scholarly journals Predicting Liver Disease Risk Using a Combination of Common Clinical Markers: A Screening Model from Routine Health Check-Up

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yi Wang ◽  
Yanni Li ◽  
Xiaoyi Wang ◽  
Ranko Gacesa ◽  
Jie Zhang ◽  
...  
Keyword(s):  
Liver Disease ◽  
Early Detection ◽  
Predictive Power ◽  
Disease Screening ◽  
Health Check ◽  
Initial Presentation ◽  
Screening Tools ◽  
Clinical Markers ◽  
Liver Disorders ◽  
High Predictive Power

Background. Early detection is crucial for the prognosis of patients with autoimmune liver disease (AILD). Due to the relatively low incidence, developing screening tools for AILD remain a challenge. Aims. To analyze clinical characteristics of AILD patients at initial presentation and identify clinical markers, which could be useful for disease screening and early detection. Methods. We performed observational retrospective study and analyzed 581 AILD patients who were hospitalized in the gastroenterology department and 1000 healthy controls who were collected from health management center. Baseline characteristics at initial presentation were used to build regression models. The model was validated on an independent cohort of 56 patients with AILD and 100 patients with other liver disorders. Results. Asymptomatic AILD individuals identified by the health check-up are increased yearly (from 31.6% to 68.0%, p<0.001). The cirrhotic rates at an initial presentation are decreased in the past 18 years (from 52.6% to 20.0%, p<0.001). Eight indicators, which are common in the health check-up, are independent risk factors of AILD. Among them, abdominal lymph node enlargement (LN) positive is the most significant different (OR 8.85, 95% CI 2.73-28.69, p<0.001). The combination of these indicators shows high predictive power (AUC=0.98, sensitivity 89.0% and specificity 96.4%) for disease screening. Except two liver or cholangetic injury makers, the combination of AGE, GENDER, GLB, LN, concomitant extrahepatic autoimmune diseases, and familial history also shows a high predictive power for AILD in other liver disorders (AUC=0.91). Conclusion. Screening for AILD with described parameters can detect AILD in routine health check-up early, effectively and economically. Eight variables in routine health check-up are associated with AILD and the combination of them shows good ability of identifying high-risk individuals.

Tu1526 – Prediction of High-Risk Individuals of Autoimmune Liver Disease by Health Check-Up: the Importance of Early Detection

2019 ◽  
Vol 156 (6) ◽  
pp. S-1353
Author(s):  
Yi Wang ◽  
Yanni Li ◽  
Ranko Gacesa ◽  
Xiaoyi Wang ◽  
Simin Zhou ◽  
...  
Keyword(s):  
Liver Disease ◽  
High Risk ◽  
Early Detection ◽  
Health Check ◽  
Autoimmune Liver Disease

Study of Biochemical and Clinical Markers in Steatohepatitis Related to Obesity

2018 ◽  
Vol 69 (6) ◽  
pp. 1501-1505
Author(s):  
Roxana Maria Livadariu ◽  
Radu Danila ◽  
Lidia Ionescu ◽  
Delia Ciobanu ◽  
Daniel Timofte
Keyword(s):  
Liver Disease ◽  
Liver Biopsy ◽  
Large Scale ◽  
Biological Data ◽  
Obese Patients ◽  
Clinical Markers ◽  
Mean Values ◽  
Nonalcoholic Fatty Liver ◽  
Obstructive Sleep ◽  
Increased Risk

Nonalcoholic fatty liver disease (NAFLD) is highly associated to obesity and comprises several liver diseases, from simple steatosis to steatohepatitis (NASH) with increased risk of developing progressive liver fibrosis, cirrhosis and hepatocellular carcinoma. Liver biopsy is the gold standard in diagnosing the disease, but it cannot be used in a large scale. The aim of the study was the assessment of some non-invasive clinical and biological markers in relation to the progressive forms of NAFLD. We performed a prospective study on 64 obese patients successively hospitalised for bariatric surgery in our Surgical Unit. Patients with history of alcohol consumption, chronic hepatitis B or C, other chronic liver disease or patients undergoing hepatotoxic drug use were excluded. All patients underwent liver biopsy during sleeve gastrectomy. NAFLD was present in 100% of the patients: hepatic steatosis (38%), NASH with the two forms: with fibrosis (31%) and without fibrosis (20%), cumulating 51%; 7 patients had NASH with vanished steatosis. NASH with fibrosis statistically correlated with metabolic syndrome (p = 0.036), DM II (p = 0.01) and obstructive sleep apnea (p = 0.02). Waist circumference was significantly higher in the steatohepatitis groups (both with and without fibrosis), each 10 cm increase increasing the risk of steatohepatitis (p = 0.007). The mean values of serum fibrinogen and CRP were significantly higher in patients having the progressive forms of NAFLD. Simple clinical and biological data available to the practitioner in medicine can be used to identify obese patients at high risk of NASH, aiming to direct them to specialized medical centers.

