Timing of insulin bolus in patients with type 1 diabetes: effect on glucose control and variability using CGMS

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Introduction

Optimal glucose control reduces both micro- and macrovascular complica-tions in patients with type 1 dia-betes.1,2 The current recommended treatment to achieve optimal control is to mimic the physiologic insulin profile either by the basal-bolus method – i.e. the injection of basal insulin and a bolus injection of rapid acting insulin for every meal calcu-lated by carbohydrate counting – or by continuous insulin delivery with an insulin pump.3 Recently, it has become apparent that, although average glucose and HbA1c indicate glucose control, minimal glucose variability is also significant in pre-venting complications.4–6

Injecting the rapid acting insulin analogue bolus 5–15 minutes prior to the meal is the recommended method of achieving optimal glucose control due to the pharmacokinetic characteristics of these drugs.7 However, despite these recommenda-tions, it may be appropriate to inject

insulin immediately after the meal in order to prevent glucose excursions – especially when the amount of carbo-hydrates the patient intends to eat is unpredictable – or to enable a flexi-ble lifestyle. A few studies have investigated this issue and have demonstrated that injecting insulin immediately after the meal is satisfac-tory as well. These studies tested point glucose measurements 2–4 hours following a standardised meal, with a known content of carbohy-drates and fat,8–11or a non- standard-ised single meal.12In two studies,13,14 patients were instructed to inject the insulin for six to 12 weeks either before or after the meal and, at the end of the period, HbA1c, glu-cosamine and glucose measurements after one meal were documented.

A continuous glucose monitoring system (CGMS) enables recordings of glucose measurements every 5 minutes for several days and, as a consequence, it is possible to analyse average glucose, duration of hypo- and

Timing of insulin bolus in patients with

type 1 diabetes: effect on glucose control

and variability using CGMS

Abstract

The aim of this non-randomised, pilot study was to examine the effect of insulin bolus injection timing on overall daily glucose control and glucose variability using a continuous glucose monitoring system (CGMS).

Twelve patients with type 1 diabetes treated with either multiple daily insulin injections (MDI) or continuous subcutaneous insulin infusion (CSII), with HbA1c ≤7.5% (58mmol/mol), were connected twice to a CGMS for 72 hours. During period one the patients injected the insulin bolus before the meal and, during period two, after the meal. The variability of blood glucose (BG) was assessed by low BG indices (LBGI) and high BG indices (HBGI) – the measure of the variability of low and high BG readings. Their sum (LBGI + HBGI) gives the BG risk index (BGRI) – a measure of overall variability and deviations towards hypo- and hyperglycaemia.

Six patients were on CSII and six on MDI. The number of meals, number of insulin injections and average BG were not different between the groups. LBGI and the number of hypoglycaemic events were not affected by the method of injection. BGRI were significantly higher for post-meal injection, mainly due to increased hyperglycaemia (p=0.003). The increased HBGI and BGRI were more prominent in CSII (p=0.05). These differences were found for the 72-hour variability but not when testing 2 hours post-prandially.

It was concluded that injecting insulin prior to the meal can reduce the overall glucose variability, and remains the preferred method of injection. Larger studies are needed in order to reinforce these results. Copyright © 2012 John Wiley & Sons.

Practical Diabetes 2012; 29(3): 98–102

Key words

CGMS; glycaemic control; post-prandial glucose

Idit F Liberty

MD, Diabetes Unit, Soroka University Medical Center, Beer Sheva, Israel

Aviv Gelber

MD, Diabetes Unit, Soroka University Medical Center, Beer Sheva, Israel

Lena Novack

PhD, Epidemiology Department, Ben Gurion University of the Negev, Beer Sheva, Israel

Victor Novack

MD, PhD, Clinical Research Center, Soroka University Medical Center, Beer Sheva, Israel

Esther Boteach

Diabetes Unit, Soroka University Medical Center, Beer Sheva, Israel

Ilana Harman-Boehm

MD, Diabetes Unit, Soroka University Medical Center, Beer Sheva, Israel

Correspondence to:

Idit F Liberty, Diabetes Unit, Soroka University, Medical Center POB 151, Beer Sheva, Israel, 84101; email: iliberty@bgu.ac.il

Received: 15 January 2012

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hyperglycaemia and glucose variabil-ity.15Our non-randomised, pilot study aimed to examine the effect of the timing of prandial insulin injection, before or immediately after the meal, on overall daily glucose control and glucose variability using a CGMS. Patients and methods

Study population

Patients were recruited at the Soroka University Medical Center Diabetes Clinic, Beer Sheva, Israel. The study protocol was approved by the local Helsinki committee. All subjects signed an informed consent form prior to participation.

