Chronic Kidney Disease or CKD is defined as a persistent reduction in renal
function over 3 months period along with biochemical or structural abnormalities or an
absolute estimated glomerular filtration (eGFR) rate < 60 ml/min/1.73 m2 over 3
months with or without abnormalities. In practice, precise knowledge of the GFR is not
required and CKD can be adequately monitored by eGFR using estimating equations.
CKD is an important confounder in the outcomes of several diseases, particularly
Diabetes Mellitus (DM), Cardiovascular Diseases (CVD) and Obesity. There is paucity
of data using CKD as a primary outcome variable in randomized clinical trials, as a
result most guidelines in this area are based on secondary analysis, observational
studies or have inadequate sample sizes. The prevalence of CKD is important not only
at an individual level to guide clinicians for proper management of their other illnesses
but also at a population level for the purposes of all-inclusiveness in the design of
clinical trials. The inclusion of individuals with CKD in emerging studies will allow us
to address whether or not CKD plays a vital confounding role on many disease
outcomes.
In order to get a good grasp on the epidemiology of CKD, an epidemiology
collaborative equation called CKD-EPI equation is most widely utilized. This equation
has its strength in being validated in several populations and estimates glomerular
filtration rate (GFR) based on several demographic factors and serum creatinine. The
National Health and Nutrition Examination Survey (NHANES) conducted by the
National Center for Health Statistics (NCHS) collects health data on noninstitutionalized
individuals in the United States via interviews, laboratory tests and
examinations [1] has given us the needed information on the Epidemiology of CKD in
the US. These surveys utilize CKD-EPI equation to quantify the statistical data on
CKD trends.
Keywords: Chronic Kidney Disease, Diabetes, Epidemiology, Obesity.
