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Indices Of Insulin Sensitivity And Secretion From A Standard Liquid Meal Test In Subjects With Type 2 Diabetes, Impaired Or Normal Fasting Glucose

Indices Of Insulin Sensitivity And Secretion From A Standard Liquid Meal Test In Subjects With Type 2 Diabetes, Impaired Or Normal Fasting Glucose

Indices of insulin sensitivity and secretion from a standard liquid meal test in subjects with type 2 diabetes, impaired or normal fasting glucose Maki et al; licensee BioMed Central Ltd.2009 To provide an initial evaluation of insulin sensitivity and secretion indices derived from a standard liquid meal tolerance test protocol in subjects with normal (NFG), impaired fasting glucose (IFG) or type 2 diabetes mellitus. Areas under the curve (AUC) for glucose, insulin and C-peptide from pre-meal to 120 min after consumption of a liquid meal were calculated, as were homeostasis model assessments of insulin resistance (HOMA2-IR) and the Matsuda index of insulin sensitivity. Subjects with NFG (n = 19), IFG (n = 19), and diabetes (n = 35) had mean SEM HOMA2-IR values of 1.0 0.1, 1.6 0.2 and 2.5 0.3 and Matsuda insulin sensitivity index values of 15.6 2.0, 8.8 1.2 and 6.0 0.6, respectively. The log-transformed values for these variables were highly correlated overall and within each fasting glucose category (r = -0.91 to -0.94, all p < 0.001). Values for the product of the insulin/glucose AUC ratio and the Matsuda index, an indicator of the ability of the pancreas to match insulin secretion to the degree of insulin resistance, were 995.6 80.7 (NFG), 684.0 57.3 (IFG) and 188.3 16.1 (diabetes) and discriminated significantly between fasting glucose categories (p < 0.001 for each comparison). These results provide initial evidence to support the usefulness of a standard liquid meal tolerance test for evaluation of insulin secretion and sensitivity in clinical and population studies. Insulin SensitivityOral Glucose Tolerance TestImpaired Fasting GlucoseInsulin Sensitivity IndexMixed Meal Both impaired insulin sensitivity and pancreatic beta-cell dysfunction play central roles in t Continue reading >>

Metabolic Phenotyping Guidelines: Assessing Glucose Homeostasis In Rodent Models

Metabolic Phenotyping Guidelines: Assessing Glucose Homeostasis In Rodent Models

Introduction The incidence of diabetes mellitus, particularly obesity-related type 2 diabetes, is increasing at an alarming rate in the developed world, and this epidemic is driving numerous research programmes into the causes of, and new treatment regimens for, this metabolic disorder. The complex hormonal control of nutrient homeostasis involves numerous tissues and organs, including liver, skeletal muscle, adipose, endocrine pancreas and CNS. While in vitro studies can provide cellular mechanistic insights, it is inevitable that in vivo models are needed to study the integrated control systems. Many animal models for the study of diabetes already exist, with various mechanisms for inducing either type 1 or type 2 diabetes (King 2012). Furthermore, genetically modified mouse models in which genes are up- or down-regulated either globally or in a tissue-specific manner are increasingly used to assess the physiological role of a potential target in glucose homeostasis and the development of diabetes. Consequently, techniques for accurately assessing glucose homeostasis in vivo in rodents are essential tools in current diabetes research. Mice and rats are by far the two most commonly used species for experimental studies of glucose homeostasis, and both models have specific advantages and disadvantages. The primary advantage of using a rat model is a technical consideration in that the larger size of the rat facilitates complex surgical procedures such as catheterisation, and the larger blood volume allows the sampling of more frequent and/or larger blood samples to enable detailed and simultaneous monitoring of multiple plasma hormone levels. Surgical techniques developed in the rat have been successfully miniaturised for use in mouse models, although they are technical Continue reading >>

Area Under The Curve (pharmacokinetics)

Area Under The Curve (pharmacokinetics)