This study enrolled 16 patients aged ≥18 years who were diagnosed with type 1 diabetes and were treated with either multiple daily insulin injec-tions (MDI) or continuous subcuta-neous insulin infusion (CSII) for at least six months, and had a

docu-mented HbA1c≤7.5% (58mmol/mol)

within the three months preceding the enrolment. All patients reported using carbohydrate counting for calculating meal insulin dosage.

Research design

This study consisted of two periods, each of three days’ duration for each participant. During each period, the patients were connected to a CGMS for 72 hours. During the first period the patients were instructed to inject the insulin bolus precisely before the meal, and during the second period the patients were instructed to inject the insulin bolus immediately after the meal. Each of the periods lasted 72 hours, Monday to Thursday, for two consecutive weeks. The study was planned to take place during weekdays in order to eliminate the confounding effects of weekend meal patterns.

During the entire study period the patients were blinded to the glu-cose measurement results and were instructed to continue their routine self-monitoring of blood glucose (SMBG) and feed into the CGMS at least four measurements per day for calibration, as well as meal times and episodes of clinical hypoglycaemia. The participants maintained a food diary and recorded their carbohy-drate counting.

Throughout the study, patients maintained their usual daily routine

and insulin regimens which they had followed before the study.

Prior to study initiation, all patients took part in a workshop with a dietitian in order to reinforce carbohydrate counting skills. The patients were instructed to calculate their bolus dose in the same way, without considering the timing of injection.

At the end of the study, the participants filled out a satisfaction questionnaire devised for the study. This included five questions: patients’ satisfaction with each of the two injection times; whether the study changed their preference for injection time; what method they would recommend to others; and what, in their opinion, would prevent hypoglycaemic episodes and induce weight gain.

Measurements

The CGMS equipment was con-tributed by MiniMed Medtronic. The system includes MiniMed Sof-Sensor (Guardian) which uses a glucose oxi-dase reaction to determine interstitial glucose levels. The system measures and records glucose levels every 5 minutes and a total of 288 readings per day (Appendix 1 [available online at www.practicaldiabetes.com]). The sensor is inserted subcutaneously in the abdominal wall and is covered with a waterproof dressing.

Statistical methods: definition of endpoints

The measurements of blood glucose (BG) variability were defined as study primary endpoints which are broadly used for CGMS data assessment and have been recently reviewed by Clarke and Kovatchev.15

The variability of BG measure-ments was assessed by low BG indices (LBGI) and high BG indices (HBGI). LBGI is the measure of the frequency and extent of low BG readings, and HBGI is the measure of the frequency and extent of high BG readings. Their sum, LBGI + HBGI, gives the BG risk index (BGRI) – a measure of overall variability and deviations towards hypo- and hyperglycaemia. These values are especially suitable for non-symmetric distributions such as BG and have been validated in other studies.15

The low BG and high BG indices were further transformed into risk groups, a method also validated in other studies.

The exact steps of computing LBGI, HBGI and BGRI values follow the algorithm:15 • BG=1.509*((log(Glucose))^1.084-5.381). • rBG=10*(BG^2). • If BG <0 then rlBG=rBG; if BG >0 then rhBG=rBG; averages of rlBG per 1 hour and rhBG per 1 hour

Male gender 6/12 (50)

Age, yrs 12/12 (100) 49.3±14.0 23–71 51

Body mass index, kg/m2 12/12 (100) 27.0±3.7 20–34 27

Waist circumference, cm 12/12 (100) 92.6±12.4 75–121 90

HbA1c, % 12/12 (100) 6.8±0.6 6–8 7

Disease duration, yrs 12/12 (100) 22.1±11.6 2–40 22

Method (time) of insulin injection

Before meal 5/12 (41.7)

After meal 5/12 (41.7)

Both 2/12 (16.7)

Duration of using the method, yrs 12/12 (100) 6.3±8.3 1–32 5 Insulin dose, units 12/12 (100) 41.23±22.43 21.00–100.00 34.40

Table 1. Study population (n=12): background characteristics

Characteristics No. of patients Result

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result in LBGI and HBGI, respec-tively; and LBGI + HBGI = BGRI, as mentioned earlier.

