Insulin Resistance Syndrome; the challenges of diagnosis. | 16924
International Research Journals

International Research Journal of Biochemistry and Bioinformatics

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Insulin Resistance Syndrome; the challenges of diagnosis.


Maxwell Madueke Nwegbu

Insulin resistance syndrome (IRS) is a clinical condition that has continued to dominate clinical research and discourse in the past two decades. This stems from its associated role in a number of disease conditions which include cardiovascular disease, diabetes mellitus, polycystic ovary disease, steatohepatitis, obstructive sleep apnoea and some cancers. While there is consensus among many authorities on many of the clinical outcomes of IRS, though still evolving on a regular basis, there remains on-going debate as regards the diagnostic pre-requisites. This arises primarily because it is a cluster of risk factors and these factors are adjudged for propensity to cause disease based on certain levels or measurement cut-points. Unfortunately these cut-off levels of the risk factors are affected by other variables like race, sex, age and sometimes biases arising from outcomes of studies which are usually slanted towards a given clinical outcome, oftentimes cardiovascular disease or diabetes mellitus. Overtime five organizations have presented the most applied set of diagnostic criteria utilized in clinical practice and these include the National Cholesterol Education Program, World Health Organization, American Association of Clinical Endocrinologists, International Diabetic Federation and European Group for the study of Insulin Resistance. Although these set of criteria basically have common determinant parameters such as obesity, atherogenic dyslipidaemia, hypertension, insulin resistance, pro-inflammatory and prothrombotic states, they differ in the weightiness allotted to some parameters vis a vis IRS diagnosis. This review appraises these diagnostic criteria and highlights the inherent challenges in such multiplicity especially in our environment which ab initio, contributed little or nothing to the generation of the diagnostic cut-offs of the parameters.

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