CClinicalTrials.gg
RecruitingNCT06273631Updated Sep 10, 2026

Effect of Different Carbohydrate Intake Patterns on Glycemic Control in Patients With Type 1 Diabetes

An interventional study of diverse carbohydrate diet and moderate carbohydrate diet in Type 1 Diabetes, Diet Intervention and Glucose Control, sponsored by Yang Tao. Recruiting at 1 site in China. Open to participants aged 18 Years to 70 Years. Per ClinicalTrials.gov, last updated 2026-09-10.

Sponsored by Yang Tao · Not applicable, Interventional, and Treatment

From the registry’s dates

  • Started Aug 2024; still recruiting 2 years 2 months later.
Phase
Not applicable
Study type
Interventional
Enrollment
80
Allocation
Randomized
Ages
18 Years to 70 Years
Sex
All
01

Study summary

This multicenter, randomized, controlled, open-label clinical trial aims to evaluate the effects of different carbohydrate intake patterns on glycemic control in adults with type 1 diabetes.

Participants will first complete a 2-week run-in period and will then be randomly assigned in a 1:1 ratio to one of two dietary groups. Both diets provide similar proportions of total energy from carbohydrates, protein, and fat, but differ in the sources of staple carbohydrates. In the moderate carbohydrate diet group, most staple foods are refined grains, whereas in the diverse carbohydrate diet group, approximately half of the staple foods are whole grains and legumes.

80 participants will follow the assigned dietary intervention for 2 weeks, followed by a 12-week follow-up period. The primary outcome is time in range (TIR), defined as the percentage of time that glucose levels are within the target range, measured using continuous glucose monitoring. Other measures of glycemic control, glycemic variability, insulin requirements, body measurements, metabolic indicators, and safety will also be evaluated. Exploratory analyses will assess potential changes in gut microbiota, immune function, and metabolomic profiles.

Read the detailed description

Medical nutrition therapy is an important component of the management of type 1 diabetes. In addition to the amount of carbohydrate consumed, the source and quality of dietary carbohydrates may influence glycemic responses and glycemic variability. However, evidence regarding the effects of different carbohydrate intake patterns in people with type 1 diabetes remains limited, particularly when glycemic outcomes are assessed using continuous glucose monitoring.

This study is designed to compare two dietary patterns that provide comparable total energy intake and the same target macronutrient distribution but differ in the sources of staple carbohydrates. Individual energy intake is determined according to each participant's estimated energy requirement. In both groups, carbohydrates provide 45%-55% of total energy, protein provides 15%-20%, and fat provides 25%-35%.

In the moderate carbohydrate diet (MCD) group, 90%-95% of staple foods are derived from refined grains. In the diverse carbohydrate diet (DCD) group, 45%-50% of staple foods are derived from refined grains and 45%-50% from whole grains and legumes. Thus, the principal difference between the two dietary patterns is the source and diversity of staple carbohydrates rather than total energy intake or overall macronutrient composition.

By minimizing differences in total energy intake and macronutrient distribution between the two groups, this study aims to evaluate whether changing the sources and diversity of dietary carbohydrates influences glycemic control and glycemic variability in people with type 1 diabetes.

In addition to clinical and metabolic assessments, exploratory analyses will evaluate changes in gut microbiota, immune function, and metabolomics to investigate potential mechanisms through which different carbohydrate intake patterns may affect glycemic control.

02

Conditions studied

  • Type 1 Diabetes
  • Diet Intervention
  • Glucose Control

Keywords

  • dietary fiber
  • autoimmunity
  • metabolomics
  • intestinal microbiota
  • time in range
03

In context

Diabetes Mellitus, Type 1

3,522 studies on the registry are indexed under Diabetes Mellitus, Type 1; 577 are open to participants now.

This study's planned enrollment of 80 is above the median of 40 across 2,649 interventional studies indexed under Diabetes Mellitus, Type 1.

Browse Diabetes Mellitus, Type 1 studies →

Lead sponsor

Yang Tao is the lead sponsor of 2 studies on the registry; 1 is open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years to 70 Years
Sexes eligible
All
Accepts healthy volunteers
No

Inclusion criteria

  1. Participants who agree to participate in the study and provide written informed consent;
  2. Diagnosed with type 1 diabetes mellitus according to the ADA 2024 criteria;
  3. Aged 18 to 70 years, inclusive;
  4. Receiving exogenous insulin therapy with a stable treatment regimen for at least 2 months before enrollment (the type of insulin should remain unchanged, while the dose may be adjusted according to blood glucose levels);
  5. Body mass index (BMI) between 18.0 and 25.0 kg/m², inclusive;
  6. Glycated hemoglobin A1c (HbA1c) \<11%.

