Comparison of various steady state surrogate insulin resistance indices in diagnosing metabolic syndrome

Abstract Background Insulin resistance is core cause of metabolic syndrome. Determining insulin resistance is one of the foremost requirements imperative to understanding the pathophysiology of disease. The gold standard “Euglycaemic clamp test” is cumbersome, long and non-feasible in routine clinic...

Full description

Bibliographic Details
Main Authors: Sikandar Hayat Khan, Ali Nawaz Khan, Nayyer Chaudhry, Roomana Anwar, Nadeem Fazal, Muhammad Tariq
Format: Article
Language:English
Published: BMC 2019-06-01
Series:Diabetology & Metabolic Syndrome
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13098-019-0439-5
id doaj-5e6d760deff74a6ab5ae5259cb05c2db
record_format Article
spelling doaj-5e6d760deff74a6ab5ae5259cb05c2db2020-11-25T03:54:26ZengBMCDiabetology & Metabolic Syndrome1758-59962019-06-011111910.1186/s13098-019-0439-5Comparison of various steady state surrogate insulin resistance indices in diagnosing metabolic syndromeSikandar Hayat Khan0Ali Nawaz Khan1Nayyer Chaudhry2Roomana Anwar3Nadeem Fazal4Muhammad Tariq5Department of Pathology PNS HAFEEZArmed Forces Institute of CardiologyDepartment of Chemical Pathology (AFIP)Department of Biochemistry, Baqai Medical UniversityDepartment of Medicine PNS HAFEEZHealthcare Administration PNS HAFEEZAbstract Background Insulin resistance is core cause of metabolic syndrome. Determining insulin resistance is one of the foremost requirements imperative to understanding the pathophysiology of disease. The gold standard “Euglycaemic clamp test” is cumbersome, long and non-feasible in routine clinical setups to diagnose metabolic syndrome. Various continuous and steady state insulin resistance indices are now available in literature. We plan to evaluate commonly utilized steady state insulin resistance indices directly and Homeostasis Model Assessment for Insulin Resistance (HOMAIR) with added triglyceride (HOMA-TG index). Methods The cross-sectional study was carried from Jan-2016 to Dec-2018 at PNS HAFEEZ and department of chemical pathology, AFIP with following objectives: (1) To evaluate steady state insulin resistance markers for diagnosing metabolic syndrome as per IDF defined criteria by ROC curve analysis, (2) to measure Kendal Concordance between various insulin resistance indices and (3) to correlate steady state insulin resistance markers with anthropometric and lipid indices. After several exclusions we selected 224 subjects based upon “non-probability convenience sampling” for inclusion in study. Clinical history, anthropometric measures were calculated and sampling was done for insulin, glucose and other biochemical parameters. Metabolic syndrome was diagnosed as per IDF criteria, while HbA1c was utilized to diagnose diabetes mellitus. Pearson correlation was used to correlate various steady state insulin resistance indices including HOMAIR, HOMA2 index, QUICKI, G/I ratio, HOMA-TG index and serum insulin. AUC was calculated by ROC analysis for all surrogate insulin measures in diagnosis of metabolic syndrome. Results “HOMA-TG index” has shown the highest AUC for diagnosing metabolic syndrome along with higher correlation with lipid markers and anthropometric indices in comparison to other steady-state insulin resistance markers. Furthermore, QUICKI and G/I ratio showed the lowest AUC for detection of metabolic syndrome. Conclusion “HOMA-TG index” has shown highest AUC for metabolic syndrome diagnosis. However, QUICKI and G/I ration showed the lowest AUC for detection of metabolic syndrome. It is hoped that the potential “HOMA-TG index” may provide better diagnostic efficiency for diagnosing metabolic syndrome.http://link.springer.com/article/10.1186/s13098-019-0439-5Insulin resistanceHOMAIRHOMA2QUICKIG/I ratioFasting Insulin Resistance Index (FIRI)
collection DOAJ
language English
format Article
sources DOAJ
author Sikandar Hayat Khan
Ali Nawaz Khan
Nayyer Chaudhry
Roomana Anwar
Nadeem Fazal
Muhammad Tariq
spellingShingle Sikandar Hayat Khan
Ali Nawaz Khan
Nayyer Chaudhry
Roomana Anwar
Nadeem Fazal
Muhammad Tariq
Comparison of various steady state surrogate insulin resistance indices in diagnosing metabolic syndrome
Diabetology & Metabolic Syndrome
