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H-FABP: A beacon of hope for prediabetic heart disease

Authors :
Priyamvadha Ramesh
Ajay Chauhan
Parul Goyal
Akanksha Singh
Source :
Journal of Family Medicine and Primary Care, Vol 9, Iss 7, Pp 3421-3428 (2020)
Publication Year :
2020
Publisher :
Wolters Kluwer Medknow Publications, 2020.

Abstract

Background: Prediabetes is increasingly being studied in the context of its association with cardiovascular disease (CVD). Besides raised HbA1c and sugar levels, the major underlying defect seems to be insulin resistance (IR). Subclinical atherosclerosis, measured by high sensitivity C reactive protein (hsCRP) and carotid artery intima media thickness (CIMT) underlies the pathogenesis of CVD in prediabetes. Heart-type fatty acid binding protein (H-FABP), a novel cardiac biomarker also might have a role in predictin prediabetic heart disease. Aims: The aim of the study is to compare serum levels of H-FABP in prediabetics and controls and correlate them with the atherosclerotic markers, hsCRP and CIMT. Setting and Design: 50 prediabetic patients and 50 age, sex and BMI matched controls were employed in the case control study. Serum F & PPBS, (HbA1c), fasting insulin levels were measured in cases and controls. Serum H-FABP was measured in both cases and controls. All cases and controls were subjected to bilateral CIMT measurements and Serum hsCRP levels. The values were compared between both the groups and subjected to appropriate statistical analysis. Statistical Analysis Used: Categorical variables were presented in number and percentage (%) and continuous variables were presented as mean ± SD and median. Normality of data was tested by Kolmogorov-Smirnov test. If the normality was rejected then non parametric test was used. Quantitative variables were compared using Independent t test/Mann-Whitney Test (when the data sets were not normally distributed) between the two groups. Qualitative variables were correlated using Chi-Square test/Fisher's Exact test. Spearman rank correlation coefficient was used to find out the correlation of various parameters with each other. Univariate linear regression was used to find out the cause and effect relationship between various parameters. A p

Details

Language :
English
ISSN :
22494863
Volume :
9
Issue :
7
Database :
Directory of Open Access Journals
Journal :
Journal of Family Medicine and Primary Care
Publication Type :
Academic Journal
Accession number :
edsdoj.0f991ce5e6034d5d95f0a8bcdfd94f5b
Document Type :
article
Full Text :
https://doi.org/10.4103/jfmpc.jfmpc_296_20