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Everything you wanted to know about food & insulin*

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Presentation on theme: "Everything you wanted to know about food & insulin*"— Presentation transcript:

1 Everything you wanted to know about food & insulin*
Stephen W. Ponder MD, FAAP, CDE Scott & White Clinic Temple, Round Rock and College Station * And a bunch of other important stuff

2 One goal of diabetes care is managing glucose…
FLUX 15 seconds drift Hint: It takes TIME and PATIENCE!

3 Non-diabetic persons

4 It’s all about inflammation

5 Postmeal Blood sugars, A1c and CV Risk
chronic inflammation Vascular system 220 glucose HbA1c 180 8% 140 7% 100 45 seconds 6% 5% Pre-meal 2 hr Pre-meal Goal: improve post-meal control: BG < 180 mg/dl 95 ? 115

6 Insulin action opens the door for sugar (glucose) to leave the bloodstream
Cell I G Holding open a door photo here

7 Diabetes – an energy management disorder
This is T2, but forget about d-type for now.

8 Why do blood sugar levels shift all the time?
Out In Sugar level

9 present Reactive Proactive past future

10 reactive vs. proactive diabetes care
Actions predetermined Minimal to no flexibility: RIGID Outcomes don’t immediately affect long term actions Easy to teach/learn Less time needed Favors “concrete” thinking Less motivation needed Actions are dependent on situation/circumstance Flexible and adaptable Outcomes influence subsequent actions Training needed, plus ongoing reinforcement More time intensive Favors problem-solving Requires motivation

11 Food = energy Carbohydrates Protein Fat Glucose

12 (Glucose production – Glucose disposal) = FLUX
Here is a picture of FLUX

13 To manage flux Everything becomes a TOOL to understand, use, and master Food Insulin Exercise Timing Devices, etc….

14 If insulin keeps us alive, as does food, then why should one get more attention than the other?

15 Because… Most doctors are not nutrition specialists
Diagnosing and prescribing are what we’re trained to do Our health care system downplays the role of RD’s by not always paying for those services Plus WE think we’re all food experts anyway!

16 New paradigm: “Insulin keeps us alive while food helps keep us in control”

17 “A well trained mind is the greatest weapon against diabetes”

18 Diabetes care is not an action, it’s a process…like a recipe

19 Why does diabetes seem so slippery?
It’s like the weather But like weather, it can be predicted and prepared for In the end, it’s a self managed condition And outcomes are largely driven by choices

20 Point of diminishing returns?
“The good is the enemy of the perfect” Point of diminishing returns?

21 Tools to develop expertise with

22 Checking BG to fine tune? Or not?

23 Meters are commodity items “a commodity is the generic term for any marketable item produced to satisfy wants or needs” The best BG meter is the one you’ll use $10.41/50 strips Changes ahead Ketone meter

24 Don’t pass up an opportunity to correct a high (or low) BG
Choose what you consider “actionable”? BG above or below chosen thresholds Consider recent and impending actions Check your results with BG levels Repeat as necessary

25 Check your targets often
Make sure you hit your target “zone” sugar (± 30 mg/dl) Rapid-acting insulin results are best examined at 2-3 hours Results should feedback to the next attempt “Practice makes better”

26 Curb your liver! The liver makes as well as stores sugar
A proper insulin level “calms down” the liver Aim for an in-range sugar level (<120 mg/dl) upon waking up each day

27 Why do lows happen at night?
Hormonal patterns Lower insulin need Insulin peaks? Post-exercise effect Snacking stacking? Lower overnight insulin/add snack

