Evidence map›Paper›PMID 37814510›Full record

ArticleEndocrinology, diabetes & metabolism2023

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

A S Bockarie, Y A Nartey, P Nsiah, E K M Edzie, D Tuoyire, S Acquah, S Eliason, B Nkum

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Endocrinology, diabetes & metabolism, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 3 pooled it
1.1field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 3 syntheses or guidelines pooled it, 5 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

A S BockarieDepartment of Internal Medicine & Therapeutics, University of Cape Coast, Cape Coast, Ghana.ORCID 0000-0003-1173-1493
Y A NarteyDepartment of Internal Medicine & Therapeutics, University of Cape Coast, Cape Coast, Ghana.
P NsiahDepartment of Chemical Pathology, University of Cape Coast, Cape Coast, Ghana.
E K M EdzieDepartment of Radiology, University of Cape Coast, Cape Coast, Ghana.ORCID 0000-0002-5485-2386
D TuoyireDepartment of Community Medicine, University of Cape Coast, Cape Coast, Ghana.
S AcquahDepartment of Medical Biochemistry, University of Cape Coast, Cape Coast, Ghana.
S EliasonDepartment of Community Medicine, University of Cape Coast, Cape Coast, Ghana.
B NkumDepartment of Medicine, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
University of Cape Coast · GHKwame Nkrumah University of Science and Technology · GH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundScant 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.

Indexed as

Insulin ResistanceNon-alcoholic Fatty Liver DiseaseBiomarkersCross-Sectional StudiesGhanaGlucoseHumansInsulinInsulin, Regular, HumanRetrospective StudiesTriglyceridesBiomarkersGlucoseInsulinInsulin, Regular, HumanTriglyceridesfatty liver indexGhanahepatic steatosis indexnon-alcoholic fatty liver diseasetriglyceride glucose index

Identifiers

PMID37814510
PMCPMC10638625
OpenAlexW4387473168

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.