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No difference between venous and capillary blood sampling and the Minimed continuous glucose monitoring system for determining the blood glucose response to food
Nutrition Research 26 (2006) 403 – 408 www.elsevier.com/locate/nutres
No difference between venous and capillary blood sampling and the Minimed continuous glucose monitoring system for determining the blood glucose response to food Alison J. Wallacea,4, Jinny A. Willisb, John A. Monroc, Chris M. Framptond, Duncan I. Hedderleyc, Russell S. Scottb a
New Zealand Institute for Crop and Food Research Limited, Private Bag 4704, Christchurch, New Zealand b Lipid and Diabetes Research Group, Private Bag 4710, Christchurch, New Zealand c New Zealand Institute for Crop and Food Research Limited, Private Bag 11600, Palmerston North, New Zealand d Christchurch School of Medicine, Private Bag 4345, Christchurch, New Zealand Received 11 April 2006; revised 23 June 2006; accepted 17 July 2006
Abstract The aim of the study was to determine whether venous blood sampling and the Minimed continuous glucose monitoring system (CGMS) (Medtronic, Northridge, Calif) are possible alternative methods to capillary blood sampling for determining the blood glucose response to foods. Seven individuals without diabetes took part in the study. The glycemic glucose equivalent (GGE) expressed as GGE/bar of a muesli bar was determined on 3 occasions by capillary, venous, and CGMS blood sampling methods. The GGE was determined as the incremental area under the curve for 2 hours after consumption of a 50-g muesli bar compared with the incremental area under the curve for a 50-g glucose reference drink. The GGE of the bar was 21.4 F 7.8 GGE/serve for the CGMS, 16.6 F 6.0 GGE/serve for the venous, and 17.4 F 5.5 GGE/serve for the capillary samples. The coefficients of variation were 36% for the CGMS and venous sampling methods and 30% for the capillary samples. The differences in GGE calculations produced by the 3 blood sampling methods were not statistically significant. Therefore, it appears that the CGMS and venous blood sampling produce similar results to capillary blood sampling for measuring blood glucose response to foods. The study also attempted to reduce the intraindividual variability in GGE measurements. Measuring the blood glucose value of an individual more frequently over the 2 hours or consuming the test food and reference drink on the same day did not significantly reduce the variability in the GGE measurements. D 2006 Elsevier Inc. All rights reserved. Keywords:
Glycemic index; Capillary; Venous; Blood glucose
1. Introduction Foods vary in their ability to raise blood glucose levels. Currently, there are 2 widely published methods for determining the glycemic impact of a food. The glycemic index (GI) is often used to measure the blood glucose 4 Corresponding author. Tel.: +64 33259638; fax: +64 33252074. E-mail address: [email protected] (A.J. Wallace). 0271-5317/$ – see front matter D 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.nutres.2006.07.007
response to foods. It is defined as the incremental area under the blood glucose response curve (IAUC) elicited by a 50-g carbohydrate portion of a food expressed as a percentage of the area created when a 50-g carbohydrate from a reference food (often glucose) is taken by the same subject [1]. The other method, glycemic glucose equivalents (GGE), is a value that represents a food’s effect on blood glucose in terms of the weight of glucose an individual would need to eat to produce the same effect as a food [2-4]. Glycemic
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glucose equivalent builds on GI by measuring the glycemic impact of the whole food rather than only of the carbohydrate portion. Because GGE is responsive to changes in food intake and relates the blood glucose response to the defined portion of the food, not just to 50 g of available carbohydrate, it can be used to compare foods containing different amounts of carbohydrates [5]. Glycemic glucose equivalent can be estimated from GI by multiplying the GI of the food by the proportion of available carbohydrate in the serving of the food, referred to as the glycemic load [6]. Currently, both GI and GGE are calculated by taking capillary blood samples over 2 hours, after consumption of a test food, to determine the IAUC for this period. This results in a large number of finger prick samples to a participant over a short period (8 in 2.5 hours). A previous study has shown that venous blood samples, taken via a catheter, produce greater individual variability in assessments of a 50-g glucose reference drink than capillary blood samples [7]. However, the venous and capillary samples were taken from different individuals at different centers, which may have contributed to the result. An alternative to venous or capillary blood sampling for determining the blood glucose response of foods may be the Minimed continuous glucose monitoring system (CGMS) (Medtronic, Northridge, Calif). The CGMS monitors glucose values in the interstitial tissue fluid. A sensor is inserted just under the skin and transmits electrical signals to the monitor via an electrochemical reaction with the glucose. The enzyme glucose oxidase catalyses the conversion of glucose at the sensor surface into electrical signals, which are sent via a cable to the monitor. The monitor records an average glucose value every 5 minutes. The CGMS has been used in a number of clinical trials, and the correlation between blood glucose measurement and CGMS has been reported to be high (0.8-0.9) [8-11]. However, when glucose values are rapidly changing, there may be a lag between blood and interstitial fluid measurements [8,12,13]. Glycemic glucose equivalent and GI measurements are based on the area under the curve of blood glucose response for 2 hours after consumption of a food. Therefore, a lag may not affect the overall area under the curve but could affect the timing of the response. If the CGMS could be used to determine the GI and GGE of foods, it would replace the need for continual blood sampling. It would also allow glycemic response to be investigated over longer periods and make studies of the blood glucose profile of food and meals over the whole day easier. One of the difficulties of measuring the blood glucose response of foods is that the response varies considerably within the same individual on different days. Previously, Wolever et al [7] noted that the within-individual variability in response to a reference drink consumed on 3 different occasions was, on average, 34%. This variability can be due to many different factors, including differences in the diet
