IRIS II study: the IRIS II score--assessment of a new clinical algorithm for the classification of insulin resistance in patients with Type 2 diabetes

An Okinawan-based Nordic diet improves anthropometry, metabolic control, and health-related quality of life in Scandinavian patients with type 2 diabetes: a pilot trial

BACKGROUND

Our hypothesis was that a modified diet would improve blood glucose control with beneficial impact on weight management and overall health in established diabetes.

OBJECTIVE

This prospective interventional study investigated the clinical effect of an Okinawan-based Nordic diet on anthropometry, metabolic control, and health-related quality of life (HRQoL) in Scandinavian type 2 diabetes patients.

DESIGN

Food was prepared and delivered to 30 type 2 diabetes patients. Clinical information along with data on HRQoL, blood samples, and urine samples were collected during 12 weeks of diet interventions, with follow-up 16 weeks after diet completion.

RESULTS

After 12 weeks of dietary intervention, a reduction in body weight (7%) (p<0.001), body mass index (p<0.001), and waist circumference (7.0 cm) (p<0.001) was seen. Improved levels of proinsulin (p=0.005), insulin (p=0.011), and fasting plasma glucose (p<0.001) were found already after 2 weeks; these improved levels remained after 12 weeks when lowered levels of C-peptide (p=0.015), triglycerides (p=0.009), total cholesterol (p=0.001), and low-density lipoprotein-cholesterol (p=0.041) were also observed. Insulin resistance homeostasis model assessment for insulin resistance was lowered throughout the study, with a 20% reduction in hemoglobin A1c levels (p<0.001) at week 12, despite reduced anti-diabetes treatment. Lowered systolic blood pressure (9.6 mmHg) (p<0.001), diastolic blood pressure (2.7 mmHg) (p<0.001), and heart and respiratory rates (p<0.001) were accompanied by decreased cortisol levels (p=0.015) and improvement in HRQoL. At follow-up, increased levels of high-density lipoprotein-cholesterol were found (p=0.003).

CONCLUSION

This interventional study demonstrates a considerable improvement of anthropometric and metabolic parameters and HRQoL in Scandinavian type 2 diabetes patients when introducing a modified Okinawan-based Nordic diet, independently of exercise or other interventions. Through these dietary changes, anti-diabetes treatment could be decreased or cancelled.

A Diagnostic Score for Insulin Resistance in Nondiabetic Patients with Ischemic Stroke or Transient Ischemic Attack

GOAL

We sought to develop an instrument to screen for insulin resistance in nondiabetic patients with recent ischemic stroke or transient ischemic attack (TIA).

MATERIALS AND METHODS

Subjects were 7262 nondiabetic patients aged greater than or equal to 40 years with ischemic strokes or TIA within the past 6 months. Features were analyzed in bivariate analysis for association with insulin resistance, measured by the homeostasis model assessment of insulin resistance (HOMA-IR). Features significantly associated with HOMA-IR (P < .05) were entered into multivariable analysis. The magnitudes of regression coefficients from the multivariable model were used to assign point values for 2 diagnostic scoring instruments: a basic instrument that did not incorporate laboratory test values and an enhanced instrument that did. The performance of the instruments was tested using receiver operating characteristic (ROC) analysis.

FINDINGS

In the basic model, 5 features were retained in the multivariable regression analysis: male gender, abdominal obesity, body mass index (BMI), elevated waist-to-hip ratio, and systolic blood pressure. In the enhanced model, 4 features were retained in the multivariable regression analysis: BMI, abdominal obesity, fasting glucose greater than or equal to 100 mg/dL, and triglyceride/high-density lipoprotein ratio. In the basic model, the area under the ROC curve (aROC) was .73 in the validation cohort. In the enhanced model, the aROC was .78 in the validation cohort.

CONCLUSIONS

Our 2 scoring systems performed well in identifying stroke patients with insulin resistance, but they are probably not sufficiently accurate for high-stake clinical decisions. We suggest strategies for improving the accuracy of future instruments.

Association of Serum Magnesium Deficiency with Insulin Resistance in Type 2 Diabetes Mellitus

Background:

Insulin resistance (IR) is the key pathophysiological defect that leads to the development of type 2 diabetes mellitus. The purpose of this study was to estimate serum magnesium level and insulin sensitivity indices among type 2 diabetes mellitus patients and to see an association between them.