Exclusion criteria

Exclusion Criteria:

  1. Type 1 diabetes mellitus in the honeymoon phase;
  2. Pregnant or breastfeeding women, or women for whom pregnancy cannot be ruled out;
  3. Patients who are vegetarians or are undergoing weight loss;
  4. Patients who are users of oral hypoglycemic drugs (alpha-glucosidase inhibitors, DPP-4 inhibitors, etc.);
  5. Use of glucocorticoids within 30 days before enrollment;
  6. History of severe food allergy;
  7. Patients with acute complications such as diabetic ketoacidosis (DKA) or hyperosmolar hyperglycemic state (HHS) within the previous 6 months;
  8. Patients with gastroparesis, inflammatory bowel disease or other complications;
  9. Patients with macroalbuminuria (albumin-to-creatinine ratio > 34 mg/mmol) or renal insufficiency (creatinine > 200 μmol/L);
  10. Patients with uncontrolled hyperthyroidism or hypothyroidism (Uncontrolled hyperthyroidism is defined as abnormal TSH and FT4. Uncontrolled hypothyroidism is defined as TSH > 10 mIU/L.);
  11. History of heart disease, coronary artery disease or arrhythmia;
  12. Alanine aminotransferase (ALT) or aspartate aminotransferase (AST) >3 times the upper limit of normal;
  13. History of malignant tumors; history of tumors or surgery affecting digestion or nutrient absorption. Eligibility of participants with a history of benign tumors will be determined by the investigator;
  14. Patients with other uncontrolled immune system diseases or uncontrolled infections;
  15. Alcohol abuse, drug abuse, mental disorders, or other conditions unsuitable for study participation;
  16. Any disease or condition that, in the investigator's judgment, may interfere with study participation or evaluation.
05

Study design

Phase
Not applicable
Primary purpose
Treatment
Allocation
Randomized
Intervention model
Parallel assignment
Masking
Single (Outcomes assessor)
Enrollment
80 participants (estimated)

Study arms

  • Experimental
    diverse carbohydrate diet

    Carbohydrate, protein, and fat provide 45-55%, 15-20%, and 25-35% of total dietary energy, respectively. Of the staple carbohydrate sources, 45-50% are derived from refined grains and 45-50% from whole grains and legumes. Total daily energy intake is divided among three meals, with breakfast providing 25-30% of total energy, lunch 30-40%, and dinner 30-35%.

    Other: diverse carbohydrate diet

  • Other
    moderate carbohydrate diet

    Carbohydrate, protein, and fat provide 45-55%, 15-20%, and 25-35% of total dietary energy, respectively. Of the staple carbohydrate sources, 90-95% are derived from refined grains. Total daily energy intake is divided among three meals, with breakfast providing 25-30% of total energy, lunch 30-40%, and dinner 30-35%.

    Other: moderate carbohydrate diet

Interventions

  • Otherdiverse carbohydrate diet

    Carbohydrate, protein, and fat provide 45-55%, 15-20%, and 25-35% of total dietary energy, respectively. Of the staple carbohydrate sources, 45-50% are derived from refined grains and 45-50% from whole grains and legumes. Total daily energy intake is divided among three meals, with breakfast providing 25-30% of total energy, lunch 30-40%, and dinner 30-35%.

  • Othermoderate carbohydrate diet

    Carbohydrate, protein, and fat provide 45-55%, 15-20%, and 25-35% of total dietary energy, respectively. Of the staple carbohydrate sources, 90-95% are derived from refined grains. Total daily energy intake is divided among three meals, with breakfast providing 25-30% of total energy, lunch 30-40%, and dinner 30-35%.

06

What researchers measure

Primary outcomes

  1. Time in range (TIR)

    TIR is defined as the percentage of time that glucose levels are between 3.9 and 10.0 mmol/L, as measured by continuous glucose monitoring (CGM). TIR at the end of the 2-week dietary intervention will be compared between the two groups.

    Time frame: 4 weeks (2 weeks after randomization)

Secondary outcomes

  1. Time above range(TAR)

    TAR is defined as the percentage of time that glucose levels are above 10.0 mmol/L, as measured using continuous glucose monitoring (CGM). TAR at the end of the 2-week dietary intervention will be compared between the two groups.