Insulin resistance
HOMAIR
HOMA2
QUICKI
G/I ratio
Fasting Insulin Resistance Index (FIRI)
author_facet Sikandar Hayat Khan
Ali Nawaz Khan
Nayyer Chaudhry
Roomana Anwar
Nadeem Fazal
Muhammad Tariq
author_sort Sikandar Hayat Khan
title Comparison of various steady state surrogate insulin resistance indices in diagnosing metabolic syndrome
title_short Comparison of various steady state surrogate insulin resistance indices in diagnosing metabolic syndrome
title_full Comparison of various steady state surrogate insulin resistance indices in diagnosing metabolic syndrome
title_fullStr Comparison of various steady state surrogate insulin resistance indices in diagnosing metabolic syndrome
title_full_unstemmed Comparison of various steady state surrogate insulin resistance indices in diagnosing metabolic syndrome
title_sort comparison of various steady state surrogate insulin resistance indices in diagnosing metabolic syndrome
publisher BMC
series Diabetology & Metabolic Syndrome
issn 1758-5996
publishDate 2019-06-01
description Abstract Background Insulin resistance is core cause of metabolic syndrome. Determining insulin resistance is one of the foremost requirements imperative to understanding the pathophysiology of disease. The gold standard “Euglycaemic clamp test” is cumbersome, long and non-feasible in routine clinical setups to diagnose metabolic syndrome. Various continuous and steady state insulin resistance indices are now available in literature. We plan to evaluate commonly utilized steady state insulin resistance indices directly and Homeostasis Model Assessment for Insulin Resistance (HOMAIR) with added triglyceride (HOMA-TG index). Methods The cross-sectional study was carried from Jan-2016 to Dec-2018 at PNS HAFEEZ and department of chemical pathology, AFIP with following objectives: (1) To evaluate steady state insulin resistance markers for diagnosing metabolic syndrome as per IDF defined criteria by ROC curve analysis, (2) to measure Kendal Concordance between various insulin resistance indices and (3) to correlate steady state insulin resistance markers with anthropometric and lipid indices. After several exclusions we selected 224 subjects based upon “non-probability convenience sampling” for inclusion in study. Clinical history, anthropometric measures were calculated and sampling was done for insulin, glucose and other biochemical parameters. Metabolic syndrome was diagnosed as per IDF criteria, while HbA1c was utilized to diagnose diabetes mellitus. Pearson correlation was used to correlate various steady state insulin resistance indices including HOMAIR, HOMA2 index, QUICKI, G/I ratio, HOMA-TG index and serum insulin. AUC was calculated by ROC analysis for all surrogate insulin measures in diagnosis of metabolic syndrome. Results “HOMA-TG index” has shown the highest AUC for diagnosing metabolic syndrome along with higher correlation with lipid markers and anthropometric indices in comparison to other steady-state insulin resistance markers. Furthermore, QUICKI and G/I ratio showed the lowest AUC for detection of metabolic syndrome. Conclusion “HOMA-TG index” has shown highest AUC for metabolic syndrome diagnosis. However, QUICKI and G/I ration showed the lowest AUC for detection of metabolic syndrome. It is hoped that the potential “HOMA-TG index” may provide better diagnostic efficiency for diagnosing metabolic syndrome.
topic Insulin resistance
HOMAIR
HOMA2
QUICKI
G/I ratio
Fasting Insulin Resistance Index (FIRI)
url http://link.springer.com/article/10.1186/s13098-019-0439-5
work_keys_str_mv AT sikandarhayatkhan comparisonofvarioussteadystatesurrogateinsulinresistanceindicesindiagnosingmetabolicsyndrome
AT alinawazkhan comparisonofvarioussteadystatesurrogateinsulinresistanceindicesindiagnosingmetabolicsyndrome
AT nayyerchaudhry comparisonofvarioussteadystatesurrogateinsulinresistanceindicesindiagnosingmetabolicsyndrome
AT roomanaanwar comparisonofvarioussteadystatesurrogateinsulinresistanceindicesindiagnosingmetabolicsyndrome
AT nadeemfazal comparisonofvarioussteadystatesurrogateinsulinresistanceindicesindiagnosingmetabolicsyndrome
AT muhammadtariq comparisonofvarioussteadystatesurrogateinsulinresistanceindicesindiagnosingmetabolicsyndrome
_version_ 1724473725752967168