[14] and/or previous evening meal of an individual before the test meals [15], the amount of physical activity on the days preceding the test meal [16], the alcohol consumption on the night before the test meal [17], and the exact length of the overnight fast [18]. These factors will all lead to variability in response within an individual from day to day. Therefore, if these factors can be controlled by measuring the food and reference drink on the same day, the intraindividual variability may be able to be reduced. The present study aimed to examine whether the capillary, venous, and CGMS methods estimate the same GGE values for a food and whether the intraindividual variation for each of the 3 methods is comparable. It also investigated whether more frequent blood sampling or measuring of the test food and reference drink on the same day using the CGMS would reduce the intraindividual variability in GGE measurements. 2. Methods and materials Volunteers were recruited for this study using advertisements at local universities and hospitals. To be eligible for the study, participants had to be older than 18 years and not suffer from diabetes (as determined by a fasting plasma glucose less than 7.0 mmol/L). Seven individuals took part in this study: 4 males and 3 females. The average age of the participants was 33 years (range, 18-65 years); height, 1.7 m; weight 69.5 kg; body mass index, 23.0 kg/m2; and fasting venous plasma glucose, 4.9 F 0.5 mmol/L. This study was approved by the Canterbury ethical committee, and all the participants gave their informed consent. The Minimed CGMS was inserted into the outer quadrant buttock in each participant late one afternoon. The CGMS, once fitted, was worn for up to 72 hours continuously. During each 24-hour period that an individual was wearing the CGMS, they carried out 4 self-monitoring blood glucose (SMBG) tests and entered these values into the CGMS. The SMBG test was carried out using an Advantage blood glucose meter and Advantage II blood glucose strips (Roche Diagnostics, Mannheim, Germany). The morning after the CGMS was fitted to the participants, they came into the clinic fasting (from 10 pm the night before) and remained there for about 3 hours. The participants were instructed to eat a meal high in carbohydrates the evening before and not to undertake any strenuous exercise in the 12 hours preceding their visit to the clinic. Before beginning, each CGMS monitor was downloaded to check it was working. A catheter was then placed in the arm, and 2 fasting venous blood samples (2 mL) were taken approximately 5 minutes apart. Two fasting blood samples were also obtained by means of a finger prick and approximately 0.6 mL collected in a blood tube. On 1 of the finger prick samples, an SMBG test was carried out, and this number was entered in the CGMS. The participant then consumed a test food within 10 minutes, and further blood samples were taken in the same manner using both the
A.J. Wallace et al. / Nutrition Research 26 (2006) 403–408
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Table 1 The average incremental area under the curve for glucose and muesli bar and the average GGE values per serve as determined by the CGMS, venous, and capillary blood sampling on 3 occasions; the pooled intraindividual SD; and the coefficient of variation Average IAUC (mmol min/L) (min, max) Glucose CGMS (n = 7) Venous (n = 6) Capillary (n = 7) Bar CGMS (n = 7) Venous (n = 6) Capillary (n = 7) GGE/serve CGMS (n = 7) Venous (n = 6) Capillary (n = 7)
a
130.8 (80.3, 220.6) 161.4 (102.4, 268.4)a 261.2 (181, 345.4)b a
46.5 (16.3, 79.3) 53.8 (18.3, 92.0)a 90.6 (48.9, 148.4)b Average GGE/serve (g) (min, max) 21.4 (10.0, 41.1)ns 16.6 (8.6, 24.5)ns ns 17.4 (11.2, 22.1)
SD (min, max)
CV (min, max) (%)
54.5 (7.4, 113.9) 46.5 (20.7, 74.8) 42.1 (21.6, 63.4)
42 (7-54) 29 (24 - 45)a 16 (9 -19)b
16.8 (4.3, 45.7) 21.2 (2.0, 37.8) 25.2 (6.9, 43.0)
47 (9 - 66) 39 (3 -54)ns 28 (5 - 47)ns
SD 7.8 6.0 5.5
CV (%) 36 (14 - 63)ns 36 (27- 43)ns ns 30 (16 - 47)
a,b
ns
(min, max) (2.4, 14.0) (3.0, 10.5) (1.8, 9.9)
Different letters indicate significant differences between the methods (CGMS, venous, and capillary), P b .05; ns, P N .05 for comparison between the 3 methods.
catheter and finger pricks at about 15, 30, 45, 60, 90, and 120 minutes after the patient had begun eating. The exact times when the samples were taken were recorded and used in subsequent calculations. All blood samples were taken in tubes containing glycolytic inhibitor. Samples were analyzed for plasma glucose concentrations at the end of each morning using the Abbott glucose hexokinase enzymatic assay. At the end of the morning, the participants left the clinic to continue their normal activities, but they continued to wear the CGMS. This procedure was then repeated on the following 2 days. While the participants were away from the clinic, they carried out 2 SMBG measurements and entered them into the CGMS, 1 SMBG late afternoon or early evening and 1 before bedtime. At the end of the third day of testing, the CGMS was removed. The same procedure was repeated the following week. The effect on each participant of consuming a 50-g glucose drink was measured on 3 occasions and a 50-g Mother Earth Baked Oaty Slice, Sultana Oat, and Honey muesli bar on other 3 occasions. A 50-g muesli bar had an energy content of 780 kJ, carbohydrate 29.4 g, of which total sugars was 19.7 g, dietary fiber 2.5 g, total fat 6.8 g, of which 4.1 g was saturated fat, and protein 3.0 g. Because of the burden on the participants of wearing the CGMS continually for 72 hours, attending the clinic 3 mornings in a row and having at least 10 finger pricks a day, only a muesli bar and a glucose reference were measured on 3 occasions each. Apart from the first participant who received 3 glucose drinks in 1 week and 3 muesli bars the following week, the participants alternated between the glucose drink and the bar and were randomized to start with either the drink or the bar. In 3 of the participants, the CGMS monitor failed and had to be removed before the third day of testing was complete. Hence, for 2 individuals, only 2 glucose drinks were measured, and for 1 individual, only 2 bars were measured. For another individual, venous samples could not be collected.