    Time frame: 4 weeks (2 weeks after randomization)

  2. Time below range(TBR)

    TBR is defined as the percentage of time that glucose levels are below 3.9 mmol/L, as measured using continuous glucose monitoring (CGM). TBR at the end of the 2-week dietary intervention will be compared between the two groups.

    Time frame: 4 weeks (2 weeks after randomization)

  3. Mean glucose (MG)

    Mean glucose is defined as the arithmetic mean of all valid glucose values recorded during the 2-week continuous glucose monitoring (CGM) period. Mean glucose at the end of the 2-week dietary intervention will be compared between the two groups.

    Time frame: 4 weeks (2 weeks after randomization)

  4. Standard deviation of glucose (SD)

    SD is a continuous glucose monitoring (CGM)-derived measure of glycemic variability. SD at the end of the 2-week dietary intervention will be compared between the two groups.

    Time frame: 4 weeks (2 weeks after randomization)

  5. Glucose coefficient of variation (CV)

    CV is a continuous glucose monitoring (CGM)-derived measure of glycemic variability. CV at the end of the 2-week dietary intervention will be compared between the two groups.

    Time frame: 4 weeks (2 weeks after randomization)

  6. Mean amplitude of glycemic excursions (MAGE)

    MAGE is a continuous glucose monitoring (CGM)-derived measure of glycemic variability. MAGE at the end of the 2-week dietary intervention will be compared between the two groups.

    Time frame: 4 weeks (2 weeks after randomization)

  7. Largest amplitude of glycemic excursions (LAGE)

    LAGE is a continuous glucose monitoring (CGM)-derived measure of glycemic variability. LAGE at the end of the 2-week dietary intervention will be compared between the two groups.

    Time frame: 4 weeks (2 weeks after randomization)

  8. Glycated albumin (GA)

    Glycated albumin will be measured at the end of the 2-week dietary intervention and compared between the two groups.

    Time frame: 4 weeks (2 weeks after randomization)

  9. Glycated hemoglobin A1c (HbA1c)

    HbA1c will be measured at the end of the follow-up period and compared between the two groups.

    Time frame: 16 weeks (14 weeks after randomization)

  10. C-peptide area under the curve (AUC C-peptide)

    C-peptide area under the curve will be assessed during a 3-hour mixed-meal tolerance test and calculated using the trapezoidal rule. The assessment will be performed in participants with fasting C-peptide \>80 pmol/L.

    Time frame: 16 weeks (14 weeks after randomization)

  11. Glucagon area under the curve (AUC glucagon)

    Glucagon area under the curve will be assessed during a 3-hour mixed-meal tolerance test and calculated using the trapezoidal rule. The assessment will be performed in participants with fasting C-peptide \>80 pmol/L.

    Time frame: 16 weeks (14 weeks after randomization)

  12. Fasting blood glucose (FBG)

    Fasting blood glucose will be measured at the end of the dietary intervention and at the end of the follow-up period and compared between the two groups.

    Time frame: 4 weeks (2 weeks after randomization) and 16 weeks (14 weeks after randomization)

  13. Total cholesterol (TC)

    Total cholesterol will be measured at the end of the dietary intervention and at the end of the follow-up period and compared between the two groups.

    Time frame: 4 weeks (2 weeks after randomization) and 16 weeks (14 weeks after randomization)

  14. Triglycerides (TG)

    Triglycerides will be measured at the end of the dietary intervention and at the end of the follow-up period and compared between the two groups.

    Time frame: 4 weeks (2 weeks after randomization) and 16 weeks (14 weeks after randomization)

  15. Low-density lipoprotein cholesterol (LDL-C)

    LDL-C will be measured at the end of the dietary intervention and at the end of the follow-up period and compared between the two groups.

    Time frame: 4 weeks (2 weeks after randomization) and 16 weeks (14 weeks after randomization)

  16. High-density lipoprotein cholesterol (HDL-C)

    HDL-C will be measured at the end of the dietary intervention and at the end of the follow-up period and compared between the two groups.

    Time frame: 4 weeks (2 weeks after randomization) and 16 weeks (14 weeks after randomization)

  17. 1,5-Anhydroglucitol (1,5-AG)

    1,5-AG will be measured at the end of the dietary intervention and at the end of the follow-up period and compared between the two groups.