In the field of pharmacokinetics , the area under the curve (AUC) is the definite integral in a plot of drug concentration in blood plasma vs. time. In practice, the drug concentration is measured at certain discrete points in time and the trapezoidal rule is used to estimate AUC. Interpretation and usefulness of AUC values Edit The AUC (from zero to infinity) represents the total drug exposure over time. Assuming linear pharmacodynamics with elimination rate constant K, one can show that AUC is proportional to the total amount of drug absorbed by the body. The proportionality constant is 1/K. This is useful when trying to determine whether two formulations of the same dose (for example a capsule and a tablet ) release the same dose of drug to the body. Another use is in the therapeutic drug monitoring of drugs with a narrow therapeutic index. For example, gentamicin is an antibiotic that can be nephrotoxic (kidney damaging) and ototoxic (hearing damaging); measurement of gentamicin through concentrations in a patient's plasma and calculation of the AUC is used to guide the dosage of this drug. AUC becomes useful for knowing the average concentration over a time interval, AUC/t. Also, AUC is referenced when talking about elimination . The amount eliminated by the body (mass) = clearance (volume/time) * AUC (mass*time/volume). In pharmacokinetics , bioavailability generally refers to the fraction of drug absorbed systemically, and is thus available to produce a biological effect. This is often measured by quantifying the "AUC". In order to determine the respective AUCs, the serum concentration vs. time plots are typically gathered using C-14 labeled drugs and AMS (accelerated mass spectroscopy). [1] Bioavailability can be measured in terms of "absolute bioavailablity" o Continue reading >>

Evaluation Of Fasting State-/oral Glucose Tolerance Test-derived Measures Of Insulin Release For The Detection Of Genetically Impaired -cell Function.

Evaluation Of Fasting State-/oral Glucose Tolerance Test-derived Measures Of Insulin Release For The Detection Of Genetically Impaired -cell Function.

Division of Endocrinology, Diabetology, Angiology, Nephrology, and Clinical Chemistry, Department of Internal Medicine, University Hospital Tbingen and Eberhard Karls University Tbingen, Tbingen, Germany. To date, fasting state- and different oral glucose tolerance test (OGTT)-derived measures are used to estimate insulin release with reasonable effort in large human cohorts required, e.g., for genetic studies. Here, we evaluated twelve common (or recently introduced) fasting state-/OGTT-derived indices for their suitability to detect genetically determined -cell dysfunction. A cohort of 1364 White European individuals at increased risk for type 2 diabetes was characterized by OGTT with glucose, insulin, and C-peptide measurements and genotyped for single nucleotide polymorphisms (SNPs) known to affect glucose- and incretin-stimulated insulin secretion. One fasting state- and eleven OGTT-derived indices were calculated and statistically evaluated. After adjustment for confounding variables, all tested SNPs were significantly associated with at least two insulin secretion measures (p0.05). The indices were ranked according to their associations' statistical power, and the ranks an index obtained for its associations with all the tested SNPs (or a subset) were summed up resulting in a final ranking. This approach revealed area under the curve (AUC)(Insulin(0-30))/AUC(Glucose(0-30)) as the best-ranked index to detect SNP-dependent differences in insulin release. Moreover, AUC(Insulin(0-30))/AUC(Glucose(0-30)), corrected insulin response (CIR), AUC(C-Peptide(0-30))/AUC(Glucose(0-30)), AUC(C-Peptide(0-120))/AUC(Glucose(0-120)), two different formulas for the incremental insulin response from 0-30 min, i.e., the insulinogenic indices (IGI)(2) and IGI(1), and insulin 30 min w Continue reading >>

