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The study proposed to recruit approximately 435 children and young people who have T1D and who regularly use Dexcom continuous glucose monitoring (CGM). Recruitment was be via their local dietitian. The dietitian was asked to provide baseline information about the participants which will include demographic data and information on clinical data, treatment and anthropometrics. Participants will be asked to provide access to Dexcom CGM data throughout the period of recording. Participants were issued with, for seven consecutive days, two survey questionnaires, one in the morning at breakfast time and the other in the evening. The morning survey will include questions on the breakfast meal (including a photograph of the meal) and insulin dosage, similarly the evening survey will also include questions on diabetes management and food and fluid intake in addition to questions on activities all of which took place during the four-hour postprandial period. These data will be statistically described using univariate, bivariate and multivariate analysis.
This is a quantitative observational study. Dexcom CGM data was collected for the period recording. Retrospective CGM data was collected to assess glucose variability during the day and night time periods. The Participants were then asked to provide information for seven days about their breakfast meal and the four hour post meal period. This included information on the type of meal consumed, a photograph of the meal and their diabetes management for the meal for example the insulin dose amount and timing. For the four hour post meal period the participants were asked about any adjustments they had to make to their diabetes management for example the treatment of high or low glucose readings, any snacks they ate and any activities they took part in. They were also asked to describe their mood during the post meal period.
Recruitment - Paediatric diabetes dietitians, working across the United Kingdom (UK), were enrolled to help recruit participants and become principal investigators (PI) for their site.
As this was an observational study there was no power calculation. The sample size was calculated from the number of dietitians that were likely to be available to help with recruitment; this was estimated to be around 32 and was based on the number that had already been approached. It was felt that they would have capacity to recruit 13-14 participants and this would result in 435 participants.
Methodology Baseline data
In order to make comparisons between relevant variables and glucose levels, the following baseline data will be collected from the dietitians and sent to the chief investigator, along with the artificial identifier on the Excel spreadsheet as discussed earlier at the stage of recruitment of participants:
Parent's email address Sex, date of birth and recent weight and height (for calculation of BMI and BMI centile) and date of when this was taken Date of diagnosis of T1D Last four HbA1c Total daily insulin dose (TDD) Insulin: carbohydrate ratios (ICR) and Insulin Sensitivity Factor (ISF) Current insulin regimen - including the type of insulin prescribed and if applicable type of insulin pump i.e. open or closed loop system.
Glucose measurement data on interstitial glucose was be collected via Dexcom CGM. The Dexcom CGM data will be accessed by a research 'Clarity Clinic' with Dexcom CLARITY® Clinic Portal (Dexcom In, San Diego, California (CA), USA). The researcher was the administrator of this clinic. Once the local dietitian had recruited, the participant's parent's email address will be sent to the researcher along with the baseline information/data as described above. The researcher, as administrator of the Clarity Clinic account, then invited the participant, via email, to be added to the clinic. Once the invite has been accepted, it stood for the period of the recording i.e. until all the seven day breakfast recording period was completed. Once the participant had submitted their last questionnaire, they were removed from the Dexcom CLARITY® Clinic Portal.
The participants were not asked to make changes to their diabetes management and their breakfast meal. The participants were asked to submit two daily questionnaires (a morning and post-meal questionnaire) for seven days about their breakfast meal and the postprandial period and email a photograph of the breakfast meal.