    Time frame: 4 weeks (2 weeks after randomization) and 16 weeks (14 weeks after randomization)

  18. Total daily insulin dose

    Total daily insulin dose, expressed as IU/kg/day, will be assessed at the end of the dietary intervention and at the end of the follow-up period.

    Time frame: 4 weeks (2 weeks after randomization) and 16 weeks (14 weeks after randomization)

  19. Basal insulin dose

    Basal insulin dose, expressed as IU/kg/day, will be assessed at the end of the dietary intervention and at the end of the follow-up period.

    Time frame: 4 weeks (2 weeks after randomization) and 16 weeks (14 weeks after randomization)

  20. Prandial insulin dose

    Prandial insulin dose, expressed as IU/kg/day, will be assessed at the end of the dietary intervention and at the end of the follow-up period.

    Time frame: 4 weeks (2 weeks after randomization) and 16 weeks (14 weeks after randomization)

  21. Body weight

    Body weight will be measured at the end of the dietary intervention and at the end of the follow-up period.

    Time frame: 4 weeks (2 weeks after randomization) and 16 weeks (14 weeks after randomization)

  22. Waist circumference

    Waist circumference will be measured at the end of the dietary intervention and at the end of the follow-up period.

    Time frame: 4 weeks (2 weeks after randomization) and 16 weeks (14 weeks after randomization)

  23. Hip circumference

    Hip circumference will be measured at the end of the dietary intervention and at the end of the follow-up period.

    Time frame: 4 weeks (2 weeks after randomization) and 16 weeks (14 weeks after randomization)

  24. Waist-to-hip ratio (WHR)

    Waist-to-hip ratio will be calculated from waist and hip circumference measurements at the end of the dietary intervention and at the end of the follow-up period.

    Time frame: 4 weeks (2 weeks after randomization) and 16 weeks (14 weeks after randomization)

  25. Body composition

    Body composition will be assessed using a body composition analyzer at the end of the dietary intervention and at the end of the follow-up period.

    Time frame: 4 weeks (2 weeks after randomization) and 16 weeks (14 weeks after randomization)

  26. Hypoglycemic events

    Hypoglycemic events will be assessed by the number of events per participant, the proportion of participants experiencing at least one hypoglycemic event, and the incidence rate of hypoglycemic events.

    Time frame: From randomization to the end of follow-up at 16 weeks

  27. Diabetic ketoacidosis (DKA)

    The number and proportion of participants experiencing diabetic ketoacidosis will be assessed and compared between the two groups.

    Time frame: From randomization to the end of follow-up at 16 weeks

Other outcomes

  1. Gut microbiota profile

    Gut microbiota profiles will be assessed from fecal samples at the end of the dietary intervention and at the end of the follow-up period to evaluate differences between the two groups.

    Time frame: 4 weeks (2 weeks after randomization) and 16 weeks (14 weeks after randomization)

  2. Metabolomic profile

    Metabolomic profiles will be assessed at the end of the dietary intervention and at the end of the follow-up period to evaluate differences between the two groups.

    Time frame: 4 weeks (2 weeks after randomization) and 16 weeks (14 weeks after randomization)

  3. T-cell subset proportions

    The proportions of T-cell subsets will be assessed by flow cytometry at the end of the dietary intervention and at the end of the follow-up period.

    Time frame: 4 weeks (2 weeks after randomization) and 16 weeks (14 weeks after randomization)

07

Study locations

1 of 1 sites recruiting
  • First Affiliated Hospital, Nanjing Medical University
    Nanjing, Jiangsu 210029, China
    Recruiting
08