Methods:

This study was carried out among 38 type 2 diabetic patients and forty age and sex matched controls. Serum fasting glucose, magnesium, insulin, urea, and creatinine levels were estimated. Insulin sensitivity indices, homeostasis model assessment for insulin resistance (HOMA-IR) and quantitative insulin sensitivity check index (QUICKI) levels were calculated as per formulae.

Results:

A highly significant low serum magnesium level was found in diabetic subjects as compared to the controls. Statistically significant high HOMA levels (>2.6) and low QUICKI levels (<0.33) were found among the case group. An inverse, statistically significant correlation was found between serum magnesium and fasting insulin level. A highly statistically significant inverse correlation was found between serum magnesium and HOMA level, and a positive correlation was found between serum magnesium and QUICKI level, that is, serum magnesium level decreases with increase in IR. A strong association was also found between fasting serum insulin level and insulin sensitivity indices.

Conclusion:

This study showed a lower serum magnesium level in diabetic patients compared to control. A strong association was also found between serum magnesium level and insulin sensitivity indices. For proper management of type 2 diabetes, it may, therefore, be necessary to treat hypomagnesemia in these patients.

Indian Diabetes Risk Score helps to distinguish type 2 from non-type 2 diabetes mellitus (GDRC-3)

AIM

The aim of this study was to investigate whether the Indian Diabetes Risk Score (IDRS) could assist in classifying type 2 diabetes mellitus (T2DM) and non-T2DM among patients attending clinics in India.

METHODS

Patient records from 2006 through 2009 were taken from the clinical database of a tertiary care diabetes hospital in Chennai, Southern India. A total of 8747 patients with diabetes, diagnosed by a physician either as type 1 diabetes mellitus (T1DM), T2DM, or other types were included for analysis. The IDRS, based on age, abdominal obesity, family history of diabetes, and physical activity, was calculated for each patient at first visit to our clinic. Receiver operating characteristic (ROC) curves were generated to obtain optimal IDRS cut points for predicting T2DM and non-T2DM.

RESULTS

Of the 8747 patient records analyzed, 204 (2.3%) were classified as non-T2DM and 8543 (97.7%) as T2DM. In ROC analysis, an IDRS ≥60 [area under the curve (AUC), 0.894; sensitivity, 83.8%; specificity, 81.0%] was predictive of T2DM, while an IDRS <60 (AUC, 0.882; sensitivity, 79.9%; specificity, 83.8%) was predictive of non-T2DM.

CONCLUSIONS

The IDRS, a simple, cost-effective risk score, can assist in classifying T2DM versus non-T2DM among clinic patients in India.

Successful switch from insulin therapy to treatment with pioglitazone in type 2 diabetes patients with residual beta-cell function: results from the PioSwitch study

AIM

Insulin treatment is considered to be the final option for patients with progressive type 2 diabetes. This study investigated, whether reconverting type 2 patients from insulin treatment to oral treatment using pioglitazone is possible without deterioration of blood glucose control.

METHODS

The PioSwitch study was a prospective, open label, proof of concept study. Thiazolidinedione-naïve patients with residual beta-cell function were switched from an existing insulin therapy to treatment with pioglitazone and glimepiride for 6 months. Efficacy was assessed by laboratory parameters and scores for evaluation of metabolic control, beta-cell function, insulin resistance and cardiovascular risk.

RESULTS

In total, 98 patients [66 men, 32 women, age (mean +/- s.d.): 59 +/- 9 years; disease duration: 5.6 +/- 3.6 years; Hemoglobin A1c (HbA1c): 6.9 +/- 0.8%; body mass index (BMI): 33.9 +/- 5.2 kg/m(2), initial daily insulin therapy dose: 0.36 +/- 0.3 U/kg body weight] out of 117 screened patients were treated. During the observation period, 23 patients were prematurely terminated because of an increase in HbA1c from baseline > 0.5% or other reasons. In 75 patients (76%), no deterioration of glucose metabolism occurred and additional improvements were seen in the majority of the observation parameters [baseline vs. endpoint; HbA1c: 6.79 +/- 0.74%/6.66 +/- 0.69% (p < 0.05), glucose: 6.4 +/- 1.5/5.2 +/- 1.4 mmol/l (p < 0.001), adiponectin: 7 +/- 3 mg/l/17 +/- 8 mg/l (p < 0.001), C-peptide: 987 +/- 493/1756 +/- 789 (p < 0.001), sensitivity index derived from the intravenous glucose tolerance test (SI(ivGTT)): 1.21 +/- 0.85/1.49 +/- 0.95 (p < 0.05), hsCRP: 3.3 +/- 2.4/2.6 +/- 2.4 mg/l (p < 0.01), macrophage chemo-attractant protein 1 (MCP1): 487 +/- 246/382 +/- 295 ng/l (p < 0.05)]. BMI increased from 33.8 +/- 5.1 to 34.4 +/- 5.3 kg/m(2) (p < 0.001).

