Postprandiale Hypoglykämie nach Magenbypass

Bariatrische Operationen haben sich in der Behandlung der Adipositas als Therapieoption bewährt. Zu den postoperativen Risiken gehört neben dem Dumpingsyndrom auch die postprandiale Hypoglykämie. Sie entwickelt sich oft erst einige Monate bis Jahre nach der Operation und kann in Einzelfällen mit bedrohlichen Symptomen wie Bewusstseinsstörungen und Krampfanfällen einhergehen. Als eine wichtige Ursache gilt die inkretininduzierte inadäquate postprandiale Hyperinsulinämie. Auch erhöhte präoperative Konzentrationen von Insulin-like Growth Factor 1 (IGF-1) können mit einem erhöhten Risiko für die postprandiale Hypoglykämie verbunden sein. Grundlage der Therapie ist eine intensive diätologische Betreuung mit Identifikation der auslösenden Mahlzeiten. Schnell resorbierbare Kohlehydrate sollten generell vermieden werden. Medikamente wie Acarbose können den postprandialen Glukoseanstieg reduzieren und damit den Stimulus für die Insulinsekretion minimieren. Insgesamt ist die postprandiale Hypoglykämie noch nicht ausreichend erforscht; die Entwicklung standardisierter diagnostischer Tests ist dringend erforderlich.Bariatric surgery has proved successful as a treatment option for obesity. Dumping syndrome and postprandial hypoglycemia are among the postoperative risks. The latter often develops several months to years after surgery and in individual cases it may be associated with life-threatening symptoms such as loss of consciousness and seizures. A significant cause is impaired incretin-induced postprandial hyperinsulinemia. Raised preoperative concentrations of insulin-like growth factor 1 (IGF-1) may also be linked to an increased risk of postprandial hypoglycemia. The basis of treatment is intensive dietary supervision, with identification of the triggering foods. Fast-absorbing carbohydrates should generally be avoided. Medications such as acarbose can reduce the postprandial increase in glucose, thus minimizing the stimulus for insulin secretion. Overall, postprandial hypoglycemia has not yet been sufficiently studied; the development of standardized diagnostic tests is urgently required.(VLID)361991

Pericardial- Rather than Intramyocardial Fat Is Independently Associated with Left Ventricular Systolic Heart Function in Metabolically Healthy Humans.

BACKGROUND:Obesity is a major risk factor to develop heart failure, in part due to possible lipotoxic effects of increased intramyocardial (MYCL) and/or local or paracrine effects of pericardial (PERI) lipid accumulation. Recent evidence suggests that MYCL is highly dynamic and might rather be a surrogate marker for disturbed energy metabolism than the underlying cause of cardiac dysfunction. On the other hand, PERI might contribute directly by mechanic and paracrine effects. Therefore, we hypothesized that PERI rather than MYCL is associated with myocardial function. METHODS:To avoid potential confounding of metabolic disease 31 metabolically healthy subjects (age: 29±10yrs; BMI: 23±3kg/m2) were investigated using 1H-magnetic resonance spectroscopy and imaging. MYCL and PERI, as well as systolic and diastolic left ventricular heart function were assessed. Additionally, anthropometric data and parameters of glucose and lipid metabolism were analyzed. Correlation analysis was performed using Pearson's correlation coefficient. Linear regression model was used to show individual effects of PERI and MYCL on myocardial functional parameters. RESULTS:Correlation analysis with parameters of systolic heart function revealed significant associations for PERI (Stroke Volume (SV): R = -0.513 p = 0.001; CardiacIndex (CI): R = -0.442 p = 0.014), but not for MYCL (SV: R = -0.233; p = 0.207; CI: R = -0.130; p = 0.484). No significant correlations were found for E/A ratio as a parameter of diastolic heart function. In multiple regression analysis CI was negatively predicted by PERI, whereas no impact of MYCL was observed in direct comparison. CONCLUSIONS:Cardiac fat depots impact left ventricular heart function in a metabolically healthy population. Direct comparison of different lipid stores revealed that PERI is a more important predictor than MYCL for altered myocardial function

Whole-body insulin sensitivity rather than body-mass-index determines fasting and post-glucose-load growth hormone concentrations.

