The Laws of Small Numbers 1,2,3

 or

How To Have Tight Control Without Hypoglycemia 

"Big inputs make big mistakes; small inputs make small mistakes."  

 Over the next couple of weeks I will give you the tools to understand and teach the Laws of Small Numbers.  This week I will explain the importance of small numbers and how to begin to achieve blood sugar predictability.  We will start with The Law of Carbohydrate Estimation and in the next article we will discuss “The Law of Insulin Dose Absorption”,  “The Law of Insulin Timing” and finally “Obeying the Laws of Small Numbers” 

PART 1

 "Big inputs make big mistakes; small inputs make small mistakes."

 That is the first thing my friend Kanji Ishikawa says to himself each morning on arising. It is his mantra, the single most important thing he knows about diabetes.

Kanji is the oldest surviving Type I diabetic in Japan (he is, by the way, younger than I, but afflicted with numerous long-term diabetic complications because of many years of uncontrolled blood sugars). 

Many biological and mechanical systems respond in a predictable way to small inputs but in a chaotic and considerably less predictable way to large inputs. Consider for a moment traffic. Put a small number of automobiles on a given stretch of highway, and traffic acts in a predictable fashion: cars can maintain speed, enter and merge into open spaces, and exit with a minimum of danger. There's room for error. Double the number of cars, and the risks don't just double, they increase geometrically. Triple or quadruple the number of cars, and the unpredictability of a safe trip increases exponentially. 

The name of the game for the diabetic in achieving blood sugar normalization is predictability. It's very difficult to use medications safely unless you can predict the effect they'll have. Your patients can't normalize blood sugar unless they can predict the effects of what they are eating. 

If your patients can't accurately predict blood sugar levels, then they can't accurately predict their insulin needs. If the kinds of foods your patient is eating give continuously unpredictable blood sugar levels, then it will be impossible to normalize blood sugars. 

One of the prime intents of this article is to give you the information your patients need to learn how to predict  blood sugar levels, and to learn how to ensure that their predictions will be accurate. Here the Laws of Small Numbers are exceedingly important. 

 Predictability. How does your patient achieve it?

The Law of Carbohydrate Estimation

 The old ADA dietary recommendations allowed 150 grams of carbohydrate per meal. This, as you may know by now, is grossly excessive. Here is one reason why.

Typically, 150 grams of carbohydrate would be a good-sized bowl of cooked pasta. Let's say that your patient is a whiz at estimating the amount of carbohydrate in the pasta and can usually estimate it to within 20 percent from one day to the next. Twenty percent of 150 grams is 30 grams of carbohydrate. Now, if your patient is a non obese Type I diabetic who makes no insulin, 1 gram of carbohydrate will raise her blood sugar by about 5 mg/dl. So, even with a finely tuned ability to "guesstimate" the amount of carbohydrate, your patient’s blood sugar is off by a whopping ±150 mg/dl for just this one meal. If your patient’s target blood sugar level is approximately 90 mg/dl, she’s now got a blood glucose level of 240 mg/dl, or, alternately, 0 mg/dl. Either situation is clearly unacceptable. If a 20 percent margin of error is one’s average, then there will be some days your patient is off by only 10 percent, but others when off by 30 percent. 

Let's try another example. Say your patient is a Type 2 diabetic, obese, and makes some insulin of his own but also injects insulin. You've found that 1 gram of carbohydrate only raises his blood sugar by 3 mg/dl.  His blood sugar would then be off by ±90 mg/dl. If your patient’s target blood sugar value is, say, 90 mg/dl, you're looking at a post meal blood sugar level of anywhere from 180 mg/dl to 0 mg/dl. 

That's the chief problem with the old ADA diet. Big inputs. But if your patients can eat food that will affect their blood sugar by one-thirteenth of that margin of error, then they are going to have a much simpler time of normalizing blood sugar levels. My diet plan aims to keep these margins in the realm of about 10–20 mg/dl. How do we accomplish this? Small inputs. 

Eating only a quarter-cup of pasta is not the answer. Even small amounts of some carbohydrate can cause big swings in blood sugar. And anyway, who would feel satisfied after a meal of a quarter-cup of pasta? The key is to eat foods that will affect blood sugar in a very small way. 

Small inputs, small mistakes. Sounds so simple and straightforward, so elegant, it may make your patients want to ask why no one has told them about it before. 

Say that instead of eating pasta as the carbohydrate portion of their meal, they eat salad. If they estimate 2 cups of salad at 12 grams of carbohydrate and are off not by their usual 20 percent but by 30 percent, that's still an uncertainty of only four grams of carbohydrate—a maximum potential 20 mg/dl rise or fall in blood sugar. A bowl of pasta for a couple of cups of salad? Not much of a trade, you may say. Well, we don't intend that your patients starve. As they decrease the amount of fast-acting carbohydrate they eat, your patients can often simultaneously increase the amount of protein consumed. 

 Protein can, as you may recall, also cause a blood sugar rise, but this takes place much more slowly, to a much smaller degree, and is more easily prevented with medication.  In theory, your patients could weigh everything eaten right down to the last gram and make their calculations based on information provided by the manufacturer or derived from some of the books we use. Still, there are problems with that approach. Say they weigh dried pasta—the manufacturer's estimate of how much carbohydrate exists in a serving is exactly that, an estimate, with a margin for error. The Food and Drug Administration allows for a margin of error in labeling of +20%.  And there are other variables—some pastas are made with egg yolks and wheat flour, some with water and durum semolina flour. If the manufacturer's estimate proves to be off by 20 percent, and then your patient’s estimate is off by 20 percent, you're in a realm of big time blood sugar problems. He will have only a vague idea of what is really consumed, and of the effect it will have on blood sugar. 

The idea here is to stick with low levels of carbohydrates. In addition, stick with foods that will make your patients feel satisfied without causing huge swings in blood sugar. Simple. 

In my next article in 2 weeks I will explain The Law of Insulin Dose Absorption,  The Law of Insulin Timing and finally, e weeks hereafter,  “Obeying the Laws of Small Numbers”