The IAUC to 120 minutes was calculated geometrically using the method described by Wolever and Jenkins [19] for all 3 methods (venous, capillary and CGMS). Areas where the curve dropped below baseline were excluded. For the CGMS, the blood glucose response every 5 minutes for the 120 minutes was used in the calculation rather than just the 15-, 30-, 45-, 60-, 90-, and 120-minute readings used in the capillary and venous instances. The GGE of the muesli bar was calculated as GGE/50 g bar by dividing the IAUCbar by the IAUCglucose and multiplying the result by 50 g (the amount of glucose in the reference drink). This was calculated for the 3 times the bar was consumed for each method (venous, capillary, and CGMS) for each individual using the first time the bar was consumed against the first time the glucose reference drink was consumed, the second time the bar was consumed against the second time the glucose reference was consumed, and so on. The average GGE/serve by each method was then calculated. The GGEs were compared between the 3 groups in a pair case manner using the Wilcoxon signedrank test. The intraindividual coefficient of variation (CV) of the GGE was calculated and compared between the 3 methods also using the Wilcoxon signed-rank test. A further part to the study was carried out using the CGMS only in the same 7 individuals to determine whether Table 2 The average GGE values per serve as determined by the CGMS on 3 days when the muesli bar and reference glucose are measured on the same day and different days; the pooled intraindividual SD; and the coefficient of variation
Different days (n = 7) Same day (n = 7)
Average GGE/serve (g) (min, max) 21.4 (10.0, 41.1)
SD (min, max)
CV (min, max) (%)
7.8 (2.4, 14.0)
36 (14 - 63)
20.5 (15.2, 27.5)
11.7 (3.9, 21.1)
63 (25 -130)
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Table 3 Comparison of the GGE of the muesli bar and coefficient of variation when the incremental area under the curve was calculated by measuring blood glucose using the CGMS with readings taken every 5 minutes compared with readings taken every 15 minutes for the first hour and every 30 minutes for the second hour 5-minute readings
Bar and glucose consumed on different days (n = 7) Bar and glucose on same day (n = 7)
Readings every 15 minutes for first hour and every 30 minutes for second hour
Average GGE/serve (g) 21.4 (10.0, 41.1)
CV (%) 36
Average GGE/serve (g) 22.6 (7.8, 47.4)
20.5 (15.1, 27.5)
63
20.7 (16.0, 30.3)
the intraindividual variability in GGE measurements could be reduced by measuring the food and drink in 1 day. The study was carried out in the same way, as described above, except that the test food and reference drink were measured on the same day, one after the other, on 3 consecutive days. The participants were randomized to the order in which they received the drink and the bar on each day. Before receiving the second food on the same day (after 120 minutes), the CGMS was downloaded. The participant was then given the other food (either the muesli bar or the 50-g reference drink) and asked to sit quietly for a further 120 minutes. After 120 minutes, another SMBG was taken and entered into the CGMS. The participants were then given lunch and allowed to leave the clinic for the day. Values for the GGE/50-g serve of the bar for the CGMS only were also calculated using the blood glucose results at 0, 15, 30, 45, 60, 90, and 120 minutes rather than with readings taken every 5 minutes, as used above. The GGE/ 50-g serve and its variability calculated using 5-minute readings were compared with the corresponding GGE/50-g serve and variability when readings at 15, 30, 45, 60, 90 and 120 minutes were used using the nonparametric Wilcoxon signed-rank test. 3. Results Table 1 presents the average IAUC for glucose and muesli bar and the average GGE values for the 3 occasions they were measured by the CGMS, venous, and capillary blood samples, the pooled intraindividual standard deviation, and the variability in the measurement by each method (CV). The IAUCs of both glucose and muesli bar were significantly lower when measured using the CGMS or venous sampling methods than using the capillary method. The CV of glucose by venous blood sampling was significantly higher than by capillary blood sampling. The GGE of the bar was 21.4 g/serve for the CGMS, 16.6 g/serve for the venous samples, and 17.4 g/serve for the capillary samples, and these values were not statistically different. The coefficients of variation for the GGE/serve were 36% for the CGMS and venous sampling methods and 30% for the capillary samples, and these differences were not significantly different.