28 D-teens count carbs POORLY
23% TitleThe carbohydrate counting in adolescents with type 1 diabetes (CCAT) study.AuthorsBishop, F. K.; Maahs, D. M.; Spiegel, G.; Owen, D.; Klingensmith, G. J.; Bortsov, A.; Thomas, J.; Mayer-Davis, E. J.Journal Diabetes Spectrum 2009 Vol. 22 No. 1 pp ISSN DOI /diaspect URL article reports pilot study results evaluating the accuracy of carbohydrate counting among adolescents with type 1 diabetes. This cross-sectional observational study included 48 adolescents ages years (mean 15.2±1.8 years) with type 1 diabetes of >1 year in duration (mean A1C 8.0±1.0%) who used insulin:carbohydrate (I:C) ratios for at least one meal per day. The adolescents were asked to assess the amount of carbohydrate in 32 foods commonly consumed by youths. Foods were presented either as food models or as actual food, with some items presented as standard serving sizes and some self-served by study participants. T-tests were used to assess the significance of over- or underestimation of carbohydrate content. For each meal, accuracy was categorized as accurate (within 10 grams), overestimated (by >10 grams), or underestimated (by >10 grams) based on the commonly used I:C ratio of 1 unit of insulin per 10 grams of carbohydrate. Only 23% of adolescents estimated daily carbohydrate within 10 grams of the true amount despite selection of common meals. For dinner meals, individuals with accurate estimation of carbohydrate grams had the lowest A1C values (7.69±0.82%, P=0.04). The pilot study provides preliminary evidence that adolescents with type 1 diabetes do not accurately count carbohydrates. Further data are needed on carbohydrate counting accuracy and other factors that affect glycemic control.

29 clinical dietitian (n.)
A person specializing in medical nutrition therapy. An underappreciated and underpaid member of the diabetes team. Someone who can help your left brain

30 We have > 60,000 thoughts daily
Eat at home Groups of thoughts comprise decisions The typical non-D person makes ~ 250 decisions a day about food How many more food choices does a PWD/CWD make? “What are we doing for dinner, dear?”

31 “You can delegate authority but you can’t delegate responsibility”

32 Do 2 RN’s = 1 kid? Ok? Ok to me! =

33 “Assuming a good working knowledge of the system, diabetes control is generally proportional to the time and attention directed towards it.”

34 Why do some PWD/CWD’s seem to have it “easier”
Why do some PWD/CWD’s seem to have it “easier”? It depends on your point of view “Honeymoon” Type 2 MODY? Other? Residual insulin…honeymoon. Early type 2 and weight loss lowers resistance…wrong diagnosis…MODY

35 It’s more than just food: the role of the gut

36 The pancreas has an “off” switch for insulin
…and it’s triggered by exercise

37 Kinetic versus Dynamic Insulin
Kinetic: how fast insulin gets in and out Dynamic: time that insulin lowers sugar Glucose infusion rate (mg/kg/minute) Time in hours

38 Current insulin pump therapy…
Early Insulin Pumps Current insulin pump therapy… Multi-dose insulin therapy “Think of insulin as a tool” Different tools for different jobs Lantus Levemir Humalog Novolog NPH Get my point? 70/30

39 The “3 dimensions” of insulin What is the 4th dimension?
peak onset duration

40 And the 4th dimension is: “consistency”
The final product 6 h 12 h 18 h 24 h

41 The 2013 “insulin arsenal” Long (Lantus, Levemir) Intermediate (NPH)
Fast (Regular) Rapid (Humalog, Novolog, Apidra) Premixed (75/25 and 70/30) Ultra-rapid? (in development) Ultra-long? (Degludec and others)

42 Comparing insulin actions

43 basal insulins are not very precise
Figure 2. Within-subject variability of insulin detemir, NPH insulin, and insulin glargine are graphically shown by the width of a prediction interval containing 95% of the predicted values. The prediction intervals illustrating day-to-day variability in the pharmacodynamic response are exemplified for a subject with the same mean response with any given treatment (insulin detemir, NPH insulin, or insulin glargine). A: A subject with a mean GIR over 24 h of 1 mg · kg-1 · min-1 has a probability to experience an effect of less than half the usual effect (i.e., <0.5 mg · kg-1 · min-1) of 0.5% using insulin detemir, 16% with NPH insulin, and 7% with insulin glargine. B: Similarly, for a subject with a maximum effect of 2 mg · kg-1 · min-1, the probability of experiencing a maximum effect of more than twice the usual level (i.e., >4 mg · kg-1 · min-1) will be 0.1% if the subject uses insulin detemir, 6% with NPH insulin, and 3% with insulin glargine. Note: a linear scale has been used in this figure to improve readability of values, and therefore the prediction intervals are not distributed symmetrically around the mean.

