Fatty liver biomarkers and insulin resistance indices in the prediction of non‐alcoholic fatty liver disease in Ghanaian patients

Author:

Bockarie A. S.12ORCID,Nartey Y. A.12,Nsiah P.3,Edzie E. K. M.4ORCID,Tuoyire D.5,Acquah S.6,Eliason S.5,Nkum B.7

Affiliation:

1. Department of Internal Medicine & Therapeutics University of Cape Coast Cape Coast Ghana

2. Department of Medicine Cape Coast Teaching Hospital Cape Coast Ghana

3. Department of Chemical Pathology University of Cape Coast Cape Coast Ghana

4. Department of Radiology University of Cape Coast Cape Coast Ghana

5. Department of Community Medicine University of Cape Coast Cape Coast Ghana

6. Department of Medical Biochemistry University of Cape Coast Cape Coast Ghana

7. Department of Medicine Kwame Nkrumah University of Science and Technology Kumasi Ghana

Abstract

AbstractBackgroundScant West African data on non‐alcoholic fatty liver disease (NAFLD) means there is little representation of this population in the modelling used to derive biomarkers and predictive indices for risk stratification of patients for the presence of hepatic steatosis. This study evaluates the performance of the fatty liver index (FLI), hepatic steatosis index (HSI) and triglyceride‐glucose (TyG) index and its derivatives in predicting ultrasound detected NAFLD in a locally resident population of Ghanaian participants.Methods and FindingsA post hoc analysis of data from a cross sectional assessment of NAFLD and cardiovascular risk was performed. Data from 210 participants without significant alcohol intake, or secondary causes of fatty liver and not on steatogenic drugs was evaluated. A structured questionnaire had been used to collect demographic data, medical and drug history. Anthropometry, blood sampling for liver chemistry and fasting lipids were performed. Hepatic steatosis was detected by ultrasonography. A retrospective analysis involving multivariate binary logistic regression assessed FLI, HIS, TyG (and its derivatives) as predictors of NAFLD with p < .05 considered statistically significant. Sensitivity, specificity, predictive values, likelihood ratios were calculated and accuracy of the proxies evaluated from area under the receiver operating characteristics curve (AUROC).All the biomarkers and indices were significantly associated with NAFLD (p ≤ .001). All the lipid and fatty liver indices assessed performed acceptably as predictors of NAFLD. FLI (AUC = 0.8, 95% CI [0.74–0.87]), TyG‐WC (AUC = 0.81, 95% CI [0.75–0.88]) and TyG‐WHtR (AUC = 0.81, 95% CI [0.74–0.88]) performed best at predicting NAFLD. Whilst in all cases the markers had good specificity (>90%) they lacked sufficient sensitivity with FLI having the highest sensitivity of 36.7%. Their overall accuracy was greater than 70% in each case.ConclusionThe overall accuracy of HSI, FLI, TyG index and its derivatives (TyG WHtR, TyG BMI, TyG WC) was acceptable for predicting NAFLD in this population. Given their performance in this study and in light of their low cost, accessibility, easy interpretation and non‐invasive nature; they are suitable tools for screening in the Ghanaian population.

Publisher

Wiley

Subject

Endocrinology, Diabetes and Metabolism

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