(pdf) The Use Of Areas Under Curves In Diabetes Research

(pdf) The Use Of Areas Under Curves In Diabetes Research

Bariatric surgery is associated with significant and sustained weight loss and improved metabolic outcomes. It is unclear if weight loss alone is the main mechanism of improved metabolic health. The purpose of this trial was to compare indices of appetite regulation, insulin sensitivity and energy intake (EI) between participants achieving 10 kg of weight loss via RouxenY Gastric Bypass (RYGB) or dietary restriction (DIET); intake of a very low calorie liquid diet (800 kcal/d; 40% protein, 40% fat, 20% carbohydrate that matched the postRYGB dietary protocol). Adults qualifying for bariatric surgery were studied before and after 10 kg of weight loss (RYGB [n = 6]) or DIET [n = 17]). Appetite (hunger, satiety, and prospective food consumption [PFC]), appetiterelated hormones, and metabolites (ghrelin, PYY, GLP1, insulin, glucose, free fatty acids [FFA], and triglycerides [TG]) were measured in the fasting state and every 30 min for 180 min following breakfast. Participants were provided lunch to evaluate acute ad libitum EI, which was similarly reduced in both groups from pre to post weight loss. Fasting ghrelin was reduced to a greater extent following RYGB compared to DIET (P = 0.04). Area under the curve (AUC) for ghrelin (P = 0.01), hunger (P < 0.01) and PFC (P < 0.01) increased after DIET compared to RYGB, following 10 kg weight loss. Satiety AUC increased after RYGB and decreased after DIET (P < 0.01). Glucose and insulin (fasting and AUC) decreased in both groups. FFA increased in both groups, with a greater increase in AUC seen after RYGB versus DIET (P = 0.02). In summary, appetiterelated indices were altered in a manner that, if maintained, may promote a sustained reduction in energy intake with RYGB compared to DIET. Future work with a larger sample size and l Continue reading >>

A Comparison Of Methods For Analyzing Glucose And Insulin Areas Under The Curve Following Nine Months Of Exercise In Overweight Adults

A Comparison Of Methods For Analyzing Glucose And Insulin Areas Under The Curve Following Nine Months Of Exercise In Overweight Adults

A comparison of methods for analyzing glucose and insulin areas under the curve following nine months of exercise in overweight adults International Journal of Obesity volume 26, pages 8789 (2002) OBJECTIVE: We examined three methods for calculating the area under the curve (AUC) following an oral glucose tolerance test (OGTT) in overweight adults prior to and after 9 months of exercise. METHOD: Subjects (n=27) were randomly assigned to a control (CON, n=9) or intervention (INT, n=18) group. INT performed supervised exercise 5 days per week, 45 min per session, at 65% of heart rate reserve. OGTTs were administered pre- and post-training. Blood was collected during a 75 g OGTT and analyzed for glucose (GLU) and insulin (INS) concentrations. AUCs were calculated using the incremental, positive incremental, and total AUC methods and the difference scores for pre- and post-training were determined. RESULTS: No differences were observed among the methods for glucose AUC for either group. Significant differences were observed for INT insulin AUC with total AUC (15253291 U/1/180 min) significantly greater than incremental AUC (11123229 U/1/180 min) or positive incremental AUC (10853195 U/I/180 min). Total insulin AUC was significantly reduced following training for INT, while incremental and positive incremental insulin AUCs showed no change. CONCLUSION: These data suggest that the method of used to calculate AUC may affect the interpretation of whether or not an intervention was effective. Recently, Allison et al 1 identified several concerns surrounding the calculations of areas under the curve (AUC) when performing an oral glucose tolerance test (OGTT). In one method the baseline measures are subtracted from all subsequent readings before the AUC is calculated and is refer Continue reading >>

Auc: Area Under The Curve? Waaa?

Auc: Area Under The Curve? Waaa?