CONCLUSIONS

The switch from insulin therapy resulting in a moderately HbA1c level, to oral treatment with pioglitazone was successful in a majority of patients with sufficient residual beta-cell function. It allows a simple and less expensive therapy with a better cardiovascular risk marker profile.

Pioglitazone improves metabolic markers in patients with type 2 diabetes independently from physical activities: results from the IRIS III study

AIM

Pioglitazone is an established peroxisome proliferator-activated receptor gamma agonist for the treatment of insulin resistance in patients with type 2 diabetes mellitus. This analysis of the observational IRIS III study was performed to evaluate the effects of pioglitazone treatment in relation to the degree of physical exercise activities in a large patient population under daily life conditions.

METHODS

A total of 1298 patients out of 2092 enrolled into the IRIS III study who had provided information about their exercise level could be included in the final analysis (622 female, 676 male; age: 63.1 +/- 10.4 years, diabetes duration: 6.6 +/- 5.0 years, mean +/- SD). All patients were glitazone naïve prior to study entry. They received pioglitazone in addition to their previous oral antidiabetic treatment. The patients were stratified according to their physical activity level (never, sometimes, and regularly). Data were evaluated at baseline and after 20 +/- 2 weeks of treatment. Observation parameters were fasting blood glucose, lipids, and blood pressure. Hemoglobin A1c (HbA1c) was determined in a central laboratory, and insulin sensitivity was assessed by the IRIS II score.

RESULTS

Glycemic control, blood pressure, and the lipid profile improved independently from the degree of physical activity (e.g., no exercise vs frequent exercise: DeltaHbA1c: -0.89 +/- 1.2% vs -0.72 +/- 1.1%, not significant). A positive impact of exercise on insulin resistance could be observed at baseline, which, however, was further decreased by pioglitazone treatment [IRIS II score (baseline/end point): no exercise vs frequent exercise: 74.0 +/- 15.9/62.5 +/- 20.2 vs 66.7 +/- 19.0/58.0 +/- 21.8, p < 0.001/not significant].

CONCLUSIONS

These observational results, obtained from a nonselected patient population under daily routine conditions, confirm that the benefits of pioglitazone treatment on glycemic control, lipid metabolism, and blood pressure are independent from physical activity. Exercise has a positive influence on insulin sensitivity, but pioglitazone shows additional favorable effects and is, therefore, recommended for use independently from the activity level of the patients.

High-sensitivity C-reactive protein as cardiovascular risk marker in patients with diabetes mellitus

C-reactive protein (CRP) is a liver-derived pattern recognition molecule that is increased in inflammatory states. It rapidly increases within hours after tissue injury, and it is suggested that it is part of the innate immune system and contributes to host defense. Since cardiovascular disease is at least in part an inflammatory process, CRP has been investigated in the context of arteriosclerosis and subsequent vascular disorders. Based on multiple epidemiological and intervention studies, minor CRP elevation [high-sensitivity CRP (hsCRP)] has been shown to be associated with future major cardiovascular risk (hsCRP:<1 mg/L=low risk; 1-3 mg/L=intermediate risk; 3-10 mg/L=high risk; >10 mg/L=unspecific elevation). It is recommended by the American Heart Association that patients at intermediate or high risk of coronary heart disease may benefit from measurement of hsCRP with regard to their individual risk prediction. Elevation of hsCRP is associated with increased risk of type 2 diabetes development in patients with all levels of metabolic syndrome. In type 1 and type 2 diabetes mellitus, hemoglobin A1c significantly correlates with hsCRP levels and future cardiovascular risk. Also, hsCRP levels increase with the stage of beta-cell dysfunction and insulin resistance. Non-diabetes drugs that have been shown to reduce hsCRP concentrations include aspirin, statins, cyclooxygenase-2 inhibitors, and fibrates. Recent intervention studies have also demonstrated the distinct efficacy of different anti-diabetes treatments on a variety of cardiovascular risk markers. Intensive insulin therapy may reduce inflammation, but this effect may be influenced by the degree of weight gain. Treatment with peroxisome proliferator-activated receptor gamma has lead to substantial reduction of hsCRP and other cardiovascular risk markers in several comparator studies. Since this effect was shown to be independent of the degree of glycemic improvement, it can be regarded as a classspecific effect. Whether these findings translate into a reduction of overall cardiovascular mortality will soon be shown by the currently running thiazolidinedione outcome studies. Positive results in these trials will further strengthen the value and acceptance of hsCRP, which is recommended as a predictive laboratory marker for cardiovascular disease risk also in patients with diabetes mellitus.