The BG data were also characterised by the standard deviation (SD) of rate of change, which is a measure of the stability of closed-loop control over time, and exactly the SD of the BG rate of change between two points in time that are 15 minutes apart. The period of 15 minutes was chosen as the one most fre-quently recommended and used in the literature.15

Analysis

The CGMS data were downloaded using MiniMed Solutions software. The data were further analysed using the SAS 9 software package.

Descriptive statistics were provided for all data points in the study and included mean±SD, median and minimum–maximum ranges for con-tinuous variables. Data for categorical variables were presented by percentages and number of cases. Comp -arisons between two groups were per-formed using non-parametric tests due to the small number of patients in the study. Thus, comparisons between independent groups were analysed by Wilcoxon test, while matched observa-tions, e.g. two methods experienced by the same patient, were compared by Sign test.

Multivariable analysis was per-formed by mixed linear models

allowing for independent intercept represented by each patient and only when distribution of a dependent variable did not violate the model assumptions. In fact, all dependent variables were normally distributed due to the nature of their definition as discussed by Clarke and Kovatchev.15 Analysis of variability measurements (BGRI, HBGI and LBGI) used all observations averaged on an hourly basis, and analysis of rate of change endpoint was based on 15-minute resolution.

The variability endpoint is dis-played on a graph for randomly chosen patients (Appendix 1). Results

The background characteristics of the study population are shown in Table 1.

Sixteen patients started the study; four of the 16 dropped out due to discomfort when using the CGMS. Twelve patients, aged 23–71 years (mean 49.3±14), completed the study. Six patients were treated with an insulin pump (CSII) and the other six with the MDI method.

The mean BMI was 27±3.7kg/m2

and the mean HbA1c was 6.8±0.6%. The average duration of diabetes was 22.1±11.6 years.

Prior to the study, five patients injected the insulin bolus before the meal, five injected after the meal and two patients reported that they used both options.

Glucose control by timing of injection

We analysed glucose control based on all glucose measurements during the study (Figure 1), and performed an analysis based on the measure-ments at the first and second hours after reported meals (Table 2). Extreme hypoglycaemia, charac-terised by BG <2.77mmol/L, was seen on average in <3% of observa-tions and was not different between injection methods. High glucose measurements, >13.87mmol/L, were seen in 3.7% of observations when injected before a meal, and in 8.0% for after meal injection (p=0.73). Similarly, no significant differences were found in hypoglycaemia or hyperglycaemia for the 2 post-prandial hours (data not shown).

The measure of the frequency and extent of low BG readings (LBGI) was not affected by the method of injection (before vs after the meal). However, HBGI, reflecting the frequency and extent of high BG readings, was found to be signifi-cantly higher for the after meal injec-tion method (p=0.003). The BGRI was significantly higher for the after meal injection method, mostly on account of an increased hypergly-caemia index (HBGI); p=0.003. (Table 2.) The HBGI and BGRI were significantly lower in the MDI group compared to the CSII group (p=0.02 and p=0.05, respectively), after adjusting for the timing of injection, before or after the meal, and the overall number of meals consumed during the study. Each additional meal was shown to significantly increase overall variability by a co effi-cient of 0.29 (Appendix 2 [available online at www.practicaldiabetes. com]). These differences were found for the 72-hour variability, but not when analysing the 2-hour post-meal period due to a lower power of test-ing within this sub-group.

The risk for hypoglycaemia meas-ured by categories of LBGI is mini-mal to low in both methods of timing of the meal injection (83.4% and 91.7% for before and after meal injection respectively, p=0.625). On the other hand, the risk for hypergly-caemia measured by categories of HBGI is high in 25% of instances when injecting after the meal com-pared to 8.3% when injecting before

Figure 1. Blood glucose during 72 hours of follow up, by mode of insulin injection – before or after meal

Blo od glu co se ( 95 % CI) mmo l/L 12.00 10.00 8.00 6.00 4.00 Before After

Day 1 Day 2 Day 3 Day 4

10 12 14 16 18 2022 0002 04 06 0810 12 14 1618 2022 0002 0406 08 10 12 14 1618 2022 00 02 0406 08

Time of follow up (hours)

Area under the curve (AUC) for the follow up of 72 hours was not different between the modes of insulin injection (Sign test p-value 0.388).

