Sugar Surfing™ Lesson #20 Covering the bases
Imagine you are an experienced and confident baseball shortstop. Your position on the field allows for lots of “in the moment” choices to be made during the game. You are continuously aware of the following: 1) the player at bat, 2) what you know about the batter’s hitting style and power, 3) the number of runners on base, their speed and quickness, 4) the game score at the moment, 5) number of outs, strikes and balls called, 6) the skills of the pitcher and your fellow players, 7) the playing conditions on the field and in the sky, 8) your unique abilities and experience, and perhaps even more.
A line drive ground ball streaks your way, slightly to your left. You quickly intercept it on the run. Next, your choice of where you throw the ball will be determined by several factors. Whether there is a runner on 3rd base, racing for home. Or…perhaps a double play if third base was empty and there is a runner already on 1st. These sorts of split-second decisions are prepared for and rehearsed in training.
The principles of dynamic decision making are similar between many sports and Sugar Surfing™. They only differ in their speed of execution. The Sugar Surfer has the added benefit of more time to choose her/his actions or omissions. Hopefully, Surfers choose wisely and use their results to gain experience for next time.
Fielders need choices
Ever since blood sugar meters came on the scene, rapid-acting insulin dosing for meals, snacks or out of range corrections has been approached as a basic math problem. First, someone provides a formula, ratio, or ‘sliding scale’. Next, the person plugs in ‘variables’ (blood sugar level and/or carbohydrate count) and voila the amount of rapid insulin to inject materializes.
Prior to blood sugar meters, a color chart was used to define the amount of sugar in a urine sample. That was all we had to estimate blood sugar levels. It was grossly indirect and backwards looking. It was also impossible to convert a color into a number which would be suitable for calculating an insulin dose in the moment. Therefore, we were assigned fixed daily insulin doses which were only changed by the doctor every few months.
Today, the blood sugar meter era is transitioning into the age of continuous glucose monitoring (CGM). With this revolution comes the need for a paradigm shift in our thinking about how to estimate a rapid acting insulin dose in response to a planned self-management situation (e.g., eating food), or in response to a sudden change in blood sugar conditions (e.g., “correct a high”).
Traditionally, rapid acting insulin dosing is based on a measured blood sugar level and/or an anticipated amount of food (usually but not always just the carbohydrate amount) to be eaten. Some people make dosing modifications for fat and protein. The data we input are one-dimensional (e.g., point in time glucose level, grams of carbs).
This contrasts with the dynamic nature of blood sugar ebb and flow as reflected in a CGM trendline. CGM users quickly discovered that old style insulin dosing management was like putting a mathematical square peg into a round hole. The equations into which these estimates are inserted were themselves rigid and unyielding. They do not consider changing (dynamic) conditions.
Anyone with type 1 diabetes who has worn a glucose sensor for a few days quickly realizes that blood sugars are in constant motion and can shift up and down capriciously. These shifting sugars may often defy your expectations based your understanding of how insulin and carbohydrates work within the body. Over time, you may start to question the value of the set of dosing equations you were assigned. These equations might have seemed to work at first. Yet, over time their effectiveness fell off.
As rigid ratio-based insulin dosing lost its luster, you might have started to question the static concept altogether. At first you might have concluded they were improperly assigned by the specialist at the last medical visit. Or, maybe you think you have just outgrown the last ratios given. Maybe the insulin itself is not working for some unknown reason. Maybe you miscounted