Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT04655131 |
| Other study ID # |
01-18-18 |
| Secondary ID |
|
| Status |
Completed |
| Phase |
N/A
|
| First received |
|
| Last updated |
|
| Start date |
June 18, 2018 |
| Est. completion date |
November 25, 2018 |
Study information
| Verified date |
December 2020 |
| Source |
University Hospitals Cleveland Medical Center |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Interventional
|
Clinical Trial Summary
In type 1 Diabetes Mellitus, patients receive insulin doses if they consume specific amounts
of carbohydrates. Currently, insulin is not being administered for consumption of protein
although studies in adults show that consuming about 75 grams of protein causes elevation in
post prandial glucose levels and might need insulin coverage. We are proposing that this
amount is different for kids and it might vary based on weight, age, pubertal stage, HbA1C or
other factors.
This has not been studied in children before, and it will provide information about the
amount of protein in the diet that can cause elevation in post prandial glucose.
Description:
In target glycemic control in children with type 1 diabetes (T1D) continues to be a challenge
despite advances in methods of insulin delivery and medical knowledge in this area. One of
the major aspects is controlling postprandial glycemia (PPG). The relationship between
dietary intake of carbohydrates and PPG is well established, and the use of insulin coverage
for carbohydrate intake is standard of care. Insulin dose for carbohydrate coverage increases
with body weight and progression through puberty. Multiple researchers have attempted to
study the effect of dietary intake of protein and fat on PPG as well, but this relationship
is not well established in the pediatric age group and there are not clear guidelines for
patients on when and how to give insulin for protein intake.
Meals with high protein content have been shown to cause higher glucose excursions in
patients with T1D, and lower glycemic response in healthy individuals which suggests that
physiologic response to protein intake involves higher insulin secretion. This has also been
demonstrated by Sun et al, where they showed an increase in insulinemic index in healthy
individuals when consuming chicken with rice compared to rice alone.
The effect of dietary protein in individuals with T1D has been studied in mixed meals several
times. Smart et al demonstrated that the greatest glucose excursions after high protein low
fat meal occurred most significantly form min 150 to 300 after the meal, when insulin is
given to cover carbohydrates only. In 2013, Borie-Swinburne et al measured interstitial
glucose levels by CGM in 28 c-peptide negative T1D patients, on two consecutive nights, with
and without addition of 21.5 grams of protein to dinner (40 g vs 61.5 g). They concluded that
no additional insulin is needed to cover for the added protein. Neu et al studied 15
adolescents with T1D on two consecutive nights. They used CGM monitoring for 12 hours, and
they compared the area under the curve (AUC) between regular meals and fat/ protein rich
meal. They found a significant difference and they recommended additional insulin for fat
/protein rich meals.
Investigating the effect of protein-only intake is also an area of research focus. Paterson
et al studied 27 patients with TID , aged 7-40 yrs, where they were given 6 test meals of
varying amounts (0g, 12.5g, 25g, 50g, 75g and 100g) of pure protein without giving insulin.
Postprandial glycemia was found to be significantly higher only for 75 and 100 grams of
protein compared to the lower quantities. Glucose levels were slower to rise when compared to
consumption of 20 grams of carbohydrates. Paterson et al also conducted another study with
slightly different design: 27 participants with T1D [aged 10-40 years, HbA1c ≤ 64 mmol/mol
(8%), BMI ≤ 91st percentile] received a 30-g carbohydrate (negligible fat) test drink with a
variable amount of protein daily over 5 days in randomized order. Protein (whey isolate 0
g/kg carbohydrate, 0 g/kg lipid) was added in amounts of 0 (control), 12.5, 25, 50 and 75 g.
A standardized dose of insulin was given for the carbohydrate. PPG was assessed by 5 hours of
continuous glucose monitoring. Increasing protein quantity in a low-fat meal containing
consistent amounts of carbohydrate decreases glucose excursions in the early (0-60-min)
postprandial period and then increases in the later postprandial period in a dose-dependent
manner. In summary, Paterson et al concluded that there was a threshold for dietary protein
intake (75 grams), and only protein intake above this threshold regardless of body weight
would result in post prandial hyperglycemia. However, these studies included a wide range of
ages and did not adjust for body weight in their analysis.
B. Innovation The purpose of this study is to explore the role of weight in the relationship
between protein intake and post prandial glucose (PPG) levels. The study design (36 children
each receiving 6 increasing nominal doses of protein) allows for the relationship to be
studied both across patients of varying weights within each nominal dose, and across patients
(whose weights remain the same) across the increasing doses.
Our aims:
Aim 1: To describe the relationship of weight (in kg), and mg of protein per kg body weight,
to PPG, graphically and statistically, at each nominal dose. The heaviest children will
receive the lowest mg/kg amount of protein at each nominal dose, so these relationships with
PPG will be inverse. Additionally, children with different weights and receiving different
nominal doses, may be receiving the same mg/kg protein. Observing all nominal doses together
will allow us to determine whether the relationship, if any, is linear, demonstrates a
threshold, or exhibits a doseresponse curve, as examples.
Aim 2: To describe graphically and statistically the relationship of dose of protein to PPG
by patient across increasing doses. Since the weight remains constant (or approximately
constant) within a patient, adjustment by weight would yield the same results. The
expectation is that these results will confirm those from Aim 1.
Aim 3: To construct a multivariate mixed model where any observed relationships can be
controlled for other demographic and clinical characteristics possibly associated with blood
glucose levels. The type of model will depend on the results of Aims 1 and 2.
