Appendix C: Sample Decision Trees
Sample Decision Tree: Insulin-Dependent Diabetes
Below you will find sample decision trees for a person living with type 1 diabetes and a person living with type 2 diabetes. These are basic examples to illustrate the fundamentals of how to use a decision tree. Your initial decision trees may be more complex and you may have more data to document, which will require a second page to complete a full day. The more detailed you are in this process, the more you will benefit.
Let’s walk through a sample for an insulin-dependent person living with type 1 diabetes and evaluate each decision together. Jim uses Lantus as a long-acting insulin and Humalog as a fast-acting insulin.
Jim wakes up.
5:30 A.M. —Jim wakes up with a fasting blood glucose of 105 mg/dL. He injects 1 unit to treat the dawn phenomenon.
Jim prepares for exercise.
6:15 A.M. —Jim tests his blood glucose before a cycling class, and he is at 110 mg/dL. He eats 1 medium banana, which has 30 grams of carbohydrate, and injects 0.5 unit of Humalog insulin. He chooses to under-inject insulin given that he is about to exercise and he predicts that his pre-exercise carbohydrate-to-insulin ratio is 60:1.
6:30 A.M .—Jim starts a 45-minute cycling class.
Jim is finished with exercise.
7:30 A.M .—While talking with friends and stretching, Jim measures his post-exercise blood glucose to be 115 mg/dL. It’s time to prepare for eating breakfast.
Jim prepares to eat breakfast.
8:45 A.M —Seated at his desk to start the workday, Jim calculates his breakfast meal to contain approximately 175 grams of carbohydrate from bananas, mangoes, and apples. He predicts that a 25:1 carbohydrate-to-insulin ratio is the correct insulin sensitivity after exercise, and injects 7 units of fast-acting insulin 15 minutes before he eats (following our insulin timing strategies, on this page ).
9:00 A.M .—Jim measures his blood glucose and it is 130 mg/dL. He is confused why his blood glucose is on an upward trend. He patiently waits for the insulin he injected 15 minutes ago to start working.
9:15 A.M .—Jim measures his blood glucose again at 118 mg/dL. Given that he is under 120 mg/dL and trending down, he begins eating his breakfast.
Jim checks his blood glucose two hours after breakfast.
11:30 A.M .—Two hours after he is done eating, Jim measures his blood glucose at 126 mg/dL. He is excited because his predicted breakfast carbohydrate-to-insulin ratio of 25:1 worked well.
Jim prepares to eat lunch.
12:30 P.M .—Jim is ready to eat lunch, which he brought from home, so he knows it contains 150 grams of carbohydrate. His blood glucose is 120 mg/dL. His predicted carbohydrate-to-insulin ratio is 25:1 at lunch, so he injects 6 units of fast-acting insulin.
12:45 P.M .—Jim’s blood glucose is 105 mg/dL. Since he is under 120 mg/dL and trending downward, he begins eating immediately.
Jim checks his blood glucose two hours after lunch.
3:30 P.M .—Jim measures his blood glucose at 200 mg/dL. He suspects it’s high because of an adrenaline rush owing to a very important presentation he’ll be delivering to his boss and colleagues. Jim takes a 1 unit fast-acting insulin correction bolus.
Jim prepares to eat dinner.
6:00 P.M .—Jim is home and ready to eat dinner. His blood glucose is 111 mg/dL and his dinner contains 115 grams of carbohydrate energy. Jim knows that he tends to be more insulin sensitive in the evening, so he injects with a predicted carbohydrate-to-insulin ratio of 32:1 and injects 3.5 units of fast-acting insulin.
6:15 P
.M .—Jim starts to enjoy his delicious dinner after waiting for 15 minutes to allow insulin to start working.
Jim corrects hypoglycemia.
7:45 P.M .—90 minutes after Jim started eating his dinner, he feels shaky. He measures his blood glucose at 65 mg/dL and eats 1 Medjool date to recover. He writes down that he consumed 15 grams of carbohydrate energy. In 15 minutes he feels great. Now Jim can calculate his actual carbohydrate-to-insulin ratio, which is 115 + 15 / 3.5 = 37. Tomorrow when he injects bolus insulin for his dinner meal, he will inject at a 37:1 ratio rather than the 32:1, which led to hypoglycemia today.