Looking at Carelink Pro, my data for the last three months, I see two puzzling stats: I was told by my Medtronic Rep that it's Area Under the Curve, and Less is Good. Any statistics or math majors out there - can you tell me? I tried google and got even more confused. Did I mention I failed Calculus in College? Twice. D.D. Family T1 for 72 years, here to help There is not enough info here for me to comment Drew. Can you give me a website, or something? I have not used carelink so I will need some background first. I used to teach calculus and statistics in college. Lol! I hope you were not one of my students. Type 1 for 72 years. Using the MM 630g pump, and Dexcom G5. A1c=6.1 Washington State, Pacific Northwest of United States Looking at Carelink Pro, my data for the last three months, I see two puzzling stats: I was told by my Medtronic Rep that it's Area Under the Curve, and Less is Good. The picture below shows a hypothetical plot of blood glucose for ten hours from morning 6:00 am (when the person got up and tested the morning fasting BG) till 4:00 pm, four hours after lunch. The area shaded in yellow above the 7.8 mmol/L (140 mg/dL) line is the area under the BG curve above 7.8 (140). For this hypothetical case, I calculated the area of the first (smaller) shaded area as 0.4 hour-mmol/L (6.6 hour-mg/dL) and the second area as 1.3 (22.7) by approximating the shapes to triangles and using the formula for the area of the triangle which is base x height/2. The total area for these ten hours is 1.7 (29.3). The term 'average area' is not very intuitive - probably they mean area per hour. If this is what they mean, the 'average area' in our hypothetical case is the total area divided by ten, which is 0.17 (2.93). Note that the unit of area in this example is hour-mmol/L Continue reading >>

Consideration Of The Validity Of Glycemic Index Using Blood Glucose And Insulin Levels And Breath Hydrogen Excretion In Healthy Subjects - Sciencedirect

Consideration Of The Validity Of Glycemic Index Using Blood Glucose And Insulin Levels And Breath Hydrogen Excretion In Healthy Subjects - Sciencedirect

Volume 2, Issue 2 , August 2010, Pages 88-94 Consideration of the validity of glycemic index using blood glucose and insulin levels and breath hydrogen excretion in healthy subjects Author links open overlay panel TsuneyukiOku Although glycemic index (GI) is very important in choosing appropriate foods for patients with diabetes mellitus, GI itself does not provide sufficient information for choosing adequate foods. The validity of GI is considered by measurement of blood glucose and insulin levels, and breath hydrogen excretion, testing several cultivars in the same type food. Twelve females, 23.8y participated in this within-subject, repeated-measures study. To clarify variations in GI in inter-cultivars of various foods, we examined four white rice and three potato cultivars and three noodle brands. Starchy-foods with a glucose equivalent of 50g were repeatedly and randomly given to each subject. Blood and end-expiration were collected at selected periods. The significant difference of GI and insulinemic index (II) was not observed among the four white rice cultivars, though II of one cultivar were smaller than those of other three white rice cultivars. GI of three potato cultivars was relatively small, but the range of II was very large among three cultivars. Moreover, GI did not correspond to II among three noodle brands. AUC-3h-glucose and AUC-3h-insulin scores of white rice and noodle were significantly larger than those for 2h. The amount of breath hydrogen excretion showed a negative correlation to GI of tested foods. We should recognize that rare foods in which GI does not correspond to II exist in the cultivar of foods used for diet therapy of diabetes mellitus. We propose the addition of other information such as II and breath hydrogen excretion of selected Continue reading >>

Glucose And Insulin Measurements From The Oral Glucose Tolerance Test And Relationship To Muscle Mass

Glucose And Insulin Measurements From The Oral Glucose Tolerance Test And Relationship To Muscle Mass

Glucose and Insulin Measurements From the Oral Glucose Tolerance Test and Relationship to Muscle Mass Division of Endocrinology and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland Search for other works by this author on: Clinical Research Branch, National Institute on Aging, Baltimore, Maryland Search for other works by this author on: Clinical Research Branch, National Institute on Aging, Baltimore, Maryland Search for other works by this author on: Clinical Research Branch, National Institute on Aging, Baltimore, Maryland Search for other works by this author on: Division of Endocrinology and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland Search for other works by this author on: Clinical Research Branch, National Institute on Aging, Baltimore, Maryland Search for other works by this author on: The Journals of Gerontology: Series A, Volume 67A, Issue 1, 1 January 2012, Pages 7481, Rita R. Kalyani, E. Jeffrey Metter, Ramona Ramachandran, Chee W. Chia, Christopher D. Saudek, Luigi Ferrucci; Glucose and Insulin Measurements From the Oral Glucose Tolerance Test and Relationship to Muscle Mass, The Journals of Gerontology: Series A, Volume 67A, Issue 1, 1 January 2012, Pages 7481, Diabetes is associated with decreased muscle mass. The effect of higher levels of glucose and insulin on muscle mass has not been studied in individuals without diabetes. We sought to determine the relationship of insulin and glucose measurements from the oral glucose tolerance test (OGTT) with muscle mass in persons without diabetes. We analyzed data from 587 participants in the Baltimore Longitudinal Study of Aging (mean age 67.3 years, range 2695 years) without diabetes who underwent a Continue reading >>

Assessment Of Insulin Sensitivity From Measurements In Fasting State And During An Oral Glucose Tolerance Test In Obese Children.