CV (%) 45 71
The GGE of the bar using the CGMS method only was also calculated when the bar and the drink were measured on the same day. Table 2 presents the average GGE values for the 3 occasions they were measured, the pooled intraindividual standard deviation, and the variability in the measurement by each method. The intraindividual CV for the average GGE/50g serve was 64%, which was higher than the 36% variability reported when the bar and reference drink were measured on separate days. However, these differences were not statistically different. Table 3 presents the GGE values for the CGMS only when they were calculated using readings taken every 5 minutes compared with readings taken every 15 minutes for the first hour and every 30 minutes thereafter, up to 120 minutes. These are shown when the bar and drink were consumed on the same day and when the bar and drink were consumed on separate days. There were no statistically significant differences in the average GGE of the bar or the variability of the measurements regardless of how frequently interstitial glucose values was measured over the 2 hours. 4. Discussion Interestingly, the main finding of this study is the enormous variability in individual response to foods, with an average CV of about 30% in all 3 methods. This finding has also been found by Wolever et al [7]. Although there were no significant difference in the GGE values between the 3 methods, the IAUC of capillary blood sampling is greater than by the other 2 methods. A larger IAUC results in better sensitivity and allows smaller differences between foods to be detected. This larger IAUC may be responsible for the fact that the CV with capillary blood sampling is significantly lower than venous blood sampling for the glucose, but not for the bar—the IAUC of glucose using the capillary method is much higher than the IAUC by the venous method and the respective IAUCs in the bar. A previous study found that within-subject variation in response to 3 glucose reference drinks when venous blood was collected was double that when capillary blood was collected [7]. However, because measurements were carried
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out in various locations using a range of methods of plasma glucose analysis and different individuals, this could have been due to factors other than the capillary and venous blood sampling methods. Another study measuring glycemic response using venous and capillary samples taken simultaneously was carried out by Wolever and Bolognesi [20]. The study determined the glycemic response of 4 different foods by venous and capillary blood samples. The study concluded that capillary measurements were a more precise way of assessing glycemic response of foods because of the greater absolute differences between food and greater heterogeneity between means, suggesting that more experimental power was obtained. None of the measurements on the individuals were repeated more than once, so no information was gained about the variability in capillary and venous measurements. This study is the first of its kind to investigate the use of a CGMS to monitor postprandial blood glucose response of foods to determine the glycemic response of foods. It has been reported that there can be a lag between blood and interstitial fluid measurements when blood glucose values are changing rapidly [8,12,13]. This does not appear to affect the measurement of blood glucose response to food, because GGE measurements were not significantly different between the CGMS, venous, and capillary blood sampling methods. Measuring the bar and the drink in 1 day, one after the other, increased the variability in GGE measurements; though because of the large variability in the measurements and small numbers, the variability was not significantly different. It is a well-known phenomenon that there is diurnal variation in insulin, with insulin sensitivity decreasing progressively over the day [21-23]. It has also been shown that a previous meal can affect individual response to a subsequent food or meal, with glycemic response being lower when a low GI meal is consumed before the test food or meal than when a high GI meal is consumed [24-27]. Subjects were randomized to the order in which they received the bar and glucose reference to minimize these effects. However, it appears that the variability in measurements due to the second meal effect and the decrease in insulin sensitivity is greater than the variability due to factors that vary in individuals from day to day, such as the amount of physical activity on the days preceding the test meal [16], the alcohol consumption on the night before the test meal [17], and the exact length of the overnight fast [18]. Therefore, it can be concluded that the reference glucose and test food should not be measured on the same day. They should continue to be measured in the morning after an overnight fast, on separate days. Surprisingly, carrying out more frequent glucose readings with the CGMS did not reduce the variability of the GGE measurements. It can therefore be concluded that the current regimen of measuring blood glucose every quarter of an hour for the first hour and every half hour for the second hour is appropriate.
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In conclusion, the results of this study show that the GGE of a muesli bar calculated using 3 different blood sampling methods does not give significantly different GGE values for the food. Although venous blood sampling was comparable to capillary blood sampling for determining the GGE of a muesli bar, this methodology still requires regular blood sampling of the participant. The CGMS on the other hand measures blood glucose values in the interstitial fluid over 72 hours and therefore opens more opportunities for following foods for longer and at other periods during the day. Although this study is limited by small numbers and a high variability in the measurements, the results of this study suggest that further work should be carried out to compare the CGMS with capillary blood sampling in a larger range of foods and more individuals to ensure that the 2 methods give the foods the same relative ranking in terms of their glycemic response. If this is found to be the case, the CGMS may be able to be used as an alternative to capillary blood sampling for measuring the glycemic response of foods.
Acknowledgment This study was funded by the New Zealand Foundation for Science, Research and Technology. The authors thank the participants who took part in the research.
References [1] Wolever TMS, et al. The glycemic index: methodology and clinical implications. Am J Clin Nutr 1991;54:846 - 54. [2] Monro JA, Williams M. Concurrent management of postprandial glycaemia and nutrient intake using glycaemic glucose equivalents, food composition data and computer-assisted meal design. Asia Pac J Clin Nutr 2000;9(2):67 - 73. [3] Monro JA. Glycaemic index and available carbohydrates in exchanges of New Zealand foods. Proc Nutr Soc NZ 1997;22:241 - 8. [4] Monro JA. Available carbohydrate data and glycemic index combined in new data sets for managing glycaemia and diabetes. J Food Compos Anal 1999;12:71 - 82. [5] Monro JA. Food data for glycaemic control. Food Sci Central 2003;1 - 12. [6] Salmeron J, et al. Dietary fibre, glycaemic load, and risk of NIDDM in men. Diabetes Care 1997;20:545 - 50. [7] Wolever TMS, et al. Determination of the glycaemic index of foods: interlaboratory study. Eur J Clin Nutr 2003;57(3):475 - 82. [8] Steil GM, et al. Accurate determination of plasma glucose during hyper- and hypoglycemia with a subcutaneous glucose sensor. Diabetes 2000;49(Suppl 1):510. [9] Guerci B, et al. Clinical performance of CGMS in type 1 diabetic patients treated by continuous subcutaneous insulin infusion using insulin analogs. Diabetes Care 2003;26(3):582 - 9. [10] Gross TM, Mastrototaro JJ. Efficacy and reliability of the continuous glucose monitoring system. Diabetes Technol Ther 2000;2(Suppl 1): S19 - S26. [11] Gross TM, et al. Performance evaluation of the Minimed continuous glucose monitoring system during patient home use. Diabetes Technol Ther 2000;2:49 - 56. [12] Rebrin K, et al. Delay correction and smoothing of subcutaneous glucose sensor measurements. Diabetes 1999;48(Suppl 1):362.