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the meal, although without statistical significance due to the small sample. In answering the satisfaction questionnaires (Table 3), 16.7% of the patients thought that injecting before the meal would avoid hypo-glycaemia compared to 41.7% who thought that post-meal injection would avoid hypoglycaemia; the remainder thought that no method avoids hypoglycaemia events. The most remarkable finding was that patients adhere to the method of insulin injection that they are taught initially – all patients in the study group replied that they would not change their previous routine of injection.

Discussion

Diabetes mellitus, a chronic disease affected by and affecting all aspects of daily living, obliges medical staff to tailor a treatment plan for each patient. Our goal is for patients to continue their everyday life and control their diabetes concomitantly. This study raises the question as to whether we can enable flexibility for the time of injection due to the fact that patients with type 1 or type 2 diabetes, treated with insulin bolus, encounter situations in which the size and content of the meal are unpredictable.

A few studies have examined this question. Jovanovic et al.12conducted two tests where the patients injected insulin either before the meal or immediately after the meal. Capillary blood glucose levels were measured before and at 1, 2, 3 and 4 hours after the start of the meal. They measured AUC (area under the curve), and found that pre-prandial insulin injection produced a better glucose profile, but both pre-prandial and post-prandial injection achieved glu-cose levels within the recommended targets. Similar results have been found by others.8–11All studies tested AUC 2–4 hours after the meals – either standard meals8–10 or flexible meals.11,12Danne et al.13treated type 1 diabetic children in a randomised, multi-centre, open-label, two-period, crossover study with aspart insulin pre-prandially and post-pre-prandially for 12 weeks and assessed fructosamine level and HBA1con top of the 7-point BG profile 2 hours after the meal, and found no significant differences.

Our study took relatively con-trolled, highly compliant adult patients and tested the 72-hour BG by connecting them to a CGMS. We found that variability was greater when injecting insulin after the meal, with a tendency for high glucose measurements. This was not found when testing at the 2-hour post-prandial point, in keeping with the previous findings by others.

Increased interest in the impor-tance of glucose variability and its effect on diabetes complications has recently emerged. Studies4–6 have shown that not only overall glucose control, but also increased post-prandial glucose and greater vari-ability, worsen diabetes outcomes. Moreover, in tightly controlled diabetes, when hypoglycaemia can

be common, emphasis on glucose variability becomes of greater impor-tance. Therefore, any treatment recommendation should consider the effect on overall control and on glucose variability.

The importance of meal composi-tion in relacomposi-tion to the timing of insulin injection has been discussed in a pre-vious study.16This indicates that post-prandial administration is preferred when the meal contains fatty foods and foods with a low glycaemic index. Whereas, when the meal content is mostly with carbohydrate and with a high glycaemic index, it is preferable to inject prior to the meal. The studies discussed above8–10tested a fixed meal that was mostly composed of carbohy-drates. In our study, the patients kept a food diary and we saw that most of

BGRI: average for 72 hrs

Mean±SD (n) 5.29±3.40 (12) 6.57±4.57 (12) 0.774 0.003

Median 4.18 5.00

Range 2.64–15.4 1.52–17.04

LBGI: average for 72 hrs

Mean±SD (n) 1.80±1.40 (12) 1.97±1.92 (12) 0.774 0.815

Median 1.59 1.36

Range 0.52–5.55 0.53–7.81

HBGI: average for 72 hrs

Mean±SD (n) 3.49±2.29 (12) 4.60±3.35 (12) 1.000 0.003

Median 2.84 3.78

Range 1.03–9.88 0.58–9.96

SD of BG rate of change/15 mins

Mean±SD (n) 0.91±0.38 (12) 0.88±0.30 (12) 1.000 0.862 Median 0.74 0.86 Range 0.60–1.89 0.43–1.50 Mean BG, mmol/L 1st post-prandial hr Mean±SD (n) 7.41±1.0 (12) 8.39±2.09 (12) 0.146 0.114 Median 7.24 8.39 Range 5.47–9.24 5.65–12.9 2nd post-prandial hr Mean±SD (n) 8.1±2.36 (12) 8.79±2.5 (12) 0.151 0.145 Median 7.63 7.97 Range 4.41–14.0 5.56–13.32

BGRI = BG risk index; LBGI = low BG index; HBGI = high BG index; SD = significant difference. *Adjustment was performed by mixed linear model predicting each of the variability measurements with before/after meal method as independent variable and by controlling for the method of insulin injection, i.e. pump or MDI, and to the overall number of meals consumed by a patient.