IRIS II study: intact proinsulin is confirmed as a highly specific indicator for insulin resistance in a large cross-sectional study design

BACKGROUND

The cross-sectional IRIS-II study tried to assess the prevalence of insulin resistance and macrovascular disease in orally treated patients with Type 2 diabetes.

METHODS

In total, 4,270 patients were enrolled into the study (2,146 male, 2,124 female; mean +/- SD age 63.9 +/- 11.1 years; body mass index 30.1 +/- 5.5 kg/m2; duration of disease 5.4 +/- 5.6 years; hemoglobin A1c 6.8 +/- 1.3%). The study consisted of a single morning visit with completion of a standardized questionnaire and collection of a fasting blood sample.

RESULTS

The mean intact proinsulin value was 11.4 +/- 12.4 pmol/L (normal range < 10 pmol/L). Homeostasis model assessment resulted in 1,147 insulin-sensitive patients (26.9%) and 3,123 patients (73.1%) with insulin resistance. Of the latter patients 1,465 (34.3% of all patients) had also elevated intact proinsulin values, while 1,658 (38.8%) had no proinsulin elevation. In contrast, 1,042 (24.4%) of the insulin-sensitive patients had normal intact proinsulin, and only 105 (2.4%) had elevated intact proinsulin concentrations (chi2 test P < 0.0001). A specificity of 93.2% (sensitivity 46.9%) was calculated for elevated intact proinsulin as an indirect marker for insulin resistance. Of the 1,451 patients treated with sulfonylurea 52% had elevated intact proinsulin values and increased prevalence of cardiovascular complications (odds ratio 1.45).

CONCLUSION

Type 2 patients with elevated fasting intact proinsulin values can be regarded as being insulin resistant. The results confirm that fasting intact proinsulin is a suitable measure for beta-cell dysfunction and insulin resistance in type 2 diabetes and may be used to support therapeutic decisions.

IRIS II Study: Sensitivity and specificity of intact proinsulin, adiponectin, and the proinsulin/adiponectin ratio as markers for insulin resistance

OBJECTIVE

This study was performed to compare the specificity and sensitivity of intact proinsulin, adiponectin, and their ratio (proinsulin/adiponectin) in the prediction of insulin resistance as assessed by the homeostasis model assessment (HOMA) score (> or =2 = resistant).

RESEARCH DESIGN AND METHODS

Using a cross-sectional approach, 500 orally treated patients with type 2 diabetes (272 women, 238 men; mean +/- SD age, 64.8 +/- 11.6 years; hemoglobin A1c, 7.0 +/- 1.5%; disease duration, 5.8 +/- 6.1 years) were investigated. Various cutoffs for body mass index-adjusted adiponectin and proinsulin/adiponectin were compared with the established cutoff value of 10 pmol/L for fasting proinsulin.

RESULTS

Fasting proinsulin correlated more closely with the HOMA score (r = 0.560, P < 0.001) than fasting adiponectin (r = -0.204, P < 0.001) or proinsulin/adiponectin (r = 0.355, P < 0.001). For proinsulin, specificity and sensitivity for insulin resistance in correlation to the HOMA score results were 96% and 70%, respectively. At a comparable specificity level to proinsulin, adiponectin did not reach a comparable sensitivity (14%), while the proinsulin/adiponectin ratio almost reached the same sensitivity (65%). Overall, patients with elevated proinsulin had a higher prevalence of micro- and macrovascular disease [odds ratio 1.47 (adiponectin, 1.08; proinsulin/ adiponectin, 1.48) and 1.34 (adiponectin, 1.32; proinsulin/adiponectin, 1.27), respectively].

CONCLUSIONS

Elevation of fasting intact proinsulin seems to be the more specific marker for insulin resistance and increased cardiovascular risk than suppression of fasting adiponectin. Formation of the ratio does not lead to a further increase in the predictive value.