@article{GarciaSteinigerReichetal.2006,
  author    = {Garcia, A. L. and Steiniger, J. and Reich, S. C. and Weickert, M. O. and Harsch, I. and Machowetz, A. and Mohlig, M. and Spranger, Joachim and Rudovich, N. N. and Meuser, F. and Doerfer, J. and Katz, N. and Speth, M. and Zunft, Hans-Joachim Franz and Pfeiffer, Andreas F. H. and Koebnick, Corinna},
  title     = {Arabinoxylan fibre consumption improved glucose metabolism, but did not affect serum adipokines in subjects with impaired glucose tolerance},
  series = {Hormone and metabolic research},
  volume    = {38},
  journal   = {Hormone and metabolic research},
  number    = {2},
  publisher = {Thieme},
  address   = {Stuttgart},
  issn      = {0018-5043},
  doi       = {10.1055/s-2006-955089},
  pages     = {761 -- 766},
  year      = {2006},
  abstract  = {The consumption of arabinoxylan, a soluble fibre fraction, has been shown to improve glycemic control in type 2 diabetic subjects. Soluble dietary fibre may modulate gastrointestinal or adipose tissue hormones regulating food intake. The present study investigated the effects of arabinoxylan consumption on serum glucose, insulin, lipids, leptin, adiponectin and resistin in subjects with impaired glucose tolerance. In a randomized, single-blind, controlled, crossover intervention trial, 11 adults consumed white bread rolls as either placebo or supplemented with 15g arabinoxylan for 6 weeks with a 6-week washout period. Fasting serum glucose, insulin, triglycerides, unesterified fatty acids, apolipoprotein A1 and B, adiponectin, resistin and leptin were assessed before and after intervention. Fasting serum glucose, serum triglycerides and apolipoprotein A-1 were significantly lower during arabinoxylan consumption compared to placebo (p = 0.029, p = 0.047; p = 0.029, respectively). No effects of arabinoxylan were observed for insulin, adiponectin, leptin and resistin as well as for apolipoprotein B, and unesterified fatty acids. In conclusion, the consumption of AX in subjects with impaired glucose tolerance improved fasting serum glucose, and triglycerides. However, this beneficial effect was not accompanied by changes in fasting adipokine concentrations.},
  language  = {en}
}
@article{MoehligFloeterSprangeretal.2006,
  author    = {Moehlig, M. and Floeter, A. and Spranger, Joachim and Weickert, Martin O. and Schill, T. and Schloesser, H. W. and Brabant, G. and Pfeiffer, Andreas F. H. and Selbig, Joachim and Schoefl, C.},
  title     = {Predicting impaired glucose metabolism in women with polycystic ovary syndrome by decision tree modelling},
  series = {Diabetologia : journal of the European Association for the Study of Diabetes (EASD)},
  volume    = {49},
  journal   = {Diabetologia : journal of the European Association for the Study of Diabetes (EASD)},
  publisher = {Springer},
  address   = {Berlin},
  issn      = {0012-186X},
  doi       = {10.1007/s00125-006-0395-0},
  pages     = {2572 -- 2579},
  year      = {2006},
  abstract  = {Aims/hypothesis Polycystic ovary syndrome (PCOS) is a risk factor of type 2 diabetes. Screening for impaired glucose metabolism (IGM) with an OGTT has been recommended, but this is relatively time-consuming and inconvenient. Thus, a strategy that could minimise the need for an OGTT would be beneficial. Materials and methods Consecutive PCOS patients (n=118) with fasting glucose < 6.1 mmol/l were included in the study. Parameters derived from medical history, clinical examination and fasting blood samples were assessed by decision tree modelling for their ability to discriminate women with IGM (2-h OGTT value >= 7.8 mmol/l) from those with NGT. Results According to the OGTT results, 93 PCOS women had NGT and 25 had IGM. The best decision tree consisted of HOMA-IR, the proinsulin:insulin ratio, proinsulin, 17-OH progesterone and the ratio of luteinising hormone:follicle-stimulating hormone. This tree identified 69 women with NGT. The remaining 49 women included all women with IGM (100\% sensitivity, 74\% specificity to detect IGM). Pruning this tree to three levels still identified 53 women with NGT (100\% sensitivity, 57\% specificity to detect IGM). Restricting the data matrix used for tree modelling to medical history and clinical parameters produced a tree using BMI, waist circumference and WHR. Pruning this tree to two levels separated 27 women with NGT (100\% sensitivity, 29\% specificity to detect IGM). The validity of both trees was tested by a leave-10\%-out cross-validation. Conclusions/interpretation Decision trees are useful tools for separating PCOS women with NGT from those with IGM. They can be used for stratifying the metabolic screening of PCOS women, whereby the number of OGTTs can be markedly reduced.},
  language  = {en}
}