Are there any statistical/mathematical indicators that can be used to analyze glucose readings and insulin usage beside the standard min/max, average, standard deviation, variance? Has anyone used regression analysis effectively?
This question was referred to several members of the Diabetes Team, who have each given an answer:
Answer from Dr. O'Brien:There are several groups especially in Britain and in the U.S. that are trying to devise computer programs that can analyse blood glucose data together with information on diet and exercise to more accurately anticipate insulin needs and thus improve control. There are basically three approaches.
The first would be to establish a data base over a fairly long period and then develop a 'macro' which would rapidly extract similar settings and hopefully suggest the best dose of insulin in those circumstances. This is expensive and time consuming and inappropriate for young people whose growth and appetite parameters are changing.
Another system for which there limited evidence of benefit is called 'Teledoc' and involves calling in blood sugars to a central computer using an 800- or local number. Essentially it uses algorithms for sliding scales. The present model looks well adapted to the 'managed care' situation where clinic time is limited. Physicians and nurses don't always like surrendering personal relationship and patients have had problems with the mechanical approach too.
A third approach, and I don't know if it has been actually tried in practise yet, is to use the complex mathematics of fuzzy logic to see if there is any individual pattern to how blood sugars vary in relation to insulin dose, carbohydrate intake, exercise and stress. Many mathematicians say that it is chaotic; but if it could be worked out it might be possible to calculate insulin doses much more accurately than we do now.
All of these systems are experimental at the moment.
Answer from Dr. Robertson:I think Dr. O'Brien's answer is comprehensive. All that I can add is that there is quite a lot of work going on in the areas of fuzzy logic and probabilistic mathematical theory. I was at a computing conference in Austria a few weeks ago and heard about some of this work. I don't pretend to understand it but some potentially useful computer tools are evolving. What is striking, however is that all such systems ignore the big variable - patients that can't comply exactly with prescribed therapy.
I suppose what I'm saying is that the best and most accurate computer models can only offer support to patients who are truly motivated, and they are already relatively easy to assist.
Original posting 5 Nov 96
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