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Improvement of both fasting and postprandial glycemic control by the two-step addition of miglitol and mitiglinide to basal insulin therapy: a pilot study.

ABSTRACT: BACKGROUND:Combination therapy consisting of basal insulin and oral hypoglycemic agents (OHAs) is effective for the treatment of type 2 diabetes (T2DM) that cannot be adequately controlled using OHAs alone. Though basal insulin with metformin or sulfonylurea is an effective therapy, it cannot reduce postprandial glycemia without the risk of hypoglycemia. We examined a two-step regimen consisting of the addition of postprandial hypoglycemic agents (an alpha-glucosidase inhibitor and a glinide) in patients whose T2DM was poorly controlled using basal insulin therapy. METHODS:Inpatients between the ages of 30-79 years who had T2DM and an HbA1c level of more than 7.0% were recruited. The patients were treated with once-daily insulin glargine with or without metformin, depending on the patient's age and renal function. Insulin glargine was titrated to achieve a target fasting glucose level of 70-130 mg/dL as a first step (STEP0). If the 2-hour postprandial glucose (PBG) level was higher than the target of 180 mg/dL, miglitol treatment (150 mg/day) was initiated, with dose adjustments (75-225 mg) allowed depending on abdominal symptoms and the PBG (STEP1). If the PBG of the patients remained higher than the target after 3 days of treatment, mitiglinide (30 mg/day, titrated up to 60 mg) was added (STEP2). We then evaluated the proportion of patients who achieved the target PBG before and after the two-step regimen. Continuous Glucose Monitoring (CGM) was performed throughout the two-step protocol in most of the patients. RESULTS:Of the 16 patients who were recruited (median age, 67.0 [58.0-71.0] years; body mass index, 25.0 [22.0-27.9] kg/m(2); HbA1c level at admission, 9.1% [8.35-10.4%]), 1 patient (6.25%) achieved the target PBG at STEP 0 and 14 patients (87.5%) had achieved the target PBG at the end of the treatment protocol (P?=?0.002). CGM showed a significant decrease in the glucose level at each step of the protocol. The standard deviations in the CGM glucose levels for 24 hours, MAGE, and M-value also improved. CONCLUSIONS:The two-step addition of postprandial hypoglycemic agents to basal insulin therapy is potentially effective and safe for decreasing both the fasting and postprandial glucose levels.

SUBMITTER: Ihana N

PROVIDER: S-EPMC4025538 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Improvement of both fasting and postprandial glycemic control by the two-step addition of miglitol and mitiglinide to basal insulin therapy: a pilot study.

Ihana Noriko N Tsujimoto Tetsuro T Yamamoto-Honda Ritsuko R Kishimoto Miyako M Kajio Hiroshi H Noto Hiroshi H Kakei Masafumi M Noda Mitsuhiko M

Diabetology & metabolic syndrome 20140331

<h4>Background</h4>Combination therapy consisting of basal insulin and oral hypoglycemic agents (OHAs) is effective for the treatment of type 2 diabetes (T2DM) that cannot be adequately controlled using OHAs alone. Though basal insulin with metformin or sulfonylurea is an effective therapy, it cannot reduce postprandial glycemia without the risk of hypoglycemia. We examined a two-step regimen consisting of the addition of postprandial hypoglycemic agents (an alpha-glucosidase inhibitor and a gli ...[more]

PMID: 24684803

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Project description:IntroductionFew prospective clinical trials have investigated the role of fasting blood glucose (FBG) and/or postprandial glucose (PPG) in assessing overall glycemic control by using different insulin regimens. In the present post hoc analysis, we assessed the contribution of FBG and/or PPG in overall glycemic control in Chinese patients under insulin treatment.MethodsCLASSIFY is a phase IV, randomized, open-label, 26-week, parallel-arm, treat-to-target, multinational, controlled study in patients with type 2 diabetes mellitus to compare the efficacy and safety of insulin lispro mix 25 (LM25) and insulin lispro mix 50 (LM50) as starter insulins. Insulin was titrated with an aim to target pre-meal blood glucose (BG) levels at > 3.9 and ≤ 6.1 mmol/L before breakfast and dinner. The primary outcome assessed was the change in HbA1c from baseline.ResultsChinese patients contributed 38.7% (N = 156) of the total population. The majority of patients were male (52.6%). The mean (SD) body mass index was 24.54 (3.04) kg/m2 and mean (SD) HbA1c was 8.54 (1.10) % at baseline. At week 26, LM50 showed a significantly greater reduction from baseline in HbA1c (- 2.03% vs - 1.55%, P < 0.001), average daily BG (- 3.21 vs - 2.34 mmol/L, P < 0.001), average post-meal BG (- 3.58 vs - 2.39 mmol/L, P < 0.001), and average prandial BG excursion (- 1.01 vs - 0.22 mmol/L, P = 0.006) than the LM25 group. The reductions in average pre-meal BG (- 2.59 vs - 2.28 mmol/L, P = 0.137) were not significantly different between the groups. The proportion of patients achieving HbA1c targets (< 7% or ≤ 6.5%) without nocturnal hypoglycemia or weight gain was greater (P < 0.05) with LM50 compared with LM25.ConclusionLM50 achieved better overall glycemic control than LM25 as a starter insulin in Chinese patients, which may be due to greater improvement in PPG levels.Trial registrationClinicaltrials.gov identification number: NCT01773473.FundingEli Lilly and Company, Shanghai, China.