Obese, non-acromegalic persons show lower growth hormone (GH) concentrations at fasting and reduced GH nadir during an oral glucose tolerance test (OGTT). However, this finding has never been studied with regard to whole-body insulin-sensitivity as a possible regulator.In this retrospective analysis, non-acromegalic (NonACRO, n = 161) and acromegalic (ACRO, n = 35), non-diabetic subjects were subdivided into insulin-sensitive (IS) and -resistant (IR) groups according to the Clamp-like Index (CLIX)-threshold of 5 mg · kg(-1) · min(-1) from the OGTT.Non-acromegalic IS (CLIX: 8.8 ± 0.4 mg · kg(-1) · min(-1)) persons with similar age and sex distribution, but lower (p < 0.001) body-mass-index (BMI = 25 ± 0 kg/m2, 84% females, 56 ± 1 years) had 59% and 70%, respectively, higher (p < 0.03) fasting GH and OGTT GH area under the curve concentrations than IR (CLIX: 3.5 ± 0.1 mg · kg(-1) · min(-1), p < 0.001) subjects (BMI = 29 ± 1 kg/m2, 73% females, 58 ± 1 years). When comparing on average overweight non-acromegalic IS and IR with similar anthropometry (IS: BMI: 27 ± 0 kg/m2, 82% females, 58 ± 2 years; IR: BMI: 27 ± 0 kg/m2, 71% females, 60 ± 1 years), but different CLIX (IS: 8.7 ± 0.9 vs. IR: 3.8 ± 0.1 mg · kg(-1) · min(-1), p < 0.001), the results remained almost the same. In addition, when adjusted for OGTT-mediated glucose rise, GH fall was less pronounced in IR. In contrast, in acromegalic subjects, no difference was found between IS and IR patients with regard to fasting and post-glucose-load GH concentrations.Circulating GH concentrations at fasting and during the OGTT are lower in non-acromegalic insulin-resistant subjects. This study seems the first to demonstrate that insulin sensitivity rather than body-mass modulates fasting and post-glucose-load GH concentrations in non-diabetic non-acromegalic subjects

Journal of Magnetic Resonance Imaging / Absolute Quantification of Phosphor-Containing Metabolites in the Liver Using 31P MRSI and Hepatic Lipid Volume Correction at 7T Suggests No Dependence on Body Mass Index or Age

Background Hepatic disorders are often associated with changes in the concentration of phosphorus31 (31P) metabolites. Absolute quantification offers a way to assess those metabolites directly but introduces obstacles, especially at higher field strengths (B0 7T). Purpose To introduce a feasible method for in vivo absolute quantification of hepatic 31P metabolites and assess its clinical value by probing differences related to volunteers' age and body mass index (BMI). Study Type Prospective cohort. Subjects/Phantoms Four healthy volunteers included in the reproducibility study and 19 healthy subjects arranged into three subgroups according to BMI and age. Phantoms containing 31P solution for correction and validation. Field Strength/Sequence Phaseencoded 3D pulseacquire chemical shift imaging for 31P and singlevolume 1H spectroscopy to assess the hepatocellular lipid content at 7T. Assessment A phantom replacement method was used. Spectra located in the liver with sufficient signaltonoise ratio and no contamination from muscle tissue, were used to calculate following metabolite concentrations: adenosine triphosphates ( and ATP); glycerophosphocholine (GPC); glycerophosphoethanolamine (GPE); inorganic phosphate (Pi); phosphocholine (PC); phosphoethanolamine (PE); uridine diphosphateglucose (UDPG); nicotinamide adenine dinucleotidephosphate (NADH); and phosphatidylcholine (PtdC). Correction for hepatic lipid volume fraction (HLVF) was performed. Statistical Tests Differences assessed by analysis of variance with Bonferroni correction for multiple comparison and with a Student's ttest when appropriate. Results The concentrations for the young lean group corrected for HLVF were 2.56 0.10 mM for ATP (mean standard deviation), ATP: 2.42 0.15 mM, GPC: 3.31 0.27 mM, GPE: 3.38 0.87 mM, Pi: 1.42 0.20 mM, PC: 1.47 0.24 mM, PE: 1.61 0.20 mM, UDPG: 0.74 0.17 mM, NADH: 1.21 0.38 mM, and PtdC: 0.43 0.10 mM. Differences found in ATP levels between lean and overweight volunteers vanished after HLVF correction. Data Conclusion Exploiting the excellent spectral resolution at 7T and using the phantom replacement method, we were able to quantify up to 10 31Pcontaining hepatic metabolites. The combination of 31P magnetic resonance spectroscopy imaging data acquisition and HLVF correction was not able to show a possible dependence of 31P metabolite concentrations on BMI or age, in the small healthy population used in this study.(VLID)341761

R-values of pericardial (PERI) and intramyocardial (MYCL) adipose tissue with parameters of systolic and diastolic left ventricular functional parameters using Pearson correlation analysis in all subjects.

