IJRR

International Journal of Research and Review

| Home | Current Issue | Archive | Instructions to Authors | Journals |

Original Research Article

Year: 2018 | Month: March | Volume: 5 | Issue: 3 | Pages: 136-142

Estimation of Fasting Plasma Glucose, Fasting Insulin Levels and Insulin Resistance in Metabolic Syndrome

Dr. Sunita Manhas1, Dr. Shikhaa Mahajan2, Dr. Suvarna Prasad3, Anit Lamichhana4, Dr. Richa Goel5

1Assistant Professor, 2Associate Professor, 3Professor and Head, 4PhD Student, 5Senior Resident,
Department of Biochemistry. M.M.I.M.S.R, Mullana, Ambala, Haryana, India.

Corresponding Author: Dr. Shikhaa Mahajan

ABSTRACT

Introduction: A group of metabolic disorders like central obesity, insulin resistance, increased insulin level, impaired glucose homeostasis, dyslipidemia, raised blood pressure and low grade chronic inflammation is defined as metabolic syndrome. It is a complex disorder and an emerging clinical challenge which is associated with 2 fold increase in CVD risk and 5 fold increase in T2DM.
Materials and methods: Hundred clinically diagnosed patients with Metabolic Syndrome and fifty controls were selected for the study
Results: Fasting Plasma Glucose, Fasting Plasma Insulin, Mean HOMA-IR of patients with metabolic syndrome were significantly higher as compared to healthy controls. 61% of patients with metabolic syndrome were with severe insulin resistance consisting 38% of male and 23% of female. 18% cases were found to be with moderate insulin resistance including 11% male and 7% female. Whereas 21% of the patient with MetS were with normal insulin resistance. ROC Curve was analysed for HOMA-IR in predicting metabolic syndrome and specificity and sensitivity was calculated which came out to be87% and 100% respectively.
Conclusion: Diagnosing metabolic syndrome and assessing HOMA-IR shows the status of insulin resistance thereafter may guide in assessing the risk of development of T2DM and CVD in patients with metabolic syndrome.ROC curve further helps in early diagnosis of metabolic syndrome using a single parameter with specificity and sensitivity of 87% and 100% respectively which is more practical against the other criteria used for diagnosing metabolic syndrome.

Key words: Metabolic Syndrome, Fasting Insulin, Insulin resistance, plasma Glucose

[PDF Full Text]