Project description:Background: The potential confounding effect of different amounts and proportions of macronutrients across eating patterns on meal or dietary glycemic index (GI) and glycemic load (GL) value determinations has remained partially unaddressed.Objective: The study aimed to determine the effects of different amounts of macronutrients and fiber on measured meal GI and GL values.Design: Four studies were conducted during which participants [n = 20-22; women: 50%; age: 50-80 y; body mass index (in kg/m2): 25-30)] received food challenges containing different amounts of the variable nutrient in a random order. Added to the standard 50 g available carbohydrate from white bread was 12.5, 25, or 50 g carbohydrate; 12.5, 25, or 50 g protein; and 5.6, 11.1, or 22.2 g fat from rice cereal, tuna, and unsalted butter, respectively, and 4.8 or 9.6 g fiber from oat cereal. Arterialized venous blood was sampled for 2 h, and measured meal GI and GL and insulin index (II) values were calculated by using the incremental area under the curve (AUCi) method.Results: Adding carbohydrate to the standard white-bread challenge increased glucose AUCi (P < 0.0001), measured meal GI (P = 0.0066), and mean GL (P < 0.0001). Adding protein (50 g only) decreased glucose AUCi (P = 0.0026), measured meal GI (P = 0.0139), and meal GL (P = 0.0140). Adding fat or fiber had no significant effect on these variables. Adding carbohydrate (50 g), protein (50 g), and fat (11.1 g) increased the insulin AUCi or II; fiber had no effect.Conclusions: These data indicate that uncertainty in the determination of meal GI and GL values is introduced when carbohydrate-containing foods are consumed concurrently with protein (equal amount of carbohydrate challenge) but not with carbohydrate-, fat-, or fiber-containing foods. Future studies are needed to evaluate whether this uncertainty also influences the prediction of average dietary GI and GL values for eating patterns. This trial was registered at clinicaltrials.gov as NCT01023646.

Project description:Background: The potential impact of prior meal composition on the postprandial glycemic response and glycemic index (GI) and glycemic load (GL) value determinations remains unclear.Objective: We determined the effect of meals that varied in macronutrient composition on the glycemic response and determination of GI and GL values of a subsequent standard test food.Design: Twenty healthy participants underwent 6 test sessions within 12 wk. The subjects received each of 3 isocaloric breakfast meals (i.e., high carbohydrate, high fat, or high protein) on separate days in a random order, which was followed by a standard set of challenges (i.e., white bread and a glucose drink) that were tested on separate days in a random order 4 h thereafter. Each challenge provided 50 g available carbohydrate. Arterialized venous blood was sampled throughout the 2-h postchallenge period. GI, GL, and insulin index (II) values were calculated with the use of the incremental area under the curve (AUCi) method, and serum lipids were determined with the use of standard assays.Results: The consumption of the high-protein breakfast before the white-bread challenge attenuated the rise in the postprandial serum glucose response (P < 0.0001) and resulted in lower glucose AUCi (P < 0.0001), GI (P = 0.0096), and GL (P = 0.0101) values than did the high-carbohydrate and high-fat breakfasts. The high-protein breakfast resulted in a lower insulin AUCi (P = 0.0146) for white bread than did the high-fat breakfast and a lower II value (P = 0.0285) than did the high-carbohydrate breakfast. The 3 breakfasts resulted in similar serum lipid responses to the white-bread challenge.Conclusions: These data indicate that the macronutrient composition of the prior meal influences the glycemic response and the determination of GI and GL values for white bread. Future studies are needed to determine whether the background food macronutrient composition influences mean dietary GI and GL values that are calculated for eating patterns, which may alter the interpretation of the associations between these values and chronic disease risk. This trial was registered at clinicaltrials.gov as NCT01023646.

Dataset Information

Improvement of both fasting and postprandial glycemic control by the two-step addition of miglitol and mitiglinide to basal insulin therapy: a pilot study.

Publications

Improvement of both fasting and postprandial glycemic control by the two-step addition of miglitol and mitiglinide to basal insulin therapy: a pilot study.

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