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DM: Carbohydrate Management Strategies (2014)

Citation:

Bergenstal RM, Johnson M, Powers MA, Wynn A, Vlajnic A, Hollander P, Rendell M. Adjust to target in type 2 diabetes: Comparison of a simple algorithm with carbohydrate counting for adjustment of mealtime insulin glulisine. Diabetes Care. 2008;31:1305-1310.

PubMed ID: 18364392
 
Study Design:
Randomized Controlled Trial
Class:
A - Click here for explanation of classification scheme.
Quality Rating:
Neutral NEUTRAL: See Quality Criteria Checklist below.
Research Purpose:

To compare an insulin-to-carbohydrate ratio with a simple algorithm for adjusting the dose of prandial insulin glulisine.

Inclusion Criteria:
  • Provided written informed consent
  • Between the ages of 18 and 70 years
  • Had type 2 diabetes for six or more months
  • Had A1c of 7% to 10% at screening
  • Had taken two or more insulin injections per day with or without metformin for three or more months before study entry.
Exclusion Criteria:
  • Treatment with oral anti-diabetic drugs (except metformin) within three months before study entry
  • Planning pregnancy or lactation
  • Serum creatinine of 1.5mg or more per dL in men taking metformin, 1.4mg or more per dL in women taking metformin and more than 3.0mg per dL for any subject
  • Clinically significant renal disease or hepatic disease
  • NYHA Class III to IV heart failure
  • Any disease or condition that might interfere with study completion.
Description of Study Protocol:

Design

Multi-center, controlled, open, randomized, parallel-group study.

Blinding Used

Implied with measurements.

Intervention

  • Two different algorithms to adjust mealtime glulisine insulin:
    • A simple algorithm group was provided set doses of glulisine to take before each meal, which was split to cover three meals:
      • 50% for the largest (most carbohydrate) meal
      • 33% for the middle-sized meal
      • 17% for the smallest meal.
    • The carbohydrate counting group was provided an insulin-to-carbohydrate ratio to use for each meal and adjusted their glulisine dose based on the amount of carbohydrate consumed. The initial insulin glargine dose was calculated as 50% of the pre-randomization total daily insulin dose. Subsequent dosing was titrated weekly according to the mean of the last three days of fasting self-monitored blood glucose (SMBG). A dose increase could be split into two or more increments over the week.
  • All subjects followed an algorithm to adjust background glargine insulin
  • Study staff taught the carbohydrate counting (carb count) group about carbohydrate counting and how to use an insulin-to-carbohydrate ratio
  • Weekly contact was established by a phone call to review diaries and adjust insulin doses.
Statistical Analysis
  • A mixed model repeated measures analysis including covariates baseline A1c, number of daily injections before the study (two or more than two), metformin use at randomization, injection method and study site provided adjusted estimates and changes from baseline by visit for weeks two, six, 12, 18 and 24 for:
    • A1c
    • FPG
    • Seven-point blood glucose profile
    • Basal and bolus insulin doses
    • Lipids
    • Weights
    • BMI.
  • Percentages of patients achieving HbA1c of less than 7.0% and less than 6.5% were analyzed by logistic regression that included:
    • Treatment arm
    • Baseline A1c
    • Other randomization factors.
  • A Poisson regression model incorporated over-dispersion and was used to analyze the rate of hypoglycemia
  • A logistic regression was used to analyze the incidence of hypoglycemia.
Data Collection Summary:

Timing of Measurements

Study visits occurred at the baseline screening, and at weeks two, six, 12, 18 and 24.