Assessment Of Insulin Sensitivity From Measurements In Fasting State And During An Oral Glucose Tolerance Test In Obese Children.

Assessment of insulin sensitivity from measurements in fasting state and during an oral glucose tolerance test in obese children. Atabek ME, et al. J Pediatr Endocrinol Metab. 2007. Department of Pediatric Endocrinology and Diabetes, Faculty ofMedicine, Selcuk University, Konya, Turkey. [email protected] J Pediatr Endocrinol Metab. 2007 Feb;20(2):187-95. BACKGROUND: Few previous studies have examined the validity of the fasting glucose-to-insulin ratio (FGIR), homeostasis model assessment of insulin resistance (HOMA-IR) and quantitative insulin-sensitivity check index (QUICKI) in pediatric populations. OBJECTIVE: To compare simple indices of insulin resistance calculated from fasting glucose and insulin levels with insulin sensitivity indices (area under the response curve [AUCinsulin], insulin sensitivity index [ISI-compositeL) determined by oral glucose tolerance testing (OGTT) in obese children. METHODS: One hundred and forty-eight obese children and adolescents (86 girls and 62 boys, mean age: 10.86 +/- 3.08 years, mean body mass index (BMI): 27.7 +/- 4.2) participated in the study. OGTT was performed in all participants. After glucose and insulin measurements from OGTT, the children were divided into two groups according to the presence or absence of insulin resistance. Insulin sensitivity indices obtained from the OGTT were compared between the groups. The total plasma glucose response and insulin secretion were evaluated from the AUC estimated by the trapezoid rule. Cut-off points, and sensitivity and specificity calculations were based on insulin resistance with receiver operating characteristic curve (ROC) analysis. RESULTS: The prevalence of insulin resistance, glucose intolerance and dyslipidemia was 37.1%, 24.3% and 54% in obese children, respectively. T Continue reading >>

Post-prandial Triglycerides After Mixed Meal Associate With Insulin Sensitivity In Randomly Selected Participants

Post-prandial Triglycerides After Mixed Meal Associate With Insulin Sensitivity In Randomly Selected Participants

Post-Prandial Triglycerides after Mixed Meal Associate with Insulin Sensitivity in Randomly Selected Participants Postprandial lipids, includin Postprandial lipids, including circulating triglycerides from dietary fat, influence atherosclerosis. Studies have shown significant associations between elevated nonfasting triglycerides and cardiovascular events. We studied associations of post-prandial triglycerides (PPTG) and insulin secretion or sensitivity after a meal tolerance test (MTT) in 200 subjects aged 40-65 years randomly drawn from Hoorn, The Netherlands. Blood was drawn 0, 15, 30, 60, 90, 120, 180, 240, 300, 360 minutes after MTT (3487 kJ, 74 g carbohydrates, 49 g fat, 24 g protein). Subjects were divided into normal (NGT, n=160) or impaired glucose metabolism (IGT-IFG, n=19) or diabetes (n=20). OGTT measures included insulinogenic index, incremental area under the curve (AUC) ratio of insulin/glucose, and modeled parameters (Mari). PPTG rose over time in normal subjects after MTT, peaking at 4 hours and remained elevated at 6 hours. PPTG AUC was highest in IGT-IFG (meanSE: 18.72.4) compared to diabetes (14.51.3, p=0.03) and NGT (11.40.4, p<0.001). Insulin AUC had a similar pattern. Glucose AUC increased from NGT to IGT-IFG to diabetes. PPTG AUC correlated with glucose AUC (rs=0.42), insulin AUC (rs=0.42), waist circumference (rs=0.38) and fasting HDL (rs=-0.52), with strongest associations with insulin AUC in IGT-IFG (rs=0.65). No association was found with insulinogenic index (rs=-0.15), incremental AUC I/G (rs=0.05) or model-based parameters. Association was stronger with OGTT model-based (Mari et al) insulin sensitivity (rs=-0.49), especially in IGT-IFG (rs=-0.63). PPTG after MTT is associated with glucose AUC, insulin AUC, waist circumference, fasting HDL Continue reading >>