<p>R-values of pericardial (PERI) and intramyocardial (MYCL) adipose tissue with parameters of systolic and diastolic left ventricular functional parameters using Pearson correlation analysis in all subjects.</p

Anthropometrical characteristics and baseline examination and laboratory values, oral glucose tolerance test (OGTT) results and areas under the curve (AUCs), estimates of insulin sensitivity and insulin secretion parameters and indexes in non-diabetic insulin-resistant (IR) and –sensitive (IS) subjects without acromegaly (NonACRO), without acromegaly and with similar body mass index ((NonACRO-sBMI), and acromegaly (ACRO).

<p>Differences were analyzed by using the <i>Student</i>'s t–test: *, p<0.05 IR-NonACRO vs. IS-NonACRO; #, p<0.01 IR-NonACRO vs. IS-NonACRO; $, p<0.001 IR-NonACRO vs. IS-NonACRO; +, p<0.05 IR-NonACRO-sBMI vs. IS-NonACRO-sBMI; §, p<0.01 IR-NonACRO-sBMI vs. IS-NonACRO-sBMI; €, p<0.001 IR-NonACRO-sBMI vs. IS-NonACRO-sBMI; ÷, p<0.05 IR-ACRO vs. IS-ACRO; ¶, p<0.01 IR-ACRO vs. IS-ACRO; £, p<0.001 IR-ACRO vs. IS-ACRO.</p><p>Anthropometrical characteristics and baseline examination and laboratory values, oral glucose tolerance test (OGTT) results and areas under the curve (AUCs), estimates of insulin sensitivity and insulin secretion parameters and indexes in non-diabetic insulin-resistant (IR) and –sensitive (IS) subjects without acromegaly (NonACRO), without acromegaly and with similar body mass index ((NonACRO-sBMI), and acromegaly (ACRO).</p

Multiple regression analysis for cardiac index as depending variable; MYCL: myocardial lipid content.

<p>Multiple regression analysis for cardiac index as depending variable; MYCL: myocardial lipid content.</p

Multiple linear regression analyses with total area under the curve (AUC) of oral glucose tolerance test (OGTT) growth hormone and baseline ( = 0 min) growth hormone as dependent variables, and systolic blood pressure, sex, age, body mass index (BMI) and insulin sensitivity, determined by the Clamp–like Index (CLIX) as predictors, in all participants, all insulin resistant (IR) combined, all insulin sensitive (IS) combined, and non- acromegalic (NonACRO) subjects combined, with IR and IS subgroups, and all acromegalic (ACRO) combined, again with subgroups.

<p>The regression coefficient (<i>r</i>) with B± standard error of the mean (SE) and p-value is given for each outcome; in case the model did not yield satisfactory results, an <i>r</i>–value of 0 is listed.</p><p>Multiple linear regression analyses with total area under the curve (AUC) of oral glucose tolerance test (OGTT) growth hormone and baseline ( = 0 min) growth hormone as dependent variables, and systolic blood pressure, sex, age, body mass index (BMI) and insulin sensitivity, determined by the Clamp–like Index (CLIX) as predictors, in all participants, all insulin resistant (IR) combined, all insulin sensitive (IS) combined, and non- acromegalic (NonACRO) subjects combined, with IR and IS subgroups, and all acromegalic (ACRO) combined, again with subgroups.</p

Anthropometric characteristics, laboratory parameters and data of magnetic resonance measurements; parameters of left ventricular (LV) myocardial function was normalized to body surface area using the Dubois-formula.

<p>Anthropometric characteristics, laboratory parameters and data of magnetic resonance measurements; parameters of left ventricular (LV) myocardial function was normalized to body surface area using the Dubois-formula.</p

Correlation coefficients (<i>Pearson</i>–correlation moment products) and significance levels (p–values) of total of area under the curve (AUC) of growth hormone (GH) and basal growth hormone concentrations with anthropometric measures, parameters of the baseline clinical lab, OGTT outcomes, as fasting endogenous glucose production, hepatic insulin extraction, values of insulin sensitivity and indexes of insulin secretion in non- acromegalic (NonACRO) and acromegalic (ACRO) subjects separated.

<p>Correlation coefficients (<i>Pearson</i>–correlation moment products) and significance levels (p–values) of total of area under the curve (AUC) of growth hormone (GH) and basal growth hormone concentrations with anthropometric measures, parameters of the baseline clinical lab, OGTT outcomes, as fasting endogenous glucose production, hepatic insulin extraction, values of insulin sensitivity and indexes of insulin secretion in non- acromegalic (NonACRO) and acromegalic (ACRO) subjects separated.</p