Dependent Variables

  • All patients recorded:
    • SMBG before meals and at bedtime
    • Insulin doses
    • Food and estimated carbohydrate intake per meal (carb count group)
    • Information related to hypoglycemia
    • Activity level
    • A seven-point blood glucose profile at weeks zero, 12, 18 and 24.
  • Evaluations at study visits included:
    • Physical examinations
    • Vital signs
    • Electrocardiogram
    • A1c
    • Hematology and chemistry laboratory tests
    • Diary review.
  • Adverse events, hypoglycemic episodes and concomitant medications were recorded.
Independent Variables
  • Two different algorithms to adjust mealtime glulisine insulin:
    • Simple algorithm group was provided set doses of glulisine to take before each meal, which was split to cover three meals:
      • 50% for the largest (most carbohydrate) meal
      • 33% for the middle-sized meal
      • 17% for the smallest meal.
    • The carbohydrate counting group was provided an insulin-to-carbohydrate ratio to use for each meal; their glulisine dose was adjusted based on the amount of carbohydrate consumed.
    • The initial insulin glargine dose was calculated as 50% of the pre-randomization total daily insulin dose. Subsequent dosing was titrated weekly according to the mean of the last three days of fasting self-monitored blood glucose (SMBG). A dose increase could be split into two or more increments over the week.
  • All subjects followed an algorithm to adjust background glargine insulin
  • Study staff taught the carbohydrate counting (carb count) group about carbohydrate counting and how to use an insulin-to-carbohydrate ratio
  • Weekly contact was established by a phone call to review diaries and adjust insulin doses.
Description of Actual Data Sample:
  • Initial N: A total of 281 patients randomized
  • Attrition (final N): A total of 273 patients were included in the intent-to-treat analysis (136 simple algorithm group, 137 carbohydrate counting group). A total of 12 subjects in the simple algorithm and 28 in the carb count group discontinued treatment.
  • Age: Mean age in the simple algorithm group was 55.1±8.8 years and  55±9.5 years in the carb count group
  • Ethnicity:
    • The simple algorithm group (81.6% white, 11% black, 1.5% Asian, 5.9% other)
    • Carb count group (79.6% white, 10.9% black, 0.7% multi-racial, 8.8% other).
  • Other relevant demographics: A1c percentage in the simple group was 8.1±0.9, in the carb count group was 8.3±0.9
  • Anthropometrics: Mean BMI (kg/m2) in the simple group 37.7±8.1 and in the carb count group was 35.6±7.2. There were significant differences between groups in BMI at baseline (P=0.0416).
  • Location: Multiple locations.
Summary of Results:

Key Findings

  • A1c levels at week 24 were 6.70% (simple algorithm) and 6.54% (carb count)
  • Respective mean A1c changes from baseline to 24 weeks were -1.46% and -1.59% (P=0.24)
  • A1c of less than 7.0% was achieved by 73.2% (simple algorithm) and 69.2% (carb count) (P=0.70) of subjects; respective values for A1c less than 6.5% were 44.3% and 49.5% (P=0.28)
  • The total daily dose of insulin was lower and there was a trend toward less weight gain in the carb count group patients
  • Severe hypoglycemia rates were low and equal in the two groups
  • Both arms had significantly improved fasting plasma glucose from baseline (112.0mg per dL in the simple algorithm group, 101.8mg per dL in the carbohydrate counting group; P<0.0001 for both)
  • At 24 weeks, the adjusted mean insulin glulisine (P=0.0011), insulin glargine (P<0.0001) and total insulin doses (P=0.0002) were significantly higher in simple algorithm than in carbohydrate counting patients (108.7, 102.5 and 207.4 units vs. 88.9, 86.4 and 175.5 units, respectively); the total insulin dose was 1.9 units per kg (simple algorithm group) and 1.7 units per kg (carbohydrate counting group)
  • At 24 weeks, there were no significant differences in total cholesterol, HDL-cholesterol or LDL-cholesterol within or between groups; however, there was a significant reduction in triglycerides in the carbohydrate counting group (144.0mg to 133.0mg per dL) but not in the simple algorithm group (164.7mg to 153.4mg per dL) group (13.19mg per dL, P=0.008 and 8.19mg per dL, P=0.170, respectively)
  • At 24 weeks, both groups gained weight, 3.6kg (3.4%) in the simple algorithm group and 2.4kg (2.3%) in the carbohydrate counting group (P=0.06 between groups), resulting in a small but significant increase in BMI of 1.28kg/m2 in the simple algorithm group and 0.83kg/m2 in the carbohydrate counting group (both P<0.0001 vs. baseline; P=0.037, between groups).
Author Conclusion:

Weekly basal-bolus insulin adjustments based on pre-meal and bedtime glucose patterns resulted in significant reductions in A1c. Having two effective approaches to delivering and adjusting rapid-acting mealtime insulin may increase physicians' and patients' willingness to advance therapy to a basal-bolus insulin regimen.

Funding Source:
Not-for-profit
International Diabetes Center at Park Nicollet Minneapolis, MN
Reviewer Comments:

There were significant differences between groups in BMI at baseline (P=0.0416).

Quality Criteria Checklist: Primary Research
Relevance Questions
  1. Would implementing the studied intervention or procedure (if found successful) result in improved outcomes for the patients/clients/population group? (Not Applicable for some epidemiological studies) Yes
  2. Did the authors study an outcome (dependent variable) or topic that the patients/clients/population group would care about? Yes
  3. Is the focus of the intervention or procedure (independent variable) or topic of study a common issue of concern to dieteticspractice? Yes
  4. Is the intervention or procedure feasible? (NA for some epidemiological studies) Yes
 