Jim prepares for bed.
10:00 P.M .—Before going to bed, Jim injects 14 units of long-acting insulin. He also measures his blood glucose at 98 mg/dL and is confident that his blood glucose will remain steady throughout the night.
Sample Decision Tree: Non-Insulin-Dependent Diabetes
Veronica is living with type 2 diabetes and uses oral medications to manage her blood glucose, cholesterol, and blood pressure.
She tests her blood glucose only twice per day, as we suggested in chapter 9.
She does not monitor her calorie intake; instead she pays attention to her hunger signals for guidance about how much and how often to eat.
She eats delicious nutrient-dense meals and documents her total carbohydrate and total fat intake on her decision tree to ensure that the food she is eating does not exceed our recommendations for maximum insulin sensitivity.
Veronica wakes up.
6:30 A.M .—Veronica wakes up with a fasting blood glucose of 173 mg/dL and is happy that it is lower than yesterday’s fasting blood glucose of 205 mg/dL.
Veronica exercises.
7:30 A.M .—Veronica starts a 45-minute group fitness class.
Veronica eats breakfast.
9:00 A.M .—Veronica eats a Refreshing Fruit Delight , ensuring that her total fat intake is less than 10 grams at any given meal. She takes 1,000 mg of metformin (oral diabetes medication), 10 mg of lisinopril (an oral high blood pressure medication), and 25 mg of Crestor (an oral cholesterol-lowering statin medication).
Veronica eats lunch.
12:30 P.M .—Veronica eats the Sweet Potato Bake .
3:30 P.M .—Veronica eats a snack of 2 apples at the office.
Veronica eats dinner.
6:00 P.M .—Veronica returns home and eats one of her favorite dinners, the Pad Thai Zoodles with Ginger Sauce , which has 9 grams of fat. She also takes 1,000 mg of metformin with her dinner.
Veronica goes for a walk.
7:00 P.M .—About 30 minutes after she has finished eating, Veronica goes for a walk with her kids to get her heart rate up for 15 minutes.
Veronica prepares for bed.
10:00 P.M .—Before going to bed, Veronica measures her blood glucose at 122 mg/dL.
Acknowledgments, Mastering Diabetes
Acknowledgments
Cyrus: I would like to acknowledge my wife, Kylie Buckner, for her relentless dedication to improving the lives of thousands of people around the world, for the brilliance that she brings to my life, and for helping to improve the quality of information in this book.
I would also like to thank my mom for preparing a home-cooked lunch for me every day from the first day of kindergarten through the last day of high school, with zero exceptions.
Her dedication to grocery shopping, meal planning, and feeding me real food did not go unnoticed for even one day, and many of my habits today are a result of her unending desire to eat real food.
I would also like to thank my dad for getting me addicted to mangoes from the Indian market at a young age, and for always encouraging me to higher education.
I’d like to thank my sister Persis for opening my eyes to being a vegetarian from a young age, for starting my addiction to green peas, and for always encouraging me to challenge the status quo.
I’d like to thank my sister Shanaz for being the first person to figure out that I had type 1 diabetes, and for setting the example of what it means to work hard and always strive for excellence in the medical profession.
And last but certainly not least, I’d like to thank my adorable and silly kittens, Mew and Blu, for always keeping me company, for making me laugh, and for allowing me to be your dad.
I would be nothing without my family, so thank you for all that you’ve done to make me who I am today.
Robby: I would like to acknowledge my parents, Paul and Peggie Barbaro. Thank you for your unconditional love and unwavering support. My upbringing has set me up for success and true fulfillment. I am eternally grateful for your encouragement to pursue whatever is in my heart.