scholarly journals Metabolomic Biomarkers for the Detection of Obesity-Driven Endometrial Cancer

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 718
Author(s):  
Kelechi Njoku ◽  
Amy E. Campbell ◽  
Bethany Geary ◽  
Michelle L. MacKintosh ◽  
Abigail E. Derbyshire ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Early Detection ◽  
Minimally Invasive ◽  
Cancer Detection ◽  
Test Performance ◽  
Female Genital Tract ◽  
Screening Tools ◽  
Normal Endometrium ◽  
Endometrioid Endometrial Cancer ◽  
Post Menopausal

Endometrial cancer is the most common malignancy of the female genital tract and a major cause of morbidity and mortality in women. Early detection is key to ensuring good outcomes but a lack of minimally invasive screening tools is a significant barrier. Most endometrial cancers are obesity-driven and develop in the context of severe metabolomic dysfunction. Blood-derived metabolites may therefore provide clinically relevant biomarkers for endometrial cancer detection. In this study, we analysed plasma samples of women with body mass index (BMI) ≥ 30 kg/m2 and endometrioid endometrial cancer (cases, n = 67) or histologically normal endometrium (controls, n = 69), using a mass spectrometry-based metabolomics approach. Eighty percent of the samples were randomly selected to serve as a training set and the remaining 20% were used to qualify test performance. Robust predictive models (AUC > 0.9) for endometrial cancer detection based on artificial intelligence algorithms were developed and validated. Phospholipids were of significance as biomarkers of endometrial cancer, with sphingolipids (sphingomyelins) discriminatory in post-menopausal women. An algorithm combining the top ten performing metabolites showed 92.6% prediction accuracy (AUC of 0.95) for endometrial cancer detection. These results suggest that a simple blood test could enable the early detection of endometrial cancer and provide the basis for a minimally invasive screening tool for women with a BMI ≥ 30 kg/m2.

Remnant Lipoprotein Cholesterol as a Factor Related to Adult Fatty Liver Disease

2021 ◽  
Author(s):  
Shuang Zhang ◽  
Shitong Cheng ◽  
Xue He ◽  
Wei Wang ◽  
Ke Yun ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Liver Disease ◽  
Fatty Liver ◽  
Fatty Liver Disease ◽  
Characteristic Curve ◽  
Health Check ◽  
Lipoprotein Cholesterol ◽  
Strong Positive Correlation ◽  
Variable Model ◽  
Remnant Lipoprotein

Abstract Context Dyslipidemia is related to fatty liver disease (FLD), whose relationship with remnant lipoprotein cholesterol (RLP-C), a component of blood lipids, remains unclear. Objective To clarify the correlation between RLP-C and the occurrence and severity of FLD and establish an FLD discriminant model based on health check indicators. Methods Retrospective study of participants who underwent health check-up in the First Affiliated Hospital of China Medical University (Shenyang, China) between January and December 2019. We categorized participants according to liver ultrasound results and analyzed the correlation between RLP-C and occurrence of FLD (n = 38 885) through logistic regression, restricted cubic spline, and receiver operating characteristic curve. We categorized the severity of FLD according to the control attenuation parameter and analyzed the correlation between RLP-C and FLD severity through multiple logistic regression; only males were included (n = 564). Results The adjusted OR (aOR) per SD between RLP-C and FLD was 2.33 (95% CI 2.21-2.46, P &lt; .001), indicating a dose–response relationship (P &lt; .0001). The optimal cut-off value of RLP-C was 0.45 mmol/L and the area under the curve (AUC) was 0.79. The AUC of the 8-variable model was 0.89 in both the training and the validation sets. FLD severity was related to the level of RLP-C (aOR per SD = 1.29, 95% CI 1.07-1.55, P = .008). Conclusion RLP-C has a strong positive correlation with FLD occurrence and FLD severity. These results may help clinicians identify and implement interventions in individuals with high FLD risk and reduce FLD prevalence.

