Glucose data

Patients and clinicians can evaluate blood glucose control through a combination of self-monitoring of blood glucose data and hemoglobin HbAlc testing. 

The closed-loop system (often termed the artificial pancreas ) is essentially a more sophisticated version of the system described above. It consists not only of a pump and infusion device, but also of an integral glucose sensor and computer that analyses the blood glucose data obtained and adjusts the flow rate accordingly. The true potential of such systems remains to be assessed. 

A second, simple measure of variability is the inter-quartile range that is the interval between the upper and lower quartiles. The upper quartile of a set of data is that value that is less than 25% of the data and greater than 75% similarly, the lower quartile is the value that is greater than 25% of the data and less than 75%. For the blood glucose data the lower quartile is 3.6 mmol / Land the upper quartile 4.55 mmol/L, giving an interquartile range of 0.95 mmol/L. 

For the blood glucose data the variance is 0.488 and the standard deviation 0.698. 

Scheme 6 Examples of the equilibrium between keto and hydrate forms in aqueous solution, including the respective 13C NMR shifts of the carbonyl/hydrate atoms. Glucose data from [44]...

To give a flavor of the Bayesian approach, two summaries of the Bayesian analysis of the glucose data are now presented. A more detailed analysis, including a discussion of prior distributions and computational methods, is given in Section 5.2. 

To illustrate the impact of the choice of the tj, two examples are considered first, a simulated example and then the glucose data. 

In Figure 5(a), a similar plot is given for the glucose data, where the model contains the subset of active effects BL, Hi, Bq, Hq, BlHl, BlHq, BqHl, BqHq. Close inspection of this plot reveals a problem the posterior mean of Yj converges... 

Figure 5. Glucose data Predicted response at each of the 18 design points of Table 2 for various multiples of the default xy default values of Cj and xj are calculated (a) from equations (20) and (b) from equations (21). The model used has active effects BL, HL, Bq, Hq, BlHl, BlHq, BqHl, BqHq.

The main results of the analysis of the glucose data have already been presented in Section 1.1. Details of the hyperparameter choices, robustness calculations, and estimation of the total probability visited by the MCMC sampler are given here. 

Figure 13- Pyranose-2-oxidase. The effect of increasing concentrations of 3-deoxy-3-fluoro-D-glucose on the activity of the enzyme toward glucose. glucose only in the presence of H5 mM, A 10 mM, 15 mM 3 deoxy-3-fluoro-D-glucose. Data obtained as in Figure 11. V, micromol/min/mg protein S, glucose conentration (mM).

As indicated in Chapter 22, batch processes can benefit from recipe modifications in between consecutive batches or cycles, using a run-to-run (RtR) strategy. Run-to-run control strategies have also been developed for diabetes control, by considering glucose data for a meal response or an entire day to be the batch of interest. The similarities between the diabetic patient and the batch reactor recipe that motivate the application of this technique are the following ... 

Mazze RS, Strock E, Wesley D, Borgman S, Morgan B, Bergenstal R, Cuddihy R (1987) Ambulatory glucose profile representation of verified self-monitored blood glucose data. Diabetes Care 10(1) 111-117... 

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