The morning questionnaire was about the breakfast meal and included the following questions:
Participant's artificial identifier Date (of when meal was taken) The total average daily insulin dose (both bolus and basal insulin) if known (participant will only be asked to provide this once) Food eaten at breakfast including portion size, type and brand Drinks taken at breakfast including volume, type and brand The total carbohydrate count of breakfast in grams The number of units of insulin taken with breakfast How many units were given for a correction dose The type of bolus (for those on an insulin pump) The time of when the insulin dose was administered The time that breakfast started and ended How the bolus was calculated The amount of breakfast that was consumed (all, ¾, ½, ¼, none)
The post meal questionnaire included the following questions:
Participant's artificial identifier Date (of when meal was taken) Details of any hypo's in the four-hour postprandial period (time, treatment) Details of correction doses given in the four-hour postprandial period (whether in response to Dexcom CGM, times and number of units if insulin) Details of snacks taken in the four-hour postprandial period (type and amount of carbohydrate, responses to Dexcom CGM, number of units of insulin) Details of drinks taken in the four-hour postprandial period (volume, type/brand, carbohydrate amount if applicable) Details of any other adjustments made to insulin and or carbohydrate Type and duration of all physical activities undertaken during the 4-hour post prandial period Details of insulin adjustments made for physical activities Details of any addition information e.g. mood, menstruating, illness, stressors
Data analysis This will be a mix of univariate, bivariate and multivariate analysis as this is best suited to describing, summarising and visualising these data. Outputs will include the distribution of glucose levels post-breakfast to determine the spread and dispersion of the data.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Breakfast | Other | Breakfast meal |
| Measure | Description | Time Frame |
|---|---|---|
| Mean Postprandial Glucose | Mean CGM reading for 387 breakfast meals over 4 hour postprandial period | From baseline (start of meal) to 4 hours postprandial at 5min intervals |
| Measure | Description | Time Frame |
|---|---|---|
| Mean Glucose Excursion | The excursion is calculated by subtracting the baseline glucose from each 5min CGM reading over 4 hours. For example if at baseline the glucose is 9mmol/l and at 5min postprandial it is 9.3mmol/l the excursion at 5min is 0.3mmol/l. The mean excursion is then calculated over 4 hours for each breakfast meal (381) which had a glucose reading at baseline. | From baseline (start of meal) to 4 hours postprandial at 5min intervals |
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Inclusion Criteria:
Exclusion Criteria:
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Children and young people aged 1-17 who have type 1 diabetes
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| Name | Affiliation | Role |
|---|---|---|
| Julie Johnson, MNutr | University of Stirling | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Faculty of Health Sciences and Sport | Stirling | Stirlingshire | FK9 4LA | United Kingdom |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 24319123 | Result | Barnea-Goraly N, Raman M, Mazaika P, Marzelli M, Hershey T, Weinzimer SA, Aye T, Buckingham B, Mauras N, White NH, Fox LA, Tansey M, Beck RW, Ruedy KJ, Kollman C, Cheng P, Reiss AL; Diabetes Research in Children Network (DirecNet). Alterations in white matter structure in young children with type 1 diabetes. Diabetes Care. 2014 Feb;37(2):332-40. doi: 10.2337/dc13-1388. Epub 2013 Dec 6. | |
| 31177185 |
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96 participants were enrolled 7 participants did not respond or dropped out of the study before sharing CGM data.
89 participants shared their CGM data for glucose variability analysis and of these 74 submitted the breakfast and postprandial questionnaires of which 71 completed with corresponding CGM data.
Participants were enrolled from February - November 2021 via their local diabetes centres
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| ID | Title | Description |
|---|---|---|
| FG000 | Glucose Variability Then Breakfast and Postprandial Questionnaires | Collection of CGM data to assess glucose variability and glucose levels before and during the 4 hours postprandial period after breakfast meal |
