Evidence map›Paper›PMID 29980170›Full record

ArticleBMC gastroenterology2018

Metabolic syndrome and biochemical changes among non-alcoholic fatty liver disease patients attending a tertiary care hospital of Nepal.

Bashu Dev Pardhe, Shreena Shakya, Anjeela Bhetwal, Jennifer Mathias, Puspa Raj Khanal, Roshan Pandit, Jyotsna Shakya, Hari Om Joshi, Sujan Babu Marahatta

Open access · goldAbstract read
In one paragraph

Article in BMC gastroenterology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
3.2field-weighted citation impact, top 8% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.

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  15. Prevalence of fatty liver in metabolic syndrome.Journal of family medicine and primary care · 2020
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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

9 authors at 4 institutions in 3 countries.

Bashu Dev PardheDepartment of Laboratory Medicine, Manmohan Memorial Institute of Health Sciences, Kathmandu, Nepal. bashudev.pardhe@mmihs.edu.np.ORCID http://orcid.org/0000-0002-0745-7383
Shreena ShakyaDepartment of Laboratory Medicine, Manmohan Memorial Institute of Health Sciences, Kathmandu, Nepal.
Anjeela BhetwalDepartment of Laboratory Medicine, Manmohan Memorial Institute of Health Sciences, Kathmandu, Nepal.
Jennifer MathiasDepartment of Health Science, National Open College, Sanepa, Lalitpur, Nepal.
Puspa Raj KhanalDepartment of Laboratory Medicine, Manmohan Memorial Institute of Health Sciences, Kathmandu, Nepal.
Roshan PanditDepartment of Laboratory Medicine, Manmohan Memorial Institute of Health Sciences, Kathmandu, Nepal.
Jyotsna ShakyaDepartment of Laboratory Medicine, Manmohan Memorial Institute of Health Sciences, Kathmandu, Nepal.
Hari Om JoshiDepartment of Radiology, Bhaktapur District Hospital, Bhaktapur, Nepal.
Sujan Babu MarahattaDepartment of Public Health, Manmohan Memorial Institute of Health Sciences, Kathmandu, Nepal.
Manmohan Memorial Institute of Health Sciences · NPBhaktapur Cancer Hospital · NPNational Open University · TWSanford Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNon-alcoholic fatty liver disease (NAFLD) is mutually and bidirectionally linked with metabolic syndrome (MetS) of which it is both the cause and the consequences. Worldwide, 6.3 to 33% of the general populations are estimated to suffer from the disease with even higher prevalence in the group sharing metabolic co-morbidities. Hence, this study aims to recognize various risk factors including metabolic components and blood parameters to predict the possible incidence of the disease.

methodsTotal of 429 (219 NAFLD and 210 control) subjects were conveniently selected for study during the period of 9 months. Diagnosis of non-alcoholic fatty liver disease was done by liver imaging and based on liver enzymes. Assessment of metabolic syndrome was done by International Diabetic Federation (IDF) and National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) criteria. All biochemical and hematological parameters and liver enzymes were estimated by using standard guideline. Mean comparison of quantitative data in different groups were performed using analysis of variance (one-way ANOVA). Risk estimation of NAFLD associated with each character was verified by Chi-square test.

resultsThere was significant high levels of body mass index (BMI), waist circumference (WC) and lipid profiles in NAFLD patients in comparison to control population (p < 0.001). Further, according to the NCEP ATP III criteria, 13.6% of NAFLD were present with MetS where risk estimate was significant (OR = 2.15). Whereas, other criteria (IDF) for MetS showed higher frequency (30.1%) with higher risk (OR = 29.75) for the presence of MetS in NAFLD patients. The change in triglycerides (TG) and HDL-C (high density lipoprotein cholesterol) was also statistically significant in different grades of NAFLD. High risk for NAFLD was associated with existing co-morbid conditions like cardiovascular risk patients (3.18 times) followed by obese patients (1.72 times) and Diabetes Mellitus patients (1.68 times) at a significant level.

conclusionThe result of this study suggests that there is an increased prevalence of all the components of MetS and significant changes in biochemical markers in cases of NAFLD. Timely diagnosis would help in delaying its complications and co-morbidities.

Indexed as

AdultBiomarkersBody Mass IndexCross-Sectional StudiesFemaleHumansLipidsLiverMaleMetabolic SyndromeMiddle AgedNepalNon-alcoholic Fatty Liver DiseasePrevalenceRisk FactorsTertiary Care CentersBiomarkersLipidsBiochemical markersMetabolic syndromeNon-alcoholic fatty liver diseaseTransaminases

Identifiers

PMID29980170
PMCPMC6035472
OpenAlexW2843294905

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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.