Fatty liver biomarkers and insulin resistance indices in the prediction of non‐alcoholic fatty liver disease in Ghanaian patients
Abstract Background Scant 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 eva...
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Format: | Article |
Language: | English |
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Wiley
2023-11-01
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Series: | Endocrinology, Diabetes & Metabolism |
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Online Access: | https://doi.org/10.1002/edm2.456 |
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author | A. S. Bockarie Y. A. Nartey P. Nsiah E. K. M. Edzie D. Tuoyire S. Acquah S. Eliason B. Nkum |
author_facet | A. S. Bockarie Y. A. Nartey P. Nsiah E. K. M. Edzie D. Tuoyire S. Acquah S. Eliason B. Nkum |
author_sort | A. S. Bockarie |
collection | DOAJ |
description | Abstract Background Scant 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 Findings A 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. Conclusion The 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. |
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institution | Directory Open Access Journal |
issn | 2398-9238 |
language | English |
last_indexed | 2024-03-11T11:13:09Z |
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series | Endocrinology, Diabetes & Metabolism |
spelling | doaj.art-1b9b2973bdca43dca474ba2cabe1eb602023-11-11T09:37:05ZengWileyEndocrinology, Diabetes & Metabolism2398-92382023-11-0166n/an/a10.1002/edm2.456Fatty liver biomarkers and insulin resistance indices in the prediction of non‐alcoholic fatty liver disease in Ghanaian patientsA. S. Bockarie0Y. A. Nartey1P. Nsiah2E. K. M. Edzie3D. Tuoyire4S. Acquah5S. Eliason6B. Nkum7Department of Internal Medicine & Therapeutics University of Cape Coast Cape Coast GhanaDepartment of Internal Medicine & Therapeutics University of Cape Coast Cape Coast GhanaDepartment of Chemical Pathology University of Cape Coast Cape Coast GhanaDepartment of Radiology University of Cape Coast Cape Coast GhanaDepartment of Community Medicine University of Cape Coast Cape Coast GhanaDepartment of Medical Biochemistry University of Cape Coast Cape Coast GhanaDepartment of Community Medicine University of Cape Coast Cape Coast GhanaDepartment of Medicine Kwame Nkrumah University of Science and Technology Kumasi GhanaAbstract Background Scant 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 Findings A 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. Conclusion The 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.https://doi.org/10.1002/edm2.456fatty liver indexGhanahepatic steatosis indexnon‐alcoholic fatty liver diseasetriglyceride glucose index |
spellingShingle | A. S. Bockarie Y. A. Nartey P. Nsiah E. K. M. Edzie D. Tuoyire S. Acquah S. Eliason B. Nkum Fatty liver biomarkers and insulin resistance indices in the prediction of non‐alcoholic fatty liver disease in Ghanaian patients Endocrinology, Diabetes & Metabolism fatty liver index Ghana hepatic steatosis index non‐alcoholic fatty liver disease triglyceride glucose index |
title | Fatty liver biomarkers and insulin resistance indices in the prediction of non‐alcoholic fatty liver disease in Ghanaian patients |
title_full | Fatty liver biomarkers and insulin resistance indices in the prediction of non‐alcoholic fatty liver disease in Ghanaian patients |
title_fullStr | Fatty liver biomarkers and insulin resistance indices in the prediction of non‐alcoholic fatty liver disease in Ghanaian patients |
title_full_unstemmed | Fatty liver biomarkers and insulin resistance indices in the prediction of non‐alcoholic fatty liver disease in Ghanaian patients |
title_short | Fatty liver biomarkers and insulin resistance indices in the prediction of non‐alcoholic fatty liver disease in Ghanaian patients |
title_sort | fatty liver biomarkers and insulin resistance indices in the prediction of non alcoholic fatty liver disease in ghanaian patients |
topic | fatty liver index Ghana hepatic steatosis index non‐alcoholic fatty liver disease triglyceride glucose index |
url | https://doi.org/10.1002/edm2.456 |
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