| Title | Milestones | Reasons Not Completed | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Glucose Variability (CGM Data) |
| ||||||||||||||||
| Breakfast and Postprandial Questionnaire |
|
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| ID | Title | Description |
|---|---|---|
| BG000 | Glucose Variability and Postprandial Glucose | Collection of CGM data to assess glucose variability |
| Units | Counts |
|---|---|
| Participants |
|
| Title | Description | Population Description | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Denominator Units Selected | Denominators | Classes |
|---|---|---|---|---|---|---|---|---|---|
| Age, Continuous | Mean |
| Type | Title | Description | Population Description | Reporting Status | Anticipated Posting Date | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Time Frame | Units Analyzed | Denominator Units Selected | Arm/Group Information | Denominators | Classes | Analyses | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Primary | Mean Postprandial Glucose | Mean CGM reading for 387 breakfast meals over 4 hour postprandial period | CGM data over 4-hour postprandial period for 387 breakfast meals consumed by 71 participants | Posted | Mean | Standard Deviation | mmol/l | From baseline (start of meal) to 4 hours postprandial at 5min intervals | Breakfast meals | Breakfast meals |
|
|
One year
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| ID | Title | Description | Deaths (Affected) | Deaths (At Risk) | Serious Events (Affected) | Serious Events (At Risk) | Other Events (Affected) | Other Events (At Risk) |
|---|---|---|---|---|---|---|---|---|
| EG000 | Glucose Variability Then Breakfast and Postprandial Questionnaires | Collection of CGM data to assess glucose variability and glucose levels before and during the 4 hours postprandial period after breakfast meal |
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| Title | Organization | Phone | Extension | |
|---|---|---|---|---|
| Julie Johnson | University of Stirling | 07815893076 | julie.johnson1@stir.ac.uk |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP | Yes | Yes | No | Study Protocol and Statistical Analysis Plan | May 15, 2021 | Oct 7, 2024 | Prot_SAP_000.pdf |
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| ID | Term |
|---|---|
| D003922 | Diabetes Mellitus, Type 1 |
| ID | Term |
|---|---|
| D003920 | Diabetes Mellitus |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
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| ID | Term |
|---|---|
| D062408 | Breakfast |
| ID | Term |
|---|---|
| D062407 | Meals |
| D005502 | Food |
| D000066888 | Diet, Food, and Nutrition |
| D010829 | Physiological Phenomena |
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| Peak Glucose Excursion | The peak glucose excursions calculated from the CGM readings for 381 breakfast meals over 4 hour postprandial period - this is the highest excursion over the 4 hour period | From baseline (start of meal) to 4 hours postprandial at 5 min intervals |
| Time to Peak | From CGM data. This is the time of the highest excursion over the 4-hour period | From baseline (start of meal) to 4 hours postprandial at 5 min intervals |
| Area Under the Curve | Calculated from the CGM readings for 381 breakfast meals over 4 hour postprandial period | From baseline (start of meal) to 4 hours postprandial at 5 min intervals |
| Coefficient of Variation Percentage | Calculated from the CGM reading for 387 breakfast meals over 4 hour postprandial period | From baseline (start of meal) to 4 hours postprandial |
| Time in Range (Minutes) | Calculated from the CGM readings for 387 breakfast meals over 4 hour postprandial period. Time in range refers to the time spent with a glucose reading between 3.9-10mmol/l | From baseline (start of meal) to 4 hours postprandial at 5min intervals |
| CV% and Glycaemic Index (GI) of Breakfast Meal | The CV% taken from CGM data over a 4hour postprandial period from the ingestion of breakfast meals that had a high and medium glycaemic index | From baseline (start of meal) to 4 hours postprandial |
| Mean Postprandial Glucose and Glycaemic Index of Breakfast Meal | Mean postprandial glucose from CGM data after ingestion of breakfast meal by three categories of glycaemic index (low medium and high) | From baseline (start of meal) to 4 hours postprandial |
| Mean Postprandial Glucose and Glycaemic Load of Breakfast Meals | Mean postprandial glucose from CGM data after ingestion of breakfast meals across three categories of glycaemic load (low, medium and high) | From baseline (start of meal) to 4 hours postprandial |
