Fatty Liver Index and Development of Cardiovascular Disease: Findings from the UK Biobank

2021 ◽  
Author(s):  
Biyao Zou ◽  
Yee Hui Yeo ◽  
Ramsey Cheung ◽  
Erik Ingelsson ◽  
Mindie H. Nguyen
Keyword(s):  
Cardiovascular Disease ◽  
Fatty Liver ◽  
Uk Biobank ◽  
Liver Index ◽  
Fatty Liver Index ◽  
The Uk

scholarly journals Fatty Liver Index and Lipid Accumulation Product Can Predict Metabolic Syndrome in Subjects without Fatty Liver Disease

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Yuan-Lung Cheng ◽  
Yuan-Jen Wang ◽  
Keng-Hsin Lan ◽  
Teh-Ia Huo ◽  
Yi-Hsiang Huang ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Metabolic Syndrome ◽  
Liver Disease ◽  
Fatty Liver ◽  
Lipid Accumulation ◽  
Fatty Liver Disease ◽  
Lipid Accumulation Product ◽  
Liver Index ◽  
Fatty Liver Index ◽  
Better Than

Background. Fatty liver index (FLI) and lipid accumulation product (LAP) are indexes originally designed to assess the risk of fatty liver and cardiovascular disease, respectively. Both indexes have been proven to be reliable markers of subsequent metabolic syndrome; however, their ability to predict metabolic syndrome in subjects without fatty liver disease has not been clarified.Methods. We enrolled consecutive subjects who received health check-up services at Taipei Veterans General Hospital from 2002 to 2009. Fatty liver disease was diagnosed by abdominal ultrasonography. The ability of the FLI and LAP to predict metabolic syndrome was assessed by analyzing the area under the receiver operating characteristic (AUROC) curve.Results. Male sex was strongly associated with metabolic syndrome, and the LAP and FLI were better than other variables to predict metabolic syndrome among the 29,797 subjects. Both indexes were also better than other variables to detect metabolic syndrome in subjects without fatty liver disease (AUROC: 0.871 and 0.879, resp.), and the predictive power was greater among women.Conclusion. Metabolic syndrome increases the cardiovascular disease risk. The FLI and LAP could be used to recognize the syndrome in both subjects with and without fatty liver disease who require lifestyle modifications and counseling.

scholarly journals Fatty liver index and development of cardiovascular disease in Koreans without pre-existing cardiovascular disease: a large population-based study

2020 ◽  
Author(s):  
Jun Hyung Kim ◽  
Jin Sil Moon ◽  
Seok Joon Byun ◽  
Jun Hyeok Lee ◽  
Dae Ryong Kang ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Ischemic Stroke ◽  
Fatty Liver ◽  
Primary Endpoint ◽  
Large Population ◽  
Cardiovascular Death ◽  
Population Based ◽  
Population Based Study ◽  
Liver Index ◽  
Fatty Liver Index

Abstract Background Despite the known association between non-alcoholic fatty liver disease (NAFLD) and cardiovascular disease (CVD), it remains uncertain whether NAFLD predicts future CVD events, especially CVD mortality. We evaluated the relationship between fatty liver index (FLI), a validated marker of NAFLD, and risk of major adverse cardiac events (MACE) in a large population-based study. Methods We identified 3,011,588 subjects without a history of CVD who underwent health examinations from 2009 to 2011 in the Korean National Health Insurance System cohort. The primary endpoint was a composite of cardiovascular deaths, non-fatal myocardial infarction (MI), and ischemic stroke. Cox proportional hazards regression analysis was performed to assess the independent association between FLI and the primary endpoint. Results During the median follow-up of 6 years, there were 46,010 cases of MACE (7,148 cases of cardiovascular death, 16,574 non-fatal MI, and 22,228 ischemic stroke). There was a linear association between higher FLI values and higher incidence of the primary endpoint. In the multivariable models adjusted for factors including body weight and cholesterol levels, the hazard ratio (95% CIs) for the primary endpoint comparing the highest vs. lowest quartiles of FLI was 1.99 (1.91–2.07). The corresponding odds ratios (95% CIs) for cardiovascular death, non-fetal MI, and ischemic stroke were 1.98 (1.9-2.06), 2.16 (2.01-2.31), and 2.01 (1.90-2.13), respectively. The results were similar when we stratified analysis by age, sex, dyslipidemia medication, obesity, diabetes, and hypertension. Conclusions Our findings indicate that FLI, a surrogate marker of NAFLD, has prognostic value for detecting individuals at higher risk of cardiovascular events.