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[13] Boyne MS, et al. Timing of changes in interstitial and venous blood glucose measured with a continuous subcutaneous glucose sensor. Diabetes 2003;52:2790 - 4. [14] Hales CN, Randle PJ. Effects of low-carbohydrate diet and diabetes mellitus on plasma concentrations of glucose, non-esterified fatty acid and insulin during oral glucose tolerance tests. Lancet 1963;1: 790 - 4. [15] Robertson MD, et al. Extended effect of evening meal carbohydrate/ fat ratio on fasting and postprandial substrate metabolism. Am J Clin Nutr 2002;75:505 - 10. [16] Malkova D, et al. Prior exercise and postprandial substrate extraction across the human leg. Am J Physiol Endocrinol Metab 2000;279: E1020 - 8. [17] Siler SQ, et al. The inhibition of gluconeogenesis following alcohol in humans. Am J Physiol 1998;275:E897 - E907. [18] Klein S, et al. Progressive alterations in lipid and glucose metabolism during short-term fasting in young adult men. Am J Physiol 1993; 265:E801 - 6. [19] Wolever TMS, Jenkins DJA. The use of the glycemic index in predicting the blood glucose response to mixed meals. Am J Clin Nutr 1986;43:167 - 72.
[20] Wolever TMS, Bolognesi C. Source and amount of carbohydrate affect postprandial glucose and insulin in normal subjects. J Nutr 1996;126:2798 - 806. [21] Lee A, et al. Diurnal variation in glucose tolerance. Diabetes 1992; 41:750 - 9. [22] Jarrett RJ, Keen H. Diurnal variation of oral glucose tolerance: a possible pointer to the evolution of diabetes mellitus. BMJ 1969; 2:341 - 422. [23] Carroll KF, Nestel PJ. Diurnal variation in glucose tolerance and in insulin secretion in man. Diabetes 1973;22(5):333 - 48. [24] Wolever TMS, Bentum-Williams A, Jenkins DJ. Physiological modulation of plasma free fatty acid concentration by diet. Metabolic implications in nondiabetic subjects. Diabetes Care 1995; 18(7):962 - 70. [25] Wolever TM, et al. Second-meal effect: low glycemic-index foods eaten at dinner improve subsequent breakfast glycemic response. Am J Clin Nutr 1988;48(4):1041 - 7. [26] Trinick TR, et al. Effect of guar on second-meal glucose tolerance in normal man. Clin Science (London) 1986;71(1):49 - 55. [27] Jenkins DJ, et al. Slow release dietary carbohydrate improves second meal tolerance. Am J Clin Nutr 1982;35(6):1339 - 46.
No difference between venous and capillary blood sampling and the Minimed continuous glucose monitoring system for determining the blood glucose response to food Alison J. Wallacea,4, Jinny A. Willisb, John A. Monroc, Chris M. Framptond, Duncan I. Hedderleyc, Russell S. Scottb a
New Zealand Institute for Crop and Food Research Limited, Private Bag 4704, Christchurch, New Zealand b Lipid and Diabetes Research Group, Private Bag 4710, Christchurch, New Zealand c New Zealand Institute for Crop and Food Research Limited, Private Bag 11600, Palmerston North, New Zealand d Christchurch School of Medicine, Private Bag 4345, Christchurch, New Zealand Received 11 April 2006; revised 23 June 2006; accepted 17 July 2006
Abstract The aim of the study was to determine whether venous blood sampling and the Minimed continuous glucose monitoring system (CGMS) (Medtronic, Northridge, Calif) are possible alternative methods to capillary blood sampling for determining the blood glucose response to foods. Seven individuals without diabetes took part in the study. The glycemic glucose equivalent (GGE) expressed as GGE/bar of a muesli bar was determined on 3 occasions by capillary, venous, and CGMS blood sampling methods. The GGE was determined as the incremental area under the curve for 2 hours after consumption of a 50-g muesli bar compared with the incremental area under the curve for a 50-g glucose reference drink. The GGE of the bar was 21.4 F 7.8 GGE/serve for the CGMS, 16.6 F 6.0 GGE/serve for the venous, and 17.4 F 5.5 GGE/serve for the capillary samples. The coefficients of variation were 36% for the CGMS and venous sampling methods and 30% for the capillary samples. The differences in GGE calculations produced by the 3 blood sampling methods were not statistically significant. Therefore, it appears that the CGMS and venous blood sampling produce similar results to capillary blood sampling for measuring blood glucose response to foods. The study also attempted to reduce the intraindividual variability in GGE measurements. Measuring the blood glucose value of an individual more frequently over the 2 hours or consuming the test food and reference drink on the same day did not significantly reduce the variability in the GGE measurements. D 2006 Elsevier Inc. All rights reserved. Keywords:
Glycemic index; Capillary; Venous; Blood glucose
1. Introduction Foods vary in their ability to raise blood glucose levels. Currently, there are 2 widely published methods for determining the glycemic impact of a food. The glycemic index (GI) is often used to measure the blood glucose 4 Corresponding author. Tel.: +64 33259638; fax: +64 33252074. E-mail address: [email protected] (A.J. Wallace). 0271-5317/$ – see front matter D 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.nutres.2006.07.007
response to foods. It is defined as the incremental area under the blood glucose response curve (IAUC) elicited by a 50-g carbohydrate portion of a food expressed as a percentage of the area created when a 50-g carbohydrate from a reference food (often glucose) is taken by the same subject [1]. The other method, glycemic glucose equivalents (GGE), is a value that represents a food’s effect on blood glucose in terms of the weight of glucose an individual would need to eat to produce the same effect as a food [2-4]. Glycemic