| Time to Peak Across Categories of Glycaemic Load | CGM data over 4 hour postprandial period for three categories of glycaemic load. | From baseline (start of meal) to 4 hours postprandial |
| Mean Postprandial Glucose and Type of Breakfast Meal | Mean postprandial glucose from CGM data over four hours postprandial period after ingestion of breakfast meal containing a ready to eat cereal compared with breakfast meals containing a protein food | From baseline (start of meal) to 4 hours postprandial |
| Coefficient of Variation Percentage Over 90 Days | This measures the amount of dispersion (spread) around the mean. It is calculated from the standard deviation divided by the mean and multiplied by 100 to give a percentage. This was taken from the standard deviation and mean from up to 90 days of retrospective CGM data (mean of 79.3 days of CGM readings). This represents how much glucose moves up and down. %CV of 36% or less indicates stable glucose | 90 days |
| Diurnal Coefficient of Variation Percentage Over 90 Days | This measures the amount of dispersion (spread) around the mean. It is calculated from the standard deviation divided by the mean and multiplied by 100 to give a percentage. This was taken from the standard deviation and mean from up to 90 days of retrospective CGM data (mean of 79.3 days of CGM readings) for the 06.00-22.00 period of time. This represents how much glucose moves up and down. A CV% of 36% or less indicates stable glucose | 90 days of CGM data |
| Nocturnal Coefficient of Variation Percentage Over 90 Days | This measures the amount of dispersion (spread) around the mean. It is calculated from the standard deviation divided by the mean and multiplied by 100 to give a percentage. This was taken from the standard deviation and mean from up to 90 days of retrospective CGM data (mean of 79.3 days of CGM readings) for the 22.00 - 06.00 period of time. This represents how much glucose moves up and down. A CV% of 36% or less indicates stable glucose | 90 days of CGM data |
| Result |
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| 25998293 | Result | Bell KJ, Smart CE, Steil GM, Brand-Miller JC, King B, Wolpert HA. Impact of fat, protein, and glycemic index on postprandial glucose control in type 1 diabetes: implications for intensive diabetes management in the continuous glucose monitoring era. Diabetes Care. 2015 Jun;38(6):1008-15. doi: 10.2337/dc15-0100. |
| 20432533 | Result | Bluestone JA, Herold K, Eisenbarth G. Genetics, pathogenesis and clinical interventions in type 1 diabetes. Nature. 2010 Apr 29;464(7293):1293-300. doi: 10.1038/nature08933. |
| 28055230 | Result | Bode BW, Johnson JA, Hyveled L, Tamer SC, Demissie M. Improved Postprandial Glycemic Control with Faster-Acting Insulin Aspart in Patients with Type 1 Diabetes Using Continuous Subcutaneous Insulin Infusion. Diabetes Technol Ther. 2017 Jan;19(1):25-33. doi: 10.1089/dia.2016.0350. Epub 2017 Jan 5. |
| 11679447 | Result | Boland E, Monsod T, Delucia M, Brandt CA, Fernando S, Tamborlane WV. Limitations of conventional methods of self-monitoring of blood glucose: lessons learned from 3 days of continuous glucose sensing in pediatric patients with type 1 diabetes. Diabetes Care. 2001 Nov;24(11):1858-62. doi: 10.2337/diacare.24.11.1858. |
| 28483786 | Result | Bowering K, Case C, Harvey J, Reeves M, Sampson M, Strzinek R, Bretler DM, Bang RB, Bode BW. Faster Aspart Versus Insulin Aspart as Part of a Basal-Bolus Regimen in Inadequately Controlled Type 2 Diabetes: The onset 2 Trial. Diabetes Care. 2017 Jul;40(7):951-957. doi: 10.2337/dc16-1770. Epub 2017 May 8. |
| 635569 | Result | Bunn HF, Gabbay KH, Gallop PM. The glycosylation of hemoglobin: relevance to diabetes mellitus. Science. 1978 Apr 7;200(4337):21-7. doi: 10.1126/science.635569. |
| 30259644 | Result | Buse JB, Carlson AL, Komatsu M, Mosenzon O, Rose L, Liang B, Buchholtz K, Horio H, Kadowaki T. Fast-acting insulin aspart versus insulin aspart in the setting of insulin degludec-treated type 1 diabetes: Efficacy and safety from a randomized double-blind trial. Diabetes Obes Metab. 2018 Dec;20(12):2885-2893. doi: 10.1111/dom.13545. Epub 2018 Oct 10. |
| 3501693 | Result | Chugani HT, Phelps ME, Mazziotta JC. Positron emission tomography study of human brain functional development. Ann Neurol. 1987 Oct;22(4):487-97. doi: 10.1002/ana.410220408. |
| 29999222 | Result | Danne T, Phillip M, Buckingham BA, Jarosz-Chobot P, Saboo B, Urakami T, Battelino T, Hanas R, Codner E. ISPAD Clinical Practice Consensus Guidelines 2018: Insulin treatment in children and adolescents with diabetes. Pediatr Diabetes. 2018 Oct;19 Suppl 27:115-135. doi: 10.1111/pedi.12718. No abstract available. |
