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

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

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 analyses of pericardial fat (PERI) and myocardial fat (MYCL) with cardiac index and E/A ratio in all subjects.

<p>Correlation analyses of pericardial fat (PERI) and myocardial fat (MYCL) with cardiac index and E/A ratio in all subjects.</p