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glucose equivalent builds on GI by measuring the glycemic impact of the whole food rather than only of the carbohydrate portion. Because GGE is responsive to changes in food intake and relates the blood glucose response to the defined portion of the food, not just to 50 g of available carbohydrate, it can be used to compare foods containing different amounts of carbohydrates [5]. Glycemic glucose equivalent can be estimated from GI by multiplying the GI of the food by the proportion of available carbohydrate in the serving of the food, referred to as the glycemic load [6]. Currently, both GI and GGE are calculated by taking capillary blood samples over 2 hours, after consumption of a test food, to determine the IAUC for this period. This results in a large number of finger prick samples to a participant over a short period (8 in 2.5 hours). A previous study has shown that venous blood samples, taken via a catheter, produce greater individual variability in assessments of a 50-g glucose reference drink than capillary blood samples [7]. However, the venous and capillary samples were taken from different individuals at different centers, which may have contributed to the result. An alternative to venous or capillary blood sampling for determining the blood glucose response of foods may be the Minimed continuous glucose monitoring system (CGMS) (Medtronic, Northridge, Calif). The CGMS monitors glucose values in the interstitial tissue fluid. A sensor is inserted just under the skin and transmits electrical signals to the monitor via an electrochemical reaction with the glucose. The enzyme glucose oxidase catalyses the conversion of glucose at the sensor surface into electrical signals, which are sent via a cable to the monitor. The monitor records an average glucose value every 5 minutes. The CGMS has been used in a number of clinical trials, and the correlation between blood glucose measurement and CGMS has been reported to be high (0.8-0.9) [8-11]. However, when glucose values are rapidly changing, there may be a lag between blood and interstitial fluid measurements [8,12,13]. Glycemic glucose equivalent and GI measurements are based on the area under the curve of blood glucose response for 2 hours after consumption of a food. Therefore, a lag may not affect the overall area under the curve but could affect the timing of the response. If the CGMS could be used to determine the GI and GGE of foods, it would replace the need for continual blood sampling. It would also allow glycemic response to be investigated over longer periods and make studies of the blood glucose profile of food and meals over the whole day easier. One of the difficulties of measuring the blood glucose response of foods is that the response varies considerably within the same individual on different days. Previously, Wolever et al [7] noted that the within-individual variability in response to a reference drink consumed on 3 different occasions was, on average, 34%. This variability can be due to many different factors, including differences in the diet
[14] and/or previous evening meal of an individual before the test meals [15], the amount of physical activity on the days preceding the test meal [16], the alcohol consumption on the night before the test meal [17], and the exact length of the overnight fast [18]. These factors will all lead to variability in response within an individual from day to day. Therefore, if these factors can be controlled by measuring the food and reference drink on the same day, the intraindividual variability may be able to be reduced. The present study aimed to examine whether the capillary, venous, and CGMS methods estimate the same GGE values for a food and whether the intraindividual variation for each of the 3 methods is comparable. It also investigated whether more frequent blood sampling or measuring of the test food and reference drink on the same day using the CGMS would reduce the intraindividual variability in GGE measurements. 2. Methods and materials Volunteers were recruited for this study using advertisements at local universities and hospitals. To be eligible for the study, participants had to be older than 18 years and not suffer from diabetes (as determined by a fasting plasma glucose less than 7.0 mmol/L). Seven individuals took part in this study: 4 males and 3 females. The average age of the participants was 33 years (range, 18-65 years); height, 1.7 m; weight 69.5 kg; body mass index, 23.0 kg/m2; and fasting venous plasma glucose, 4.9 F 0.5 mmol/L. This study was approved by the Canterbury ethical committee, and all the participants gave their informed consent. The Minimed CGMS was inserted into the outer quadrant buttock in each participant late one afternoon. The CGMS, once fitted, was worn for up to 72 hours continuously. During each 24-hour period that an individual was wearing the CGMS, they carried out 4 self-monitoring blood glucose (SMBG) tests and entered these values into the CGMS. The SMBG test was carried out using an Advantage blood glucose meter and Advantage II blood glucose strips (Roche Diagnostics, Mannheim, Germany). The morning after the CGMS was fitted to the participants, they came into the clinic fasting (from 10 pm the night before) and remained there for about 3 hours. The participants were instructed to eat a meal high in carbohydrates the evening before and not to undertake any strenuous exercise in the 12 hours preceding their visit to the clinic. Before beginning, each CGMS monitor was downloaded to check it was working. A catheter was then placed in the arm, and 2 fasting venous blood samples (2 mL) were taken approximately 5 minutes apart. Two fasting blood samples were also obtained by means of a finger prick and approximately 0.6 mL collected in a blood tube. On 1 of the finger prick samples, an SMBG test was carried out, and this number was entered in the CGMS. The participant then consumed a test food within 10 minutes, and further blood samples were taken in the same manner using both the
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Table 1 The average incremental area under the curve for glucose and muesli bar and the average GGE values per serve as determined by the CGMS, venous, and capillary blood sampling on 3 occasions; the pooled intraindividual SD; and the coefficient of variation Average IAUC (mmol min/L) (min, max) Glucose CGMS (n = 7) Venous (n = 6) Capillary (n = 7) Bar CGMS (n = 7) Venous (n = 6) Capillary (n = 7) GGE/serve CGMS (n = 7) Venous (n = 6) Capillary (n = 7)
a
130.8 (80.3, 220.6) 161.4 (102.4, 268.4)a 261.2 (181, 345.4)b a
46.5 (16.3, 79.3) 53.8 (18.3, 92.0)a 90.6 (48.9, 148.4)b Average GGE/serve (g) (min, max) 21.4 (10.0, 41.1)ns 16.6 (8.6, 24.5)ns ns 17.4 (11.2, 22.1)
SD (min, max)
CV (min, max) (%)
54.5 (7.4, 113.9) 46.5 (20.7, 74.8) 42.1 (21.6, 63.4)
42 (7-54) 29 (24 - 45)a 16 (9 -19)b
16.8 (4.3, 45.7) 21.2 (2.0, 37.8) 25.2 (6.9, 43.0)
47 (9 - 66) 39 (3 -54)ns 28 (5 - 47)ns
SD 7.8 6.0 5.5
CV (%) 36 (14 - 63)ns 36 (27- 43)ns ns 30 (16 - 47)
a,b
ns
(min, max) (2.4, 14.0) (3.0, 10.5) (1.8, 9.9)
Different letters indicate significant differences between the methods (CGMS, venous, and capillary), P b .05; ns, P N .05 for comparison between the 3 methods.