The encouragement and support I have received from family and dear friends throughout the book-writing process have meant the world to me. My sincere thanks to Adam Sud, Ally Ertel, Ashley and Britton Foster, Casey and Phil McCluskey, John Pierre, Melissa Pampanin, PJ Barbaro, Setareh Khatibi, Steve and Sara Cunning, Sterling Phillips, and Tara Kemp.
Anthony William, your presence and belief in me from the beginning of my diabetes coaching career have lifted me up along the way. Thanks for the many ways you’ve expanded my horizons, and especially for instilling hope in me and millions of others.
Brian Wendel, my respect for you is immense. Your true friendship and mentorship have shaped who I am and influenced me in immeasurable ways.
Taylor Call, your wisdom, guidance, and faith mean everything. Thank you.
Last but certainly not least, I want to express my gratitude for Cyrus. You are the best partner I could ever ask for, in a million ways and more. Your commitment to excellence and scientific rigor inspire me daily. Plus, you’re the most fun and brilliant human I’ve ever met!
We would both like to acknowledge the incredible team of talented people who have supported Mastering Diabetes from the time it began. Without their efforts, this book would simply not exist, and because of that we feel indebted to them for their hard work and dedication to changing the lives of thousands of people around the world. This list of exceptional individuals includes Adam Sud; Alex MacDowell; Chelsea Morrisey; Clay Crenshaw; Dave Rogenmoser; Heather Brock; Heather Harden; Ioana Pasarin; Jamie Marie Koonce; Janis Donnaud; Jessica Stidham; Jewels Christine; Jonny Morelli; Jose Roman; Jose Tejero; Kylie Buckner, RN, MSN; Sam and Josh Ovett; Shelly Nason, PhD; Laurie Masters; Lindsay Garcia; Mariela Artega; Marc Ramirez; Navin Gupta; Rachel Kersten; and Tara Kemp.
We would also like to acknowledge the doctors, experts, pioneers and health professionals whose contributions have set a strong foundation for our work:
Alona Pulde, MD; Alan Goldhamer, DC; Angie Sadeghi, MD; Anthony Lim, MD; Brenda Davis, RD; Caldwell B.
Esselstyn Jr., MD; Caroline Trapp, DNP; Chef AJ; Chris Wark; Clint Paddison; Columbus Batiste, MD; David Katz, MD, MPH; Dan Buettner; Danielle Belardo, MD; Dean Ornish, MD; Dean and Ayesha Sherzai, MD; Doug Lisle, PhD; Doug Graham, DC; Dustyn Williams, MD; Garth David, MD; Gemma Newman, MRCGP; Hans Diehl, DrHSc, MPH; Jane Esselstyn, RN; Julieanna Hever, RD; Laurie Marbas, MD; Marc Hellerstein, MD, PhD; Matthew Lederman, MD; Mauricio González, MD; Michael Greger, MD; Michael Klaper, MD; Michelle McMacken, MD; Monica Aggarwal, MD; Nancy Bohannon, MD; Neal Barnard, MD; Jay Sutliffe, PhD; Jeff Novick, MS, RDN; Jim Loomis, MD; John McDougall MD; Joel Fuhrman, MD; Joel Kahn, MD; Ray Cronise; Rick Dina, DC; Rip Esselstyn; Robert Ostfeld, MD; Ron Weiss, MD; Rosane Oliveira, PhD; Scott Stoll, MD; Steve Lawenda, MD; Susan Peirce Thompson, PhD; Susan Levin, MS, RD; T.
Colin Campbell, PhD; Thomas Campbell, MD; Ocean Robbins; Valter Longo, PhD; Will Bulsiewicz, MD; and William Gibson, MD.
Index, Mastering Diabetes
Index
The page numbers in this index refer to the printed version of this book. The link provided will take you to the beginning of that print page. You may need to scroll forward from that location to find the corresponding reference on your e-reader.
Page numbers in italic refer to charts or illustrations. “MDM” throughout refers to the Mastering Diabetes Method.
A1c (blood test), 90 , 137 , 149 –51, 187 ,
acute coronary events, 74
adipose tissue
and carbohydrate-centric diabetes model,
entrance of fatty acids,
, 54
inflammation, 54 ,
, 56