References and documents

Publications

  • Bell E, Binkowski S, Sanderson E, Keating B, Smith G, Harray AJ, Davis EA. Substantial Intra-Individual Variability in Post-Prandial Time to Peak in Controlled and Free-Living Conditions in Children with Type 1 Diabetes. Nutrients. 2021 Nov 19;13(11):4154. doi: 10.3390/nu13114154. PubMed 34836409 ↗
  • Clark AL, Yan Z, Chen SX, Shi V, Kulkarni DH, Diwan A, Remedi MS. High-fat diet prevents the development of autoimmune diabetes in NOD mice. Diabetes Obes Metab. 2021 Nov;23(11):2455-2465. doi: 10.1111/dom.14486. Epub 2021 Aug 2. PubMed 34212475 ↗
  • Lejk A, Chrzanowski J, Cieslak A, Fendler W, Mysliwiec M. Effect of Nutritional Habits on the Glycemic Response to Different Carbohydrate Diet in Children with Type 1 Diabetes Mellitus. Nutrients. 2021 Oct 27;13(11):3815. doi: 10.3390/nu13113815. PubMed 34836071 ↗
  • Thewjitcharoen Y, Wanothayaroj E, Jaita H, Nakasatien S, Butadej S, Khurana I, Maxwell S, El-Osta A, Chatchomchuan W, Krittiyawong S, Himathongkam T. Prolonged Honeymoon Period in a Thai Patient with Adult-Onset Type 1 Diabetes Mellitus. Case Rep Endocrinol. 2021 Sep 1;2021:3511281. doi: 10.1155/2021/3511281. eCollection 2021. PubMed 34513096 ↗
  • Seidelmann SB, Claggett B, Cheng S, Henglin M, Shah A, Steffen LM, Folsom AR, Rimm EB, Willett WC, Solomon SD. Dietary carbohydrate intake and mortality: a prospective cohort study and meta-analysis. Lancet Public Health. 2018 Sep;3(9):e419-e428. doi: 10.1016/S2468-2667(18)30135-X. Epub 2018 Aug 17. PubMed 30122560 ↗
  • Jaacks LM, Crandell J, Mendez MA, Lamichhane AP, Liu W, Ji L, Du S, Rosamond W, Popkin BM, Mayer-Davis EJ. Dietary patterns associated with HbA1c and LDL cholesterol among individuals with type 1 diabetes in China. J Diabetes Complications. 2015 Apr;29(3):343-9. doi: 10.1016/j.jdiacomp.2014.12.014. Epub 2014 Dec 31. PubMed 25630525 ↗
  • Hollowell JG, Staehling NW, Flanders WD, Hannon WH, Gunter EW, Spencer CA, Braverman LE. Serum TSH, T(4), and thyroid antibodies in the United States population (1988 to 1994): National Health and Nutrition Examination Survey (NHANES III). J Clin Endocrinol Metab. 2002 Feb;87(2):489-99. doi: 10.1210/jcem.87.2.8182. PubMed 11836274 ↗
  • Zhai X, Zhang L, Chen L, Lian X, Liu C, Shi B, Shi L, Tong N, Wang S, Weng J, Zhao J, Teng X, Yu X, Lai Y, Wang W, Li C, Mao J, Li Y, Fan C, Li L, Shan Z, Teng W. An Age-Specific Serum Thyrotropin Reference Range for the Diagnosis of Thyroid Diseases in Older Adults: A Cross-Sectional Survey in China. Thyroid. 2018 Dec;28(12):1571-1579. doi: 10.1089/thy.2017.0715. Epub 2018 Nov 27. PubMed 30351201 ↗
  • Barouti AA, Bjorklund A, Catrina SB, Brismar K, Rajamand Ekberg N. Effect of Isocaloric Meals on Postprandial Glycemic and Metabolic Markers in Type 1 Diabetes-A Randomized Crossover Trial. Nutrients. 2023 Jul 10;15(14):3092. doi: 10.3390/nu15143092. PubMed 37513510 ↗
  • Wong K, Raffray M, Roy-Fleming A, Blunden S, Brazeau AS. Ketogenic Diet as a Normal Way of Eating in Adults With Type 1 and Type 2 Diabetes: A Qualitative Study. Can J Diabetes. 2021 Mar;45(2):137-143.e1. doi: 10.1016/j.jcjd.2020.06.016. Epub 2020 Jun 27. PubMed 33039330 ↗
  • Buehler LA, Noe D, Knapp S, Isaacs D, Pantalone KM. Ketogenic diets in the management of type 1 diabetes: Safe or safety concern? Cleve Clin J Med. 2021 Oct 1;88(10):547-555. doi: 10.3949/ccjm.88a.20121. PubMed 34598919 ↗
  • 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. PubMed 24170749 ↗
  • Leow ZZX, Guelfi KJ, Davis EA, Jones TW, Fournier PA. The glycaemic benefits of a very-low-carbohydrate ketogenic diet in adults with Type 1 diabetes mellitus may be opposed by increased hypoglycaemia risk and dyslipidaemia. Diabet Med. 2018 May 8. doi: 10.1111/dme.13663. Online ahead of print. PubMed 29737587 ↗