catheter and finger pricks at about 15, 30, 45, 60, 90, and 120 minutes after the patient had begun eating. The exact times when the samples were taken were recorded and used in subsequent calculations. All blood samples were taken in tubes containing glycolytic inhibitor. Samples were analyzed for plasma glucose concentrations at the end of each morning using the Abbott glucose hexokinase enzymatic assay. At the end of the morning, the participants left the clinic to continue their normal activities, but they continued to wear the CGMS. This procedure was then repeated on the following 2 days. While the participants were away from the clinic, they carried out 2 SMBG measurements and entered them into the CGMS, 1 SMBG late afternoon or early evening and 1 before bedtime. At the end of the third day of testing, the CGMS was removed. The same procedure was repeated the following week. The effect on each participant of consuming a 50-g glucose drink was measured on 3 occasions and a 50-g Mother Earth Baked Oaty Slice, Sultana Oat, and Honey muesli bar on other 3 occasions. A 50-g muesli bar had an energy content of 780 kJ, carbohydrate 29.4 g, of which total sugars was 19.7 g, dietary fiber 2.5 g, total fat 6.8 g, of which 4.1 g was saturated fat, and protein 3.0 g. Because of the burden on the participants of wearing the CGMS continually for 72 hours, attending the clinic 3 mornings in a row and having at least 10 finger pricks a day, only a muesli bar and a glucose reference were measured on 3 occasions each. Apart from the first participant who received 3 glucose drinks in 1 week and 3 muesli bars the following week, the participants alternated between the glucose drink and the bar and were randomized to start with either the drink or the bar. In 3 of the participants, the CGMS monitor failed and had to be removed before the third day of testing was complete. Hence, for 2 individuals, only 2 glucose drinks were measured, and for 1 individual, only 2 bars were measured. For another individual, venous samples could not be collected.
The IAUC to 120 minutes was calculated geometrically using the method described by Wolever and Jenkins [19] for all 3 methods (venous, capillary and CGMS). Areas where the curve dropped below baseline were excluded. For the CGMS, the blood glucose response every 5 minutes for the 120 minutes was used in the calculation rather than just the 15-, 30-, 45-, 60-, 90-, and 120-minute readings used in the capillary and venous instances. The GGE of the muesli bar was calculated as GGE/50 g bar by dividing the IAUCbar by the IAUCglucose and multiplying the result by 50 g (the amount of glucose in the reference drink). This was calculated for the 3 times the bar was consumed for each method (venous, capillary, and CGMS) for each individual using the first time the bar was consumed against the first time the glucose reference drink was consumed, the second time the bar was consumed against the second time the glucose reference was consumed, and so on. The average GGE/serve by each method was then calculated. The GGEs were compared between the 3 groups in a pair case manner using the Wilcoxon signedrank test. The intraindividual coefficient of variation (CV) of the GGE was calculated and compared between the 3 methods also using the Wilcoxon signed-rank test. A further part to the study was carried out using the CGMS only in the same 7 individuals to determine whether Table 2 The average GGE values per serve as determined by the CGMS on 3 days when the muesli bar and reference glucose are measured on the same day and different days; the pooled intraindividual SD; and the coefficient of variation
Different days (n = 7) Same day (n = 7)
Average GGE/serve (g) (min, max) 21.4 (10.0, 41.1)
SD (min, max)
CV (min, max) (%)
7.8 (2.4, 14.0)
36 (14 - 63)
20.5 (15.2, 27.5)
11.7 (3.9, 21.1)
63 (25 -130)
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Table 3 Comparison of the GGE of the muesli bar and coefficient of variation when the incremental area under the curve was calculated by measuring blood glucose using the CGMS with readings taken every 5 minutes compared with readings taken every 15 minutes for the first hour and every 30 minutes for the second hour 5-minute readings
Bar and glucose consumed on different days (n = 7) Bar and glucose on same day (n = 7)
Readings every 15 minutes for first hour and every 30 minutes for second hour
Average GGE/serve (g) 21.4 (10.0, 41.1)
CV (%) 36
Average GGE/serve (g) 22.6 (7.8, 47.4)
20.5 (15.1, 27.5)
63
20.7 (16.0, 30.3)
the intraindividual variability in GGE measurements could be reduced by measuring the food and drink in 1 day. The study was carried out in the same way, as described above, except that the test food and reference drink were measured on the same day, one after the other, on 3 consecutive days. The participants were randomized to the order in which they received the drink and the bar on each day. Before receiving the second food on the same day (after 120 minutes), the CGMS was downloaded. The participant was then given the other food (either the muesli bar or the 50-g reference drink) and asked to sit quietly for a further 120 minutes. After 120 minutes, another SMBG was taken and entered into the CGMS. The participants were then given lunch and allowed to leave the clinic for the day. Values for the GGE/50-g serve of the bar for the CGMS only were also calculated using the blood glucose results at 0, 15, 30, 45, 60, 90, and 120 minutes rather than with readings taken every 5 minutes, as used above. The GGE/ 50-g serve and its variability calculated using 5-minute readings were compared with the corresponding GGE/50-g serve and variability when readings at 15, 30, 45, 60, 90 and 120 minutes were used using the nonparametric Wilcoxon signed-rank test. 3. Results Table 1 presents the average IAUC for glucose and muesli bar and the average GGE values for the 3 occasions they were measured by the CGMS, venous, and capillary blood samples, the pooled intraindividual standard deviation, and the variability in the measurement by each method (CV). The IAUCs of both glucose and muesli bar were significantly lower when measured using the CGMS or venous sampling methods than using the capillary method. The CV of glucose by venous blood sampling was significantly higher than by capillary blood sampling. The GGE of the bar was 21.4 g/serve for the CGMS, 16.6 g/serve for the venous samples, and 17.4 g/serve for the capillary samples, and these values were not statistically different. The coefficients of variation for the GGE/serve were 36% for the CGMS and venous sampling methods and 30% for the capillary samples, and these differences were not significantly different.