| 14514571 | Result | Derr R, Garrett E, Stacy GA, Saudek CD. Is HbA(1c) affected by glycemic instability? Diabetes Care. 2003 Oct;26(10):2728-33. doi: 10.2337/diacare.26.10.2728. |
| 30058221 | Result | DiMeglio LA, Acerini CL, Codner E, Craig ME, Hofer SE, Pillay K, Maahs DM. ISPAD Clinical Practice Consensus Guidelines 2018: Glycemic control targets and glucose monitoring for children, adolescents, and young adults with diabetes. Pediatr Diabetes. 2018 Oct;19 Suppl 27:105-114. doi: 10.1111/pedi.12737. No abstract available. |
| 3517648 | Result | Eisenbarth GS. Type I diabetes mellitus. A chronic autoimmune disease. N Engl J Med. 1986 May 22;314(21):1360-8. doi: 10.1056/NEJM198605223142106. No abstract available. |
| 29527759 | Result | Faber EM, van Kampen PM, Clement-de Boers A, Houdijk ECAM, van der Kaay DCM. The influence of food order on postprandial glucose levels in children with type 1 diabetes. Pediatr Diabetes. 2018 Jun;19(4):809-815. doi: 10.1111/pedi.12640. Epub 2018 Mar 12. |
| 17705686 | Result | Gandrud LM, Xing D, Kollman C, Block JM, Kunselman B, Wilson DM, Buckingham BA. The Medtronic Minimed Gold continuous glucose monitoring system: an effective means to discover hypo- and hyperglycemia in children under 7 years of age. Diabetes Technol Ther. 2007 Aug;9(4):307-16. doi: 10.1089/dia.2007.0026. |
| 28675686 | Result | Gingras V, Taleb N, Roy-Fleming A, Legault L, Rabasa-Lhoret R. The challenges of achieving postprandial glucose control using closed-loop systems in patients with type 1 diabetes. Diabetes Obes Metab. 2018 Feb;20(2):245-256. doi: 10.1111/dom.13052. Epub 2017 Aug 10. |
| 19324943 | Result | Gonder-Frederick LA, Zrebiec JF, Bauchowitz AU, Ritterband LM, Magee JC, Cox DJ, Clarke WL. Cognitive function is disrupted by both hypo- and hyperglycemia in school-aged children with type 1 diabetes: a field study. Diabetes Care. 2009 Jun;32(6):1001-6. doi: 10.2337/dc08-1722. Epub 2009 Mar 26. |
| 15043684 | Result | Heptulla RA, Allen HF, Gross TM, Reiter EO. Continuous glucose monitoring in children with type 1 diabetes: before and after insulin pump therapy. Pediatr Diabetes. 2004 Mar;5(1):10-5. doi: 10.1111/j.1399-543X.2004.00035.x. |
| 7678404 | Result | Kaiser N, Sasson S, Feener EP, Boukobza-Vardi N, Higashi S, Moller DE, Davidheiser S, Przybylski RJ, King GL. Differential regulation of glucose transport and transporters by glucose in vascular endothelial and smooth muscle cells. Diabetes. 1993 Jan;42(1):80-9. doi: 10.2337/diab.42.1.80. |
| 8799621 | Result | Koivisto VA, Stevens LK, Mattock M, Ebeling P, Muggeo M, Stephenson J, Idzior-Walus B. Cardiovascular disease and its risk factors in IDDM in Europe. EURODIAB IDDM Complications Study Group. Diabetes Care. 1996 Jul;19(7):689-97. doi: 10.2337/diacare.19.7.689. |
| 29873107 | Result | Lopez PE, Evans M, King BR, Jones TW, Bell K, McElduff P, Davis EA, Smart CE. A randomized comparison of three prandial insulin dosing algorithms for children and adolescents with Type 1 diabetes. Diabet Med. 2018 Oct;35(10):1440-1447. doi: 10.1111/dme.13703. Epub 2018 Jun 19. |
| 29144814 | Result | Mangrola D, Cox C, Furman AS, Krishnan S, Karakas SE. SELF BLOOD GLUCOSE MONITORING UNDERESTIMATES HYPERGLYCEMIA AND HYPOGLYCEMIA AS COMPARED TO CONTINUOUS GLUCOSE MONITORING IN TYPE 1 AND TYPE 2 DIABETES. Endocr Pract. 2018 Jan;24(1):47-52. doi: 10.4158/EP-2017-0032. Epub 2017 Nov 16. |
| 24170697 | Result | Marzelli MJ, Mazaika PK, Barnea-Goraly N, Hershey T, Tsalikian E, Tamborlane W, Mauras N, White NH, Buckingham B, Beck RW, Ruedy KJ, Kollman C, Cheng P, Reiss AL; Diabetes Research in Children Network (DirecNet). Neuroanatomical correlates of dysglycemia in young children with type 1 diabetes. Diabetes. 2014 Jan;63(1):343-53. doi: 10.2337/db13-0179. Epub 2013 Oct 29. |
| 25488901 | Result | Mauras N, Mazaika P, Buckingham B, Weinzimer S, White NH, Tsalikian E, Hershey T, Cato A, Cheng P, Kollman C, Beck RW, Ruedy K, Aye T, Fox L, Arbelaez AM, Wilson D, Tansey M, Tamborlane W, Peng D, Marzelli M, Winer KK, Reiss AL; Diabetes Research in Children Network (DirecNet). Longitudinal assessment of neuroanatomical and cognitive differences in young children with type 1 diabetes: association with hyperglycemia. Diabetes. 2015 May;64(5):1770-9. doi: 10.2337/db14-1445. Epub 2014 Dec 8. |
| 26512024 | Result | Mazaika PK, Weinzimer SA, Mauras N, Buckingham B, White NH, Tsalikian E, Hershey T, Cato A, Aye T, Fox L, Wilson DM, Tansey MJ, Tamborlane W, Peng D, Raman M, Marzelli M, Reiss AL; Diabetes Research in Children Network (DirecNet). Variations in Brain Volume and Growth in Young Children With Type 1 Diabetes. Diabetes. 2016 Feb;65(2):476-85. doi: 10.2337/db15-1242. Epub 2015 Oct 28. |