  • Vetrani C, Calabrese I, Cavagnuolo L, Pacella D, Napolano E, Di Rienzo S, Riccardi G, Rivellese AA, Annuzzi G, Bozzetto L. Dietary determinants of postprandial blood glucose control in adults with type 1 diabetes on a hybrid closed-loop system. Diabetologia. 2022 Jan;65(1):79-87. doi: 10.1007/s00125-021-05587-0. Epub 2021 Oct 23. PubMed 34689215 ↗
  • Berry SE, Valdes AM, Drew DA, Asnicar F, Mazidi M, Wolf J, Capdevila J, Hadjigeorgiou G, Davies R, Al Khatib H, Bonnett C, Ganesh S, Bakker E, Hart D, Mangino M, Merino J, Linenberg I, Wyatt P, Ordovas JM, Gardner CD, Delahanty LM, Chan AT, Segata N, Franks PW, Spector TD. Human postprandial responses to food and potential for precision nutrition. Nat Med. 2020 Jun;26(6):964-973. doi: 10.1038/s41591-020-0934-0. Epub 2020 Jun 11. PubMed 32528151 ↗
  • Kanikarla-Marie P, Jain SK. Hyperketonemia and ketosis increase the risk of complications in type 1 diabetes. Free Radic Biol Med. 2016 Jun;95:268-77. doi: 10.1016/j.freeradbiomed.2016.03.020. Epub 2016 Mar 29. PubMed 27036365 ↗
  • Bolla AM, Caretto A, Laurenzi A, Scavini M, Piemonti L. Low-Carb and Ketogenic Diets in Type 1 and Type 2 Diabetes. Nutrients. 2019 Apr 26;11(5):962. doi: 10.3390/nu11050962. PubMed 31035514 ↗
  • Dabek A, Wojtala M, Pirola L, Balcerczyk A. Modulation of Cellular Biochemistry, Epigenetics and Metabolomics by Ketone Bodies. Implications of the Ketogenic Diet in the Physiology of the Organism and Pathological States. Nutrients. 2020 Mar 17;12(3):788. doi: 10.3390/nu12030788. PubMed 32192146 ↗
  • Zinn C, Lenferna De La Motte KA, Rush A, Johnson R. Assessing the Nutrient Status of Low Carbohydrate, High-Fat (LCHF) Meal Plans in Children: A Hypothetical Case Study Design. Nutrients. 2022 Apr 12;14(8):1598. doi: 10.3390/nu14081598. PubMed 35458160 ↗
  • Pasmans K, Meex RCR, van Loon LJC, Blaak EE. Nutritional strategies to attenuate postprandial glycemic response. Obes Rev. 2022 Sep;23(9):e13486. doi: 10.1111/obr.13486. Epub 2022 Jun 10. PubMed 35686720 ↗
  • Saslow LR, Mason AE, Kim S, Goldman V, Ploutz-Snyder R, Bayandorian H, Daubenmier J, Hecht FM, Moskowitz JT. An Online Intervention Comparing a Very Low-Carbohydrate Ketogenic Diet and Lifestyle Recommendations Versus a Plate Method Diet in Overweight Individuals With Type 2 Diabetes: A Randomized Controlled Trial. J Med Internet Res. 2017 Feb 13;19(2):e36. doi: 10.2196/jmir.5806. PubMed 28193599 ↗
  • Rydin AA, Spiegel G, Frohnert BI, Kaess A, Oswald L, Owen D, Simmons KM. Medical management of children with type 1 diabetes on low-carbohydrate or ketogenic diets. Pediatr Diabetes. 2021 May;22(3):448-454. doi: 10.1111/pedi.13179. Epub 2021 Feb 16. PubMed 33470021 ↗
  • Turton JL, Raab R, Rooney KB. Low-carbohydrate diets for type 1 diabetes mellitus: A systematic review. PLoS One. 2018 Mar 29;13(3):e0194987. doi: 10.1371/journal.pone.0194987. eCollection 2018. PubMed 29596460 ↗
09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Sep 10, 2026, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT06273631
Lead sponsor
Yang Tao
Responsible party
Yang Tao (professor, Chief physician, Nanjing Medical University) — Sponsor-investigator
First posted
Feb 22, 2024
Start date
Aug 1, 2024
Primary completion
Dec 31, 2027 (estimated)
Completion
Dec 31, 2027 (estimated)
Last update
Sep 10, 2026

Study contacts

Tao Yang, MD/PhD
Contact
yangt@njmu.edu.cn
86-25-83718836 ext. 6466
Tao Yang, MD/PhD
principal investigator · First Affiliated Hospital, Nanjing Medical University, China

Oversight

Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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