CV (%) 45 71
The GGE of the bar using the CGMS method only was also calculated when the bar and the drink were measured on the same day. Table 2 presents the average GGE values for the 3 occasions they were measured, the pooled intraindividual standard deviation, and the variability in the measurement by each method. The intraindividual CV for the average GGE/50g serve was 64%, which was higher than the 36% variability reported when the bar and reference drink were measured on separate days. However, these differences were not statistically different. Table 3 presents the GGE values for the CGMS only when they were calculated using readings taken every 5 minutes compared with readings taken every 15 minutes for the first hour and every 30 minutes thereafter, up to 120 minutes. These are shown when the bar and drink were consumed on the same day and when the bar and drink were consumed on separate days. There were no statistically significant differences in the average GGE of the bar or the variability of the measurements regardless of how frequently interstitial glucose values was measured over the 2 hours. 4. Discussion Interestingly, the main finding of this study is the enormous variability in individual response to foods, with an average CV of about 30% in all 3 methods. This finding has also been found by Wolever et al [7]. Although there were no significant difference in the GGE values between the 3 methods, the IAUC of capillary blood sampling is greater than by the other 2 methods. A larger IAUC results in better sensitivity and allows smaller differences between foods to be detected. This larger IAUC may be responsible for the fact that the CV with capillary blood sampling is significantly lower than venous blood sampling for the glucose, but not for the bar—the IAUC of glucose using the capillary method is much higher than the IAUC by the venous method and the respective IAUCs in the bar. A previous study found that within-subject variation in response to 3 glucose reference drinks when venous blood was collected was double that when capillary blood was collected [7]. However, because measurements were carried
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out in various locations using a range of methods of plasma glucose analysis and different individuals, this could have been due to factors other than the capillary and venous blood sampling methods. Another study measuring glycemic response using venous and capillary samples taken simultaneously was carried out by Wolever and Bolognesi [20]. The study determined the glycemic response of 4 different foods by venous and capillary blood samples. The study concluded that capillary measurements were a more precise way of assessing glycemic response of foods because of the greater absolute differences between food and greater heterogeneity between means, suggesting that more experimental power was obtained. None of the measurements on the individuals were repeated more than once, so no information was gained about the variability in capillary and venous measurements. This study is the first of its kind to investigate the use of a CGMS to monitor postprandial blood glucose response of foods to determine the glycemic response of foods. It has been reported that there can be a lag between blood and interstitial fluid measurements when blood glucose values are changing rapidly [8,12,13]. This does not appear to affect the measurement of blood glucose response to food, because GGE measurements were not significantly different between the CGMS, venous, and capillary blood sampling methods. Measuring the bar and the drink in 1 day, one after the other, increased the variability in GGE measurements; though because of the large variability in the measurements and small numbers, the variability was not significantly different. It is a well-known phenomenon that there is diurnal variation in insulin, with insulin sensitivity decreasing progressively over the day [21-23]. It has also been shown that a previous meal can affect individual response to a subsequent food or meal, with glycemic response being lower when a low GI meal is consumed before the test food or meal than when a high GI meal is consumed [24-27]. Subjects were randomized to the order in which they received the bar and glucose reference to minimize these effects. However, it appears that the variability in measurements due to the second meal effect and the decrease in insulin sensitivity is greater than the variability due to factors that vary in individuals from day to day, such as the amount of physical activity on the days preceding the test meal [16], the alcohol consumption on the night before the test meal [17], and the exact length of the overnight fast [18]. Therefore, it can be concluded that the reference glucose and test food should not be measured on the same day. They should continue to be measured in the morning after an overnight fast, on separate days. Surprisingly, carrying out more frequent glucose readings with the CGMS did not reduce the variability of the GGE measurements. It can therefore be concluded that the current regimen of measuring blood glucose every quarter of an hour for the first hour and every half hour for the second hour is appropriate.
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In conclusion, the results of this study show that the GGE of a muesli bar calculated using 3 different blood sampling methods does not give significantly different GGE values for the food. Although venous blood sampling was comparable to capillary blood sampling for determining the GGE of a muesli bar, this methodology still requires regular blood sampling of the participant. The CGMS on the other hand measures blood glucose values in the interstitial fluid over 72 hours and therefore opens more opportunities for following foods for longer and at other periods during the day. Although this study is limited by small numbers and a high variability in the measurements, the results of this study suggest that further work should be carried out to compare the CGMS with capillary blood sampling in a larger range of foods and more individuals to ensure that the 2 methods give the foods the same relative ranking in terms of their glycemic response. If this is found to be the case, the CGMS may be able to be used as an alternative to capillary blood sampling for measuring the glycemic response of foods.
Acknowledgment This study was funded by the New Zealand Foundation for Science, Research and Technology. The authors thank the participants who took part in the research.
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