Assessing Insulin Sensitivity

Assessing Insulin Sensitivity

References: McAuley KA, Williams SM, Mann JI, Walker RJ, Lewis-Barned NJ, Temple LA, Duncan AW (2001) Diagnosing insulin resistance in the general population. Diabetes Care 24:460-464. Background: The concept of insulin resistance is relatively easy to understand, but determining precisely who is insulin resistant is more complicated. The relationship between glucose and insulin is quite complex and involves the interaction of many metabolic and regulatory factors. Normal insulin sensitivity varies widely and is influenced by age, ethnicity, and obesity. Simply put, not all people with impaired insulin sensitivity are necessarily suffering from a disorder, and pregnancy is a perfect example of this. A World Health Organization consensus group recently concluded that the insulin sensitivity index (SI) of the lowest 25% of a general population can be considered insulin resistant. The European Group for the Study of Insulin Resistance took a more restricted view, defining insulin resistance as the SI of the lowest 10% of a non-obese, nondiabetic, normotensive Caucasian population. Richard Legro and his associates also used the SI of the lowest 10% of an obese, non-PCOS population to define insulin resistance. Ideally, we should be deriving the normal SI range from a population of women who are not obese, have regular menstrual cycles, are not suffering from hirsutism, and have normal circulating androgen levels. Choosing the best assessment technique The hyperinsulinemic-euglycemic clamp technique is the most scientifically sound technique for measuring insulin sensitivity, and it's against this standard that all other tests are usually compared. Because this and similar "clamp" techniques are expensive, time consuming, and labor intensive, they are not very practical in a Continue reading >>

A Comparison Of Methods For Analyzing Glucose And Insulin Areas Under The Curvefollowing Nine Months Of Exercise In Overweight Adults.

A Comparison Of Methods For Analyzing Glucose And Insulin Areas Under The Curvefollowing Nine Months Of Exercise In Overweight Adults.

1. Int J Obes Relat Metab Disord. 2002 Jan;26(1):87-9. A comparison of methods for analyzing glucose and insulin areas under the curvefollowing nine months of exercise in overweight adults. Potteiger JA(1), Jacobsen DJ, Donnelly JE. (1)Department of Health, Sport, and Exercise Sciences, University of Kansas, Lawrence, Kansas 66045, USA. [email protected] OBJECTIVE: We examined three methods for calculating the area under the curve(AUC) following an oral glucose tolerance test (OGTT) in overweight adults prior to and after 9 months of exercise.METHOD: Subjects (n=27) were randomly assigned to a control (CON, n=9) orintervention (INT, n=18) group. INT performed supervised exercise 5 days perweek, 45 min per session, at 65% of heart rate reserve. OGTTs were administeredpre- and post-training. Blood was collected during a 75 g OGTT and analyzed forglucose (GLU) and insulin (INS) concentrations. AUCs were calculated using theincremental, positive incremental, and total AUC methods and the differencescores for pre- and post-training were determined.RESULTS: No differences were observed among the methods for glucose AUC foreither group. Significant differences were observed for INT insulin AUC withtotal AUC (1525+/-3291 microU/1/180 min) significantly greater than incrementalAUC (1112+/-3229 microU/1/180 min) or positive incremental AUC (1085+/-3195microU/I/180 min). Total insulin AUC was significantly reduced following trainingfor INT, while incremental and positive incremental insulin AUCs showed nochange.CONCLUSION: These data suggest that the method of used to calculate AUC mayaffect the interpretation of whether or not an intervention was effective. Continue reading >>

