential and benefit of AI-augmented endoscopy. Deep learning applied to small bowel video capsule endoscopy also appears to enhance pathology detection and reduce capsule reading time. In the colon, multiple prospective trials including five randomized trials, showed a consistent improvement in polyp and adenoma detection rates, one of the main quality indicators in endoscopy. There are however potential additional roles for AI to assist in quality improvement of endoscopic procedures, training and therapeutic decision making. Further large-scale, multicenter validation trials are required before AI-augmented diagnostic gastrointestinal endoscopy can be integrated into our routine clinical practice.

Striving for quality improvement: can artificial intelligence help?

Chronic hepatitis B (CHB) causes liver fibrosis and then liver cirrhosis and hepatocellular carcinoma, which can result in life-threatening complications, such as gastrointestinal bleeding and liver failure (1,2). In the algorithm for management of CHB, early and accurate diagnosis of liver fibrosis/cirrhosis is particularly important to guide the preventive strategy of their related complications (3). Currently, liver biopsy remains the gold standard approach for staging liver fibrosis, but is often limited by its invasiveness, poor acceptance, sampling variability, and complications (4,5). In addition, repeated biopsy is often unacceptable for dynamic assessment of progression and regression of liver fibrosis. In this setting, the physicians have paid more and more attention to noninvasive assessment of liver fibrosis by physical examinations, routine biochemical and hematological tests, and surrogate serum fibrosis markers (6,7). Several noninvasive models have been developed, such as the FibroTest (8), aspartate aminotransferase (AST)/alanine aminotransferase (ALT) ratio (AAR) (9), AST to platelet index (APRI) (10), and Hepascore (11), etc. However, their diagnostic accuracy is not satisfactory. For example, the evidence from meta-analyses of 37 articles suggested that the APRI had moderate diagnostic performance for significant fibrosis, advanced fibrosis, and cirrhosis in patients with CHB with summary areas under the receiver operating characteristic curve of less than 0.8 (12). Some components included in these models, such as haptoglobin, α2-macroglobulin, and apolipoprotein A1, are not routinely available in clinical practice. It has been reported that liver stiffness measurement (LSM) may have a higher diagnostic accuracy for assessment of advanced liver fibrosis and cirrhosis than serum biomarkers in patients with CHB (13,14), but its usefulness is often questioned in some specific population (i.e., obesity and ascites) (15). In addition, the performance of noninvasive markers for diagnosing middle stages of fibrosis is reduced (16).

We have conducted a Chinese multicenter cross-sectional study involving 1,200 patients with CHB to develop and validate a noninvasive program (i.e., Chin-CHB score) for accurately differentiating liver fibrosis stage by stage based on 30 routinely available parameters.

A Novel Noninvasive Program for Staging Liver Fibrosis in Untreated Patients With Chronic Hepatitis B.

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A Novel Noninvasive Program for Staging Liver Fibrosis in Untreated Patients With Chronic Hepatitis B.