| 17563334 | Result | McDonnell CM, Northam EA, Donath SM, Werther GA, Cameron FJ. Hyperglycemia and externalizing behavior in children with type 1 diabetes. Diabetes Care. 2007 Sep;30(9):2211-5. doi: 10.2337/dc07-0328. Epub 2007 Jun 11. |
| 17575089 | Result | Perantie DC, Wu J, Koller JM, Lim A, Warren SL, Black KJ, Sadler M, White NH, Hershey T. Regional brain volume differences associated with hyperglycemia and severe hypoglycemia in youth with type 1 diabetes. Diabetes Care. 2007 Sep;30(9):2331-7. doi: 10.2337/dc07-0351. Epub 2007 Jun 15. |
| 18208449 | Result | Perantie DC, Lim A, Wu J, Weaver P, Warren SL, Sadler M, White NH, Hershey T. Effects of prior hypoglycemia and hyperglycemia on cognition in children with type 1 diabetes mellitus. Pediatr Diabetes. 2008 Apr;9(2):87-95. doi: 10.1111/j.1399-5448.2007.00274.x. Epub 2008 Jan 12. |
| 21953611 | Result | Perantie DC, Koller JM, Weaver PM, Lugar HM, Black KJ, White NH, Hershey T. Prospectively determined impact of type 1 diabetes on brain volume during development. Diabetes. 2011 Nov;60(11):3006-14. doi: 10.2337/db11-0589. Epub 2011 Sep 27. |
| 28117542 | Result | Piechowiak K, Dzygalo K, Szypowska A. The additional dose of insulin for high-protein mixed meal provides better glycemic control in children with type 1 diabetes on insulin pumps: randomized cross-over study. Pediatr Diabetes. 2017 Dec;18(8):861-868. doi: 10.1111/pedi.12500. Epub 2017 Jan 24. |
| 18458138 | Result | Ryan RL, King BR, Anderson DG, Attia JR, Collins CE, Smart CE. Influence of and optimal insulin therapy for a low-glycemic index meal in children with type 1 diabetes receiving intensive insulin therapy. Diabetes Care. 2008 Aug;31(8):1485-90. doi: 10.2337/dc08-0331. Epub 2008 May 5. |
| 22268422 | Result | Smart CE, King BR, McElduff P, Collins CE. In children using intensive insulin therapy, a 20-g variation in carbohydrate amount significantly impacts on postprandial glycaemia. Diabet Med. 2012 Jul;29(7):e21-4. doi: 10.1111/j.1464-5491.2012.03595.x. |
| 24170749 | Result | Smart CE, Evans M, O'Connell SM, McElduff P, Lopez PE, Jones TW, Davis EA, King BR. Both dietary protein and fat increase postprandial glucose excursions in children with type 1 diabetes, and the effect is additive. Diabetes Care. 2013 Dec;36(12):3897-902. doi: 10.2337/dc13-1195. Epub 2013 Oct 29. |
| 30062718 | Result | Smart CE, Annan F, Higgins LA, Jelleryd E, Lopez M, Acerini CL. ISPAD Clinical Practice Consensus Guidelines 2018: Nutritional management in children and adolescents with diabetes. Pediatr Diabetes. 2018 Oct;19 Suppl 27:136-154. doi: 10.1111/pedi.12738. No abstract available. |
| 21525442 | Result | Standl E, Schnell O, Ceriello A. Postprandial hyperglycemia and glycemic variability: should we care? Diabetes Care. 2011 May;34 Suppl 2(Suppl 2):S120-7. doi: 10.2337/dc11-s206. |
| 25496062 | Result | Tansey M, Beck R, Ruedy K, Tamborlane W, Cheng P, Kollman C, Fox L, Weinzimer S, Mauras N, White NH, Tsalikian E; Diabetes Research in Children Network (DirecNet). Persistently high glucose levels in young children with type 1 diabetes. Pediatr Diabetes. 2016 Mar;17(2):93-100. doi: 10.1111/pedi.12248. Epub 2014 Dec 11. |
| 8366922 | Result | Diabetes Control and Complications Trial Research Group; Nathan DM, Genuth S, Lachin J, Cleary P, Crofford O, Davis M, Rand L, Siebert C. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993 Sep 30;329(14):977-86. doi: 10.1056/NEJM199309303291401. |
| 8826962 | Result | The absence of a glycemic threshold for the development of long-term complications: the perspective of the Diabetes Control and Complications Trial. Diabetes. 1996 Oct;45(10):1289-98. |
| years |
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| Sex: Female, Male | Count of Participants | Participants |
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| Race and Ethnicity Not Collected | Race and Ethnicity were not collected from any participant. | Count of Participants | Participants |
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| Region of Enrollment | Number | participants |
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| HbA1c | Mean | Standard Deviation | mmol/mol |
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| Disease duration | Median | Inter-Quartile Range | years |
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| Insulin regimen | Count of Participants | Participants |