Insulin Area Under The Curve (auc) During An Oral Glucose Tolerance Test

Insulin Area Under The Curve (auc) During An Oral Glucose Tolerance Test

Insulin Area Under the Curve (AUC) During an Oral Glucose Tolerance Test During an oral glucose tolerance test the serum or plasma insulin will change over time, with an initial rise followed by a decline. The area under curve for insulin over time correlates with pancreatic beta-cell insulin secretion. The easiest way to measure the area under the curve is to measure the area for each trapezoidal region. (1) baseline insulin in pmol/L (or U/mL) (2) insulin measured at constant intervals following administration of the oral glucose solution area under each segment of time in pmol min / L = = ((concentration in pmol/L at start) + (concentration in pmol/L at end)) / 2 * (minutes in interval) total area under the curve in pmol min / L = This total area can be adjusted for a variety of factors. If we consider the baseline insulin as marking the patient's unstimulated state, then the insulin response to the glucose load is: insulin response to glucose load in pmol min/L = = (total area under curve) - ((baseline insulin) * (total time in minutes)) Sometimes the insulin response is adjusted for the patient's body mass index (BMI). insulin response adjusted for BMI in pmolminm^2 / (L kg) = = (area under curve in pmolmin/L) / (body mass index in kg per m^2) Bergstrom RW, Wahl PW, et al. Association of fasting glucose levels with a delayed secretion of insulin after oral glucose in subjects with glucose intolerance. J Clin Endocrinol Metab. 1990; 71: 1447-1453. Byrne MM, Sturis J, et al. Elevated plasma glucose 2 h postchallenge predicts defects in beta-cell function. Am J Physiol. 1996; 270: E572-E579. Phillips DIW, Clark PM, et al. Understanding oral glucose tolerance: Comparison of glucose or insulin measurements during the oral glucose tolerance test with specific measuremen Continue reading >>

Evaluation Of Fasting State-/oral Glucose Tolerance Test-derived Measures Of Insulin Release For The Detection Of Genetically Impaired -cell Function

Evaluation Of Fasting State-/oral Glucose Tolerance Test-derived Measures Of Insulin Release For The Detection Of Genetically Impaired -cell Function

Click through the PLOS taxonomy to find articles in your field. For more information about PLOS Subject Areas, click here . Evaluation of Fasting State-/Oral Glucose Tolerance Test-Derived Measures of Insulin Release for the Detection of Genetically Impaired -Cell Function Contributed equally to this work with: Silke A. Herzberg-Schfer, Harald Staiger Affiliation Division of Endocrinology, Diabetology, Angiology, Nephrology, and Clinical Chemistry, Department of Internal Medicine, University Hospital Tbingen and Eberhard Karls University Tbingen, Member of the German Center for Diabetes Research (DZD), Tbingen, Germany Contributed equally to this work with: Silke A. Herzberg-Schfer, Harald Staiger Affiliation Division of Endocrinology, Diabetology, Angiology, Nephrology, and Clinical Chemistry, Department of Internal Medicine, University Hospital Tbingen and Eberhard Karls University Tbingen, Member of the German Center for Diabetes Research (DZD), Tbingen, Germany Affiliation Division of Endocrinology, Diabetology, Angiology, Nephrology, and Clinical Chemistry, Department of Internal Medicine, University Hospital Tbingen and Eberhard Karls University Tbingen, Member of the German Center for Diabetes Research (DZD), Tbingen, Germany Affiliation Division of Endocrinology, Diabetology, Angiology, Nephrology, and Clinical Chemistry, Department of Internal Medicine, University Hospital Tbingen and Eberhard Karls University Tbingen, Member of the German Center for Diabetes Research (DZD), Tbingen, Germany Affiliation Division of Endocrinology, Diabetology, Angiology, Nephrology, and Clinical Chemistry, Department of Internal Medicine, University Hospital Tbingen and Eberhard Karls University Tbingen, Member of the German Center for Diabetes Research (DZD), Tbingen, Germany Continue reading >>

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