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To perform the analysis, blood glucose samples are obtained and each sample is divided and measured by two meters: a "reference method" (a meter or laboratory test known to produce accurate results); and a new meter being evaluated.
IR is insulin resistance and %β is the β-cell function (more precisely, an index for glucose tolerance, i.e. a measure for the ability to counteract the glucose load). Insulin is given in μU/mL. [7] Glucose and insulin are both during fasting. [2] This model correlated well with estimates using the euglycemic clamp method (r = 0.88). [2]
The simulated blood glucose profile is shown in the upper graph, and the carbohydrate intake and insulin injections are shown in the lower graph, with the simulated plasma insulin profile shown superimposed on the lower graph. The missed usual insulin injection is shown highlighted in yellow.
The model equations follow the principles of mass transport, fluid dynamics, and biochemistry in order to simulate the fate of a substance in the body. [9] Compartments are usually defined by grouping organs or tissues with similar blood perfusion rate and lipid content (i.e. organs for which chemicals' concentration vs. time profiles will be similar).
AGP provides both graphic and quantitative characterizations of daily glucose patterns. First developed by Drs. Roger Mazze and David Rodbard, [1] with colleagues at the Albert Einstein College of Medicine in 1987, AGP was initially used for the representation of episodic self-monitored blood glucose (SMBG). The first version included a glucose ...
The glucose tolerance test was first described in 1923 by Jerome W. Conn. [4]The test was based on the previous work in 1913 by A. T. B. Jacobson in determining that carbohydrate ingestion results in blood glucose fluctuations, [5] and the premise (named the Staub-Traugott Phenomenon after its first observers H. Staub in 1921 and K. Traugott in 1922) that a normal patient fed glucose will ...
The standard definition of a reference range for a particular measurement is defined as the interval between which 95% of values of a reference population fall into, in such a way that 2.5% of the time a value will be less than the lower limit of this interval, and 2.5% of the time it will be larger than the upper limit of this interval, whatever the distribution of these values.
For example, when measuring a hormone concentration in the blood, its secretion rate can be estimated by deconvolution. Another example is the estimation of the blood glucose concentration from the measured interstitial glucose, which is a distorted version in time and amplitude of the real blood glucose. [7]