44 Levemir variability in 9 subjects
Figure 1. Individual time-action profiles (glucose infusion rates over time) of the first nine patients randomized to insulin detemir (A), NPH insulin (B), or insulin glargine (C). The four clamps in one subject are summarized in one plot. A low within-subject variability is indicated by the four lines in one plot being close to each other (e.g., subject no. 204), whereas major deviations between the time-action profiles in one subject (e.g., subject no. 224) shows a high within-subject variability.

45 Lantus variability in 9 subjects
Figure 1. Individual time-action profiles (glucose infusion rates over time) of the first nine patients randomized to insulin detemir (A), NPH insulin (B), or insulin glargine (C). The four clamps in one subject are summarized in one plot. A low within-subject variability is indicated by the four lines in one plot being close to each other (e.g., subject no. 204), whereas major deviations between the time-action profiles in one subject (e.g., subject no. 224) shows a high within-subject variability.

46 Insulin Pens Discreet Different needle sizes ½ unit increments
Disposable Durable units More popular today

47 This is why we site-rotate…

48 Timing of Bolus Insulin vs. GI or BG

49 Timing of Bolus Insulin
(humalog/novolog/apidra) High GI Moderate GI Low GI BG Above Target Range 30-40 min. prior 15-20 min. prior 0-5 min. prior BG Within Target Range 15-20 min. after BG Below Target Range 30-40 min. after

50 Why timing matters… Note: Carbs estimated w/pre-meal insulin.
Carbs known with post-meal insulin. Source: Clinical Therapeutics 2004; 26:

51 Why timing matters… CGMS data Bolusing with meal CGMS data
Bolusing pre-meal

52 Highs after meals depend on…
Size of the bolus How early bolus is given How many carbs eaten Activity level after meal Food’s glycemic index

53 Time to reach 100 mg/dl (at ~ 4 mg/dl/min)
420 4 mg/dl/min 340 260 Blood sugar 180 minutes

54 Fixing breakfast highs

55 Timely insulin facts Rapid insulin can’t lower BG any sooner than 20 minutes It peaks on average in about 1 h 15 min It’s mostly gone in 2-4 hours Maximum fall in BG is 4 mg/dl/min (rare)

56 Beware of delayed-action foods
Pizza Pasta/noodles Mexican foods Fried foods That slowly turn to sugar in body

57 “Fried-food revenge” and correction
BG = 194 6 unit 7AM BG = 115 in 3 hours Fried food earlier in 8PM

58 Proper meal planning ? ? ? ? carbohydrate counting ? ?


60 How does a “basal” insulin work?
Turns off or tones down sugar coming out of the liver Allows a reasonable amount of sugar to enter cells Keeps sugar levels steady or in balance between meals and snacks. Picture of a complex machine with many working parts capable of failing

61 Timing and consistency are essential to success

62 Exercise is the wild card since…
It can occur suddenly or unexpectedly It can last for different periods of time Intensity can shift up or down It’s hard to measure It’s impact on blood sugar can vary

63 Tools you have seen today…
The concept of FLUX Insulin onset, peak, duration, amount Macronutrients Fast, medium and slow carbohydrate effects The volatile role of exercise Role of amount, timing and consistency Increasing your assessment and analysis frequency The role of choice and persistence

64 “Good” control of diabetes is all about the journey, not the destination. Diabetes control exists largely “in the moment”

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