Association of fatty liver index with the risk of incident cardiovascular disease and acute myocardial infarction

2018 ◽  
Vol 30 (9) ◽  
pp. 1047-1054 ◽  
Author(s):  
Olubunmi O. Olubamwo ◽  
Jyrki K. Virtanen ◽  
Ari Voutilainen ◽  
Jussi Kauhanen ◽  
Jussi Pihlajamäki ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Cardiovascular Disease ◽  
Acute Myocardial Infarction ◽  
Fatty Liver ◽  
Liver Index ◽  
Fatty Liver Index ◽  
Incident Cardiovascular Disease

1907-P: GLP-1RA and iSGLT2 Combination Treatment Effects over Fatty Liver Index

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 1907-P
Author(s):  
JUANA CARRETERO GÓMEZ ◽  
JOSE CARLOS AREVALO LORIDO ◽  
RICARDO GÓMEZ-HUELGAS ◽  
JOSÉ MIGUEL SEGUÍ-RIPOLL ◽  
MANUEL SUAREZ TEMBRA ◽  
...  
Keyword(s):  
Fatty Liver ◽  
Combination Treatment ◽  
Treatment Effects ◽  
Liver Index ◽  
Fatty Liver Index

2306-PUB: Serum CXCL14 Levels Are Associated with Plasma C-Peptide and Fatty Liver Index in T2DM Patients: A Retrospective Analysis

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 2306-PUB
Author(s):  
YURIKO MATSUSHITA ◽  
YUTAKA HASEGAWA ◽  
NORIKO TAKEBE ◽  
YASUSHI ISHIGAKI
Keyword(s):  
Fatty Liver ◽  
Retrospective Analysis ◽  
C Peptide ◽  
Liver Index ◽  
Fatty Liver Index

Advanced cardiometabolic & inflammatory markers for prediction of cardiovascular disease and cancer

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
D Radenkovic ◽  
S.C Chawla ◽  
G Botta ◽  
A Boli ◽  
M.B Banach ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Risk Score ◽  
Cancer Incidence ◽  
Risk Function ◽  
Patient Characteristics ◽  
Risk Scores ◽  
Uk Biobank ◽  
Training Set ◽  
All Cause Mortality ◽  
The Uk

Abstract   The two leading causes of mortality worldwide are cardiovascular disease (CVD) and cancer. The annual total cost of CVD and cancer is an estimated $844.4 billion in the US and is projected to double by 2030. Thus, there has been an increased shift to preventive medicine to improve health outcomes and development of risk scores, which allow early identification of individuals at risk to target personalised interventions and prevent disease. Our aim was to define a Risk Score R(x) which, given the baseline characteristics of a given individual, outputs the relative risk for composite CVD, cancer incidence and all-cause mortality. A non-linear model was used to calculate risk scores based on the participants of the UK Biobank (= 502548). The model used parameters including patient characteristics (age, sex, ethnicity), baseline conditions, lifestyle factors of diet and physical activity, blood pressure, metabolic markers and advanced lipid variables, including ApoA and ApoB and lipoprotein(a), as input. The risk score was defined by normalising the risk function by a fixed value, the average risk of the training set. To fit the non-linear model >400,000 participants were used as training set and >45,000 participants were used as test set for validation. The exponent of risk function was represented as a multilayer neural network. This allowed capturing interdependent behaviour of covariates, training a single model for all outcomes, and preserving heterogeneity of the groups, which is in contrast to CoxPH models which are traditionally used in risk scores and require homogeneous groups. The model was trained over 60 epochs and predictive performance was determined by the C-index with standard errors and confidence intervals estimated with bootstrap sampling. By inputing the variables described, one can obtain personalised hazard ratios for 3 major outcomes of CVD, cancer and all-cause mortality. Therefore, an individual with a risk Score of e.g. 1.5, at any time he/she has 50% more chances than average of experiencing the corresponding event. The proposed model showed the following discrimination, for risk of CVD (C-index = 0.8006), cancer incidence (C-index = 0.6907), and all-cause mortality (C-index = 0.7770) on the validation set. The CVD model is particularly strong (C-index >0.8) and is an improvement on a previous CVD risk prediction model also based on classical risk factors with total cholesterol and HDL-c on the UK Biobank data (C-index = 0.7444) published last year (Welsh et al. 2019). Unlike classically-used CoxPH models, our model considers correlation of variables as shown by the table of the values of correlation in Figure 1. This is an accurate model that is based on the most comprehensive set of patient characteristics and biomarkers, allowing clinicians to identify multiple targets for improvement and practice active preventive cardiology in the era of precision medicine. Figure 1. Correlation of variables in the R(x) Funding Acknowledgement Type of funding source: None

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