Blood glucose (BG) Before meal After meal Sign test Adjusted outcomes method method p-value p-value*

(n=12) (n=12)

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the meals consisted mainly of carbo-hydrates. Additional studies would be recommended in order to elucidate this issue.

An interesting finding in our study was the fact that all patients adhere to the method of insulin injection which they were taught ini-tially – all patients in the study group said that they would not change their previous method of injection. This emphasises the importance of tailor-ing insulin injection timtailor-ing to the dietary patterns and routines of each individual patient, early in the course of his/her diabetes.

The limitations of our study include the small number of patients involved; however, a vast amount of measurements per patient increases its strength. In addition, the order of injections was not randomised and this may induce biases in patients’ behav-iour including different meal compo-sition and exercise level, although the study was conducted during working days and presumably reflects patients’ routine. Moreover, no study, including our own, has examined the differences in food content on the timing of the insulin bolus. Certain patients might be able to self-adjust for their variable meals and, doing so, maximise their glucose control.

What should a patient do when the amount of carbohydrates they are

intending to eat is unpredictable? Is it preferable to inject prior to the meal in any case, or is it better to inject the exact bolus of insulin? These questions are not answered in our study.

In summary, injecting insulin prior to the meal can reduce the overall glucose variability, and remains the preferred method of injection. Larger studies are needed in order to reinforce these results and compare them to timing of injec-tion based on food content.

Acknowledgement

We wish to thank Mrs Shula Witkow from the Diabetes Clinic for all her assistance.

Declaration of interests

There are no conflicts of interest declared.

References

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2. Nathan DM, et al.; Diabetes Control and Complications Trial/Epidemiology of Diabetes. Interventions and Complications (DCCT/EDIC) Study Research Group. Intensive diabetes treat-ment and cardiovascular disease in patients with type 1 diabetes. N Engl J Med 2005; 353:2643–53.

3. American Diabetes Association. Standards of Medical

Care in Diabetes – 2011. Diabetes Care 2011;34: S11–S61; doi:10.2337/dc11-S011.

4. Hirsch IB. Glycemic variability: it’s not just about A1C

any more! Diabetes Technol Ther 2005;7:780–3. 5. Leiter LA, et al.; International Prandial Glucose

Regulation Study Group. Postprandial glucose regu-lation: new data and new implications. Clin Ther 2005;27(Suppl B):S42–56.

6. Bonora E, Muggeo M. Postprandial blood glucose as a risk factor for cardiovascular disease in type II diabetes: the epidemiological evidence. Diabetologia 2001;44:2107–14.

7. Mooradian A, et al. Narrative review: a rational approach to starting insulin therapy. Ann Intern Med 2006;145:125–34.

8. Brunner GA, et al. Post-prandial administration of the insulin analogue insulin aspart in patients with type 1 diabetes mellitus. Diabet Med 2000;17:371–5. 9. Cobry E, et al. Timing of meal insulin boluses to

achieve optimal postprandial glycemic control in patients with type 1 diabetes. Diabetes Technol Ther 2010;12:173–7.

10. Scaramuzza AE, et al. Timing of bolus in children with type 1 diabetes using continuous subcutaneous insulin infusion (TiBoDi Study). Diabetes Technol Ther 2010;12:149–52.

11. Schernthaner G, et al. Postprandial insulin lispro. A new therapeutic option for type 1 diabetic patients. Diabetes Care 1998;21:570–3.

12. Jovanovic L, et al. Efficacy comparison between preprandial and postprandial insulin aspart adminis-tration with dose adjustment for unpredictable meal size. Clin Ther 2004;26:1492–7.

13. Danne T, et al. A comparison of postprandial and preprandial administration of insulin aspart in children and adolescents with type 1 diabetes. Diabetes Care 2003;26:2359–64.

14. Schernthaner G, et al. Preprandial vs. postprandial lispro – a comparative crossover trial in patients with type 1 diabetes. Diabet Med 2004;21:279–84. 15. Clarke W, Kovatchev B. Statistical tools to analyze

continuous glucose monitor data. Diabetes Technol Ther 2009;11(Suppl 1):S45–54.