Early detection of fatty liver disease in mice via quantitative ultrasound

2014 ◽  
Author(s):  
Aiguo Han ◽  
John W. Erdman ◽  
Douglas G. Simpson ◽  
Michael P. Andre ◽  
William D. O'Brien
Keyword(s):  
Liver Disease ◽  
Early Detection ◽  
Fatty Liver ◽  
Quantitative Ultrasound ◽  
Fatty Liver Disease

scholarly journals A novel model for predicting fatty liver disease by means of an artificial neural network

2020 ◽  
Author(s):  
Yi-Shu Chen ◽  
Dan Chen ◽  
Chao Shen ◽  
Ming Chen ◽  
Chao-Hui Jin ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Liver Disease ◽  
Diagnostic Accuracy ◽  
Fatty Liver ◽  
Fatty Liver Disease ◽  
Health Check ◽  
Ann Model ◽  
Artificial Neural ◽  
Input Variables

Abstract Background The artificial neural network (ANN) emerged recently as a potent diagnostic tool, especially for complicated systemic diseases. This study aimed to establish a diagnostic model for the recognition of fatty liver disease (FLD) by virtue of the ANN. Methods A total of 7,396 pairs of gender- and age-matched subjects who underwent health check-ups at the First Affiliated Hospital, College of Medicine, Zhejiang University (Hangzhou, China) were enrolled to establish the ANN model. Indices available in health check-up reports were utilized as potential input variables. The performance of our model was evaluated through a receiver-operating characteristic (ROC) curve analysis. Other outcome measures included diagnostic accuracy, sensitivity, specificity, Cohen’s k coefficient, Brier score, and Hosmer-Lemeshow test. The Fatty Liver Index (FLI) and the Hepatic Steatosis Index (HSI), retrained using our training-group data with its original designated input variables, were used as comparisons in the capability of FLD diagnosis. Results Eight variables (age, gender, body mass index, alanine aminotransferase, aspartate aminotransferase, uric acid, total triglyceride, and fasting plasma glucose) were eventually adopted as input nodes of the ANN model. By applying a cut-off point of 0.51, the area under ROC curves of our ANN model in predicting FLD in the testing group was 0.908 [95% confidence interval (CI), 0.901–0.915]—significantly higher (P &lt; 0.05) than that of the FLI model (0.881, 95% CI, 0.872–0.891) and that of the HSI model (0.885; 95% CI, 0.877–0.893). Our ANN model exhibited higher diagnostic accuracy, better concordance with ultrasonography results, and superior capability of calibration than the FLI model and the HSI model. Conclusions Our ANN system showed good capability in the diagnosis of FLD. It is anticipated that our ANN model will be of both clinical and epidemiological use in the future.

Hepatology after Hepatitis C

2016 ◽  
Vol 34 (5) ◽  
pp. 603-606 ◽  
Author(s):  
J. Gregory Fitz
Keyword(s):  
Liver Disease ◽  
Hepatitis C ◽  
Liver Injury ◽  
Early Detection ◽  
Liver Diseases ◽  
Population Level ◽  
Success Stories ◽  
Risk Variants ◽  
Complications Of Cirrhosis ◽  
Direct Acting

The ∼90% probability of curing individual patients with hepatitis C virus (HCV)using direct-acting antivirals represents one of the most dramatic medical success stories of the modern era, and the journey from viral discovery to treatment occurred over just ∼25 years. The realities of the global burden of disease (2-3% of the world's population is infected), limited access to care and cost of treatment mean that HCV will continue to be a major problem for the next 25 years. But what if HCV (and hepatitis B) could be eradicated? Since liver transplantation and HCV management have been the mainstays of academic hepatology practice, where do we go from here? Unfortunately, we are in an era where the incidence and prevalence of liver diseases around the globe is increasing, and death from complications of cirrhosis is now among the top 10 causes in most countries; so hepatologists are expected to play a major role in the future. Despite remarkable progress, success at the population level is limited by the resource-intensive nature of caring for patients with end-stage disease. Accordingly, the major advances in the next decade are likely to focus on (i) the earlier identification of individuals and populations at higher risk for liver diseases, and (ii) initiation in high-risk populations of specific strategies for early detection and treatment of fibrosis, cancer and cirrhosis. The answers will lie in large part in the further exploration of the human genome in carefully phenotyped patients. Risk variants in the PNPLA3 gene represent the best example to date. The risk variants are common and are enriched in certain populations around the globe; and individuals that possess risk variants are more likely to have liver injury from fatty liver disease (even as children), alcohol and viral hepatitis. Further, those with liver injury are more likely to progress to cirrhosis and hepatoma. Similarly, in those with established liver disease, use of biomarkers and other strategies for early detection of fibrosis and hepatoma will pay dividends as the next generation of treatments focusing on (i) anti-fibrotic strategies and (ii) liver regeneration move to the forefront. There remains an important need to invest in hepatology as a growth industry even after the (unlikely) eradication of HCV.