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| Participants |
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| Breakfast meals |
|
|
| Secondary | Mean Glucose Excursion | The excursion is calculated by subtracting the baseline glucose from each 5min CGM reading over 4 hours. For example if at baseline the glucose is 9mmol/l and at 5min postprandial it is 9.3mmol/l the excursion at 5min is 0.3mmol/l. The mean excursion is then calculated over 4 hours for each breakfast meal (381) which had a glucose reading at baseline. | CGM data over 4-hour postprandial period for 381 breakfast meals consumed by 71 participants | Posted | Mean | Standard Deviation | mmol/l | From baseline (start of meal) to 4 hours postprandial at 5min intervals | Breakfast meals with glucose at baseline | Breakfast meals with glucose at baseline |
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| Secondary | Peak Glucose Excursion | The peak glucose excursions calculated from the CGM readings for 381 breakfast meals over 4 hour postprandial period - this is the highest excursion over the 4 hour period | CGM data over 4-hour postprandial period for 381 breakfast meals consumed by 71 participants | Posted | Mean | Standard Deviation | mmol/l | From baseline (start of meal) to 4 hours postprandial at 5 min intervals | Breakfast meals with glucose at baseline | Breakfast meals with glucose at baseline |
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| Secondary | Time to Peak | From CGM data. This is the time of the highest excursion over the 4-hour period | CGM data over 4-hour postprandial period for 381 breakfast meals consumed by 71 participants | Posted | Mean | Standard Deviation | Minutes | From baseline (start of meal) to 4 hours postprandial at 5 min intervals | Breakfast meals with glucose at baseline | Breakfast meals with glucose at baseline |
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| Secondary | Area Under the Curve | Calculated from the CGM readings for 381 breakfast meals over 4 hour postprandial period | CGM data over 4-hour postprandial period for 381 breakfast meals consumed by 71 participants | Posted | Mean | Standard Deviation | (mmol/l)*min | From baseline (start of meal) to 4 hours postprandial at 5 min intervals | Breakfast meals with glucose at baseline | Breakfast meals with glucose at baseline |
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| Secondary | Coefficient of Variation Percentage | Calculated from the CGM reading for 387 breakfast meals over 4 hour postprandial period | CGM data over 4-hour postprandial period for 387 breakfast meals consumed by 71 participants | Posted | Mean | Standard Deviation | percentage | From baseline (start of meal) to 4 hours postprandial | Breakfast meals | Breakfast meals |
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| Secondary | Time in Range (Minutes) | Calculated from the CGM readings for 387 breakfast meals over 4 hour postprandial period. Time in range refers to the time spent with a glucose reading between 3.9-10mmol/l | CGM data over 4-hour postprandial period for 387 breakfast meals consumed by 71 participants | Posted | Mean | Standard Deviation | Minutes | From baseline (start of meal) to 4 hours postprandial at 5min intervals | Breakfast meals | Breakfast meals |
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| Secondary | CV% and Glycaemic Index (GI) of Breakfast Meal | The CV% taken from CGM data over a 4hour postprandial period from the ingestion of breakfast meals that had a high and medium glycaemic index | A comparison of breakfast meals which had a low, medium and high glycaemic index | Posted | Mean | Standard Deviation | percentage | From baseline (start of meal) to 4 hours postprandial | Breakfast meals with known GI | Breakfast meals with known GI |
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| Secondary | Mean Postprandial Glucose and Glycaemic Index of Breakfast Meal | Mean postprandial glucose from CGM data after ingestion of breakfast meal by three categories of glycaemic index (low medium and high) | A comparison of breakfast meals which had a low, medium and high glycaemic index | Posted | Mean | Standard Deviation | mmol/l | From baseline (start of meal) to 4 hours postprandial | Breakfast meals | Breakfast meals |
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| Secondary | Mean Postprandial Glucose and Glycaemic Load of Breakfast Meals | Mean postprandial glucose from CGM data after ingestion of breakfast meals across three categories of glycaemic load (low, medium and high) | A comparison of breakfast meals which had a low, medium and high glycaemic load | Posted | Mean | Standard Deviation | mmol/l | From baseline (start of meal) to 4 hours postprandial | Breakfast meals | Breakfast meals |