16. Strachan MW, Frier BM. Optimal time of administra-tion of insulin lispro. Importance of meal composi-tion. Diabetes Care 1998;21:26–31.

Satisfied with before meal injection method 80.0% (4/5) 60.0% (3/5) 100.0% (2/2) 75.0% (9/12) 0.513 Satisfied with after meal injection method 40.0% (2/5) 100.0% (5/5) 50.0% (1/2) 66.7% (8/12) 0.114

Trying out a new method made patients 0.0% (0/5) 0.0% (0/5) 0.0% (0/2) 0.0% (0/12) –

change their previous way of injection

Would you recommend an after meal 40.0% (2/5) 80.0% (4/5) 0.0% (0/1) 54.5% (6/11) 0.231

injection method?

Which method avoids hypoglycaemia better? 0.975

Before meal injection 20.0% (1/5) 20.0% (1/5) 0.0% (0/2) 16.7% (2/12)

After meal injection 40.0% (2/5) 40.0% (2/5) 50.0% (1/2) 41.7% (5/12)

None of them 40.0% (2/5) 40.0% (2/5) 50.0% (1/2) 41.7% (5/12)

Which method will induce weight gain? 0.175

Before meal injection 0.0% (0/5) 40.0% (2/5) 50.0% (1/2) 25.0% (3/12)

After meal injection 60.0% (3/5) 0.0% (0/5) 50.0% (1/2) 33.3% (4/12)

None of them 40.0% (2/5) 60.0% (3/5) 0.0% (0/2) 41.7% (5/12)

Question Patients used to Patients used to Patients used to All patients Chi-square injecting before injecting after both methods (n=12) p-value meal (n=5) meal (n=5) (n=2)

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Appendix 1. Risk traces of pre- and post-meal insulin injection method during 72 hours of follow up – example of two patients: one on CSII (patient no. 1)

and one on MDI (patient no. 6). (Continued on next page)

The values of blood glucose are assigned either ‘Risk of hypo’ or ‘Risk of hyper’ following the formulae described by Clarke and Kovatchev,15

where extreme values of hyperglycaemia approach 50 and severe values of hypoglycaemia approach -50. Vertical columns in black colour represent meal times.

Patient no. 1 on CSII: Before meal insulin injection method

Time (hours) Ris k o f h ypo /ris k o f h yper: glu co se ( mmo l/L ) 50 40 30 20 10 0 -10 -20 -30 -40 -50

Patient no. 1 on CSII: After meal insulin injection method

Time (hours) Ris k o f h ypo /ris k o f h yper: glu co se ( mmo l/L ) 50 40 30 20 10 0 -10 -20 -30 -40 -50

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Appendix 1. Risk traces of pre- and post-meal insulin injection method during 72 hours of follow-up – example of two patients: one on CSII (patient no. 1)

and one on MDI (patient no. 6). (Continued from previous page)

Patient no. 6 on MDI: Before meal insulin injection method

Time (hours) Ris k o f h ypo /ris k o f h yper: glu co se ( mmo l/L ) 50 40 30 20 10 0 -10 -20 -30 -40 -50

Patient no. 6 on MDI: After meal insulin injection method

Time (hours) Ris k o f h ypo /ris k o f h yper: glu co se ( mmo l/L ) 50 40 30 20 10 0 -10 -20 -30 -40 -50

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BGRI Regression coefficient -1.153 -3.56 0.29

P-value 0.003 0.051 0.017

LBGI Regression coefficient -0.06 -0.72 0.21

P-value 0.815 0.385 0.004

HBGI Regression coefficient -1.12 -2.92 0.06

P-value 0.003 0.020 0.611

SD of BG rate Regression coefficient -0.00243 -0.00628 -0.00052

of change P-value 0.862 0.719 0.836

For 2 hours post-prandially over the 72 hours of follow up

BGRI Regression coefficient -0.09 -3.19 0.07

P-value 0.900 0.208 0.714

LBGI Regression coefficient 0.50 -1.06 0.17

P-value 0.400 0.535 0.271

HBGI Regression coefficient -0.58 -2.10 -0.10

P-value 0.369 0.064 0.482

SD of BG rate Regression coefficient 0.48 -0.16 -0.01

of change P-value 0.028 0.327 0.238

BGRI = BG risk index; LBGI = low BG index; HBGI = high BG index; SD = significant difference.

Before vs After MDI vs Pump No. of meals

Figure

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References

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