scholarly journals Increased liver stiffness in patients with severe sleep apnoea and metabolic comorbidities

2018 ◽  
Vol 51 (6) ◽  
pp. 1800601 ◽  
Author(s):  
Wojciech Trzepizur ◽  
Jérôme Boursier ◽  
Marc Le Vaillant ◽  
Pierre-Henri Ducluzeau ◽  
Séverine Dubois ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Liver Disease ◽  
Liver Fibrosis ◽  
Liver Stiffness ◽  
Sleep Apnoea ◽  
Screening Tools ◽  
The Metabolic Syndrome ◽  
Obstructive Sleep ◽  
Increased Risk ◽  
Metabolic Comorbidities

The goal of this study was to assess the relationship between the severity of obstructive sleep apnoea (OSA) and liver stiffness measurement (LSM), one of the most accurate noninvasive screening tools for liver fibrosis in nonalcoholic fatty liver disease.The study included 147 patients with at least one criterion for the metabolic syndrome, assessed by polysomnography for suspected OSA. LSM was performed using transient elastography (FibroScan). Significant liver disease and advanced liver fibrosis were defined as LSM ≥7.3 and ≥9.6 kPa, respectively.23 patients were excluded because of unreliable LSM. Among 124 patients, 34 (27.4%) had mild OSA, 38 (30.6%) had moderate OSA and 52 (42.0%) had severe OSA. LSM values were 7.3– <9.6 kPa in 18 (14.5%) patients and ≥9.6 kPa in 15 (12.1%) patients. A dose–response relationship was observed between OSA severity and LSM values (p=0.004). After adjustment for age, sex, metabolic syndrome and insulin resistance, severe OSA was associated with an increased risk of LSM ≥7.3 kPa (OR 7.17, 95% CI 2.51–20.50) and LSM ≥9.6 kPa (OR 4.73, 95% CI 1.25–17.88).In patients with metabolic comorbidities, severe OSA is independently associated with increased liver stiffness, which may predispose to a higher risk of significant liver disease and poorer prognosis.

Saponins in management of Hepatic Disorders: a review

2021 ◽  
Vol 11 ◽  
Author(s):  
Jasmine Chaudhary ◽  
Akash Jain ◽  
Randhir Dahiya
Keyword(s):  
Liver Disease ◽  
Side Effects ◽  
Liver Diseases ◽  
Hepatoprotective Activity ◽  
Herbal Drugs ◽  
Cost Of Treatment ◽  
Liver Disorders ◽  
Underlying Mechanisms ◽  
Major Factors ◽  
The Cost

: Liver disease is one of the major factors responsible for increased morbidity and mortality worldwide. Presently, limited therapeutic options are available to treat liver diseases. Moreover, allopathic medications are a double-edged sword due to their unfavorable side effects and exaggerated cost of therapy associated with the treatment. Transplantation of the liver is still in infancy state and is associated with staggering cost as well as non-accessibility of donors. Moreover, the cost of treatment is also a very significant hindrance in the treatment of liver disorders. Therefore, the focus is shifting to evaluate the potential of herbal drugs for the management of liver disorders. Although the course of treatment with the herbals is slow yet, the effects are more promising due to lesser side effects and reduced cost of therapy. Numerous plants have been reported to possess hepatoprotective activity due to the presence of phytochemicals like alkaloids, flavonoids, saponins, etc. Among these phytoconstituents, saponins are considered more promising candidates in the management of hepatic disorders. The present review is focused on the plants containing saponins used in the management of hepatic disorders with their underlying mechanisms.

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