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| Secondary | Time to Peak Across Categories of Glycaemic Load | CGM data over 4 hour postprandial period for three categories of glycaemic load. | A comparison of breakfast meals which had a baseline glucose for low medium and high glycaemic load | Posted | Mean | Standard Deviation | Minutes | From baseline (start of meal) to 4 hours postprandial | Breakfast meals with a baseline glucose | Breakfast meals with a baseline glucose |
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| Secondary | Mean Postprandial Glucose and Type of Breakfast Meal | Mean postprandial glucose from CGM data over four hours postprandial period after ingestion of breakfast meal containing a ready to eat cereal compared with breakfast meals containing a protein food | The is was a sub group analysis of 'Breakfast cereal only' meals vs 'breakfast meals with added protein food' | Posted | Mean | Standard Deviation | mmol/l | From baseline (start of meal) to 4 hours postprandial | Breakfast meals | Breakfast meals |
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| Secondary | Coefficient of Variation Percentage Over 90 Days | This measures the amount of dispersion (spread) around the mean. It is calculated from the standard deviation divided by the mean and multiplied by 100 to give a percentage. This was taken from the standard deviation and mean from up to 90 days of retrospective CGM data (mean of 79.3 days of CGM readings). This represents how much glucose moves up and down. %CV of 36% or less indicates stable glucose | %CV calculated from a mean of 79.3 days of CGM data | Posted | Mean | Standard Deviation | percentage | 90 days |
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| Secondary | Diurnal Coefficient of Variation Percentage Over 90 Days | This measures the amount of dispersion (spread) around the mean. It is calculated from the standard deviation divided by the mean and multiplied by 100 to give a percentage. This was taken from the standard deviation and mean from up to 90 days of retrospective CGM data (mean of 79.3 days of CGM readings) for the 06.00-22.00 period of time. This represents how much glucose moves up and down. A CV% of 36% or less indicates stable glucose | Diurnal CV% (06.00-22.00) calculated from 79.3 days of CGM data | Posted | Mean | Standard Deviation | percentage | 90 days of CGM data |
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| Secondary | Nocturnal Coefficient of Variation Percentage Over 90 Days | This measures the amount of dispersion (spread) around the mean. It is calculated from the standard deviation divided by the mean and multiplied by 100 to give a percentage. This was taken from the standard deviation and mean from up to 90 days of retrospective CGM data (mean of 79.3 days of CGM readings) for the 22.00 - 06.00 period of time. This represents how much glucose moves up and down. A CV% of 36% or less indicates stable glucose | Nocturnal CV% (22.00-06.00) calculated from 79.3 days of CGM data | Posted | Mean | Standard Deviation | percentage | 90 days of CGM data |
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| 0 |
| 89 |
| 0 |
| 89 |
| 0 |
| 89 |
Not provided
Not provided
| D004700 | Endocrine System Diseases |
| D001327 | Autoimmune Diseases |
| D007154 | Immune System Diseases |
| D019602 |
| Food and Beverages |
| Medium GI breakfast meal |
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| High GI breakfast meal |
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| Linear Mixed Model |
| 0.01 |
| Mean Difference (Final Values) |
| 4.4 |
| 2-Sided |
| 95 |
| 1.2 |
| 7.5 |
| Other |
| High GI vs low GI breakfast meals | Linear Mixed Model | 0.12 | a priori threshold for statistical significance <0.05 | Mean Difference (Final Values) | -2.63 | 2-Sided | 95 | -6.0 | 0.7 | Other |
| Medium GI breakfast meals |
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| High GI breakfast meals |
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| Medium glycaemic load meals |
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| High glycaemic load meals |
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| Medium glycaemic load meals |
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| High glycaemic load meals |
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| Added protein meals |
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