Validity Questions
1. Was the research question clearly stated? Yes
  1.1. Was (were) the specific intervention(s) or procedure(s) [independent variable(s)] identified? Yes
  1.2. Was (were) the outcome(s) [dependent variable(s)] clearly indicated? Yes
  1.3. Were the target population and setting specified? Yes
2. Was the selection of study subjects/patients free from bias? Yes
  2.1. Were inclusion/exclusion criteria specified (e.g., risk, point in disease progression, diagnostic or prognosis criteria), and with sufficient detail and without omitting criteria critical to the study? Yes
  2.2. Were criteria applied equally to all study groups? Yes
  2.3. Were health, demographics, and other characteristics of subjects described? Yes
  2.4. Were the subjects/patients a representative sample of the relevant population? Yes
3. Were study groups comparable? ???
  3.1. Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT) Yes
  3.2. Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline? ???
  3.3. Were concurrent controls or comparisons used? (Concurrent preferred over historical control or comparison groups.) Yes
  3.4. If cohort study or cross-sectional study, were groups comparable on important confounding factors and/or were preexisting differences accounted for by using appropriate adjustments in statistical analysis? N/A
  3.5. If case control study, were potential confounding factors comparable for cases and controls? (If case series or trial with subjects serving as own control, this criterion is not applicable.) N/A
  3.6. If diagnostic test, was there an independent blind comparison with an appropriate reference standard (e.g., "gold standard")? N/A
4. Was method of handling withdrawals described? Yes
  4.1. Were follow-up methods described and the same for all groups? Yes
  4.2. Was the number, characteristics of withdrawals (i.e., dropouts, lost to follow up, attrition rate) and/or response rate (cross-sectional studies) described for each group? (Follow up goal for a strong study is 80%.) Yes
  4.3. Were all enrolled subjects/patients (in the original sample) accounted for? Yes
  4.4. Were reasons for withdrawals similar across groups? Yes
  4.5. If diagnostic test, was decision to perform reference test not dependent on results of test under study? N/A
5. Was blinding used to prevent introduction of bias? Yes
  5.1. In intervention study, were subjects, clinicians/practitioners, and investigators blinded to treatment group, as appropriate? No
  5.2. Were data collectors blinded for outcomes assessment? (If outcome is measured using an objective test, such as a lab value, this criterion is assumed to be met.) Yes
  5.3. In cohort study or cross-sectional study, were measurements of outcomes and risk factors blinded? N/A
  5.4. In case control study, was case definition explicit and case ascertainment not influenced by exposure status? N/A
  5.5. In diagnostic study, were test results blinded to patient history and other test results? N/A
6. Were intervention/therapeutic regimens/exposure factor or procedure and any comparison(s) described in detail? Were interveningfactors described? Yes
  6.1. In RCT or other intervention trial, were protocols described for all regimens studied? Yes
  6.2. In observational study, were interventions, study settings, and clinicians/provider described? N/A
  6.3. Was the intensity and duration of the intervention or exposure factor sufficient to produce a meaningful effect? Yes
  6.4. Was the amount of exposure and, if relevant, subject/patient compliance measured? Yes
  6.5. Were co-interventions (e.g., ancillary treatments, other therapies) described? Yes
  6.6. Were extra or unplanned treatments described? Yes
  6.7. Was the information for 6.4, 6.5, and 6.6 assessed the same way for all groups? Yes
  6.8. In diagnostic study, were details of test administration and replication sufficient? N/A
7. Were outcomes clearly defined and the measurements valid and reliable? Yes
  7.1. Were primary and secondary endpoints described and relevant to the question? Yes
  7.2. Were nutrition measures appropriate to question and outcomes of concern? Yes
  7.3. Was the period of follow-up long enough for important outcome(s) to occur? Yes
  7.4. Were the observations and measurements based on standard, valid, and reliable data collection instruments/tests/procedures? Yes
  7.5. Was the measurement of effect at an appropriate level of precision? Yes
  7.6. Were other factors accounted for (measured) that could affect outcomes? Yes
  7.7. Were the measurements conducted consistently across groups? Yes
8. Was the statistical analysis appropriate for the study design and type of outcome indicators? Yes
  8.1. Were statistical analyses adequately described and the results reported appropriately? Yes
  8.2. Were correct statistical tests used and assumptions of test not violated? Yes
  8.3. Were statistics reported with levels of significance and/or confidence intervals? Yes
  8.4. Was "intent to treat" analysis of outcomes done (and as appropriate, was there an analysis of outcomes for those maximally exposed or a dose-response analysis)? Yes
  8.5. Were adequate adjustments made for effects of confounding factors that might have affected the outcomes (e.g., multivariate analyses)? Yes
  8.6. Was clinical significance as well as statistical significance reported? Yes
  8.7. If negative findings, was a power calculation reported to address type 2 error? N/A
9. Are conclusions supported by results with biases and limitations taken into consideration? Yes
  9.1. Is there a discussion of findings? Yes
  9.2. Are biases and study limitations identified and discussed? Yes
10. Is bias due to study's funding or sponsorship unlikely? Yes
  10.1. Were sources of funding and investigators' affiliations described? Yes
  10.2. Was the study free from apparent conflict of interest? Yes