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- Hedman, Christina, 1964-, et al.
(författare)
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Treatment with insulin lispro changes the insulin profile but does not affect the plasma concentrations of IGF-I and IGFBP-1 in type 1 diabetes
- 2001
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Ingår i: Clinical Endocrinology. - : Wiley. - 0300-0664 .- 1365-2265. ; 55:1, s. 107-112
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE IGF-I levels in patients with type 1 diabetes without endogenous insulin production are low. Our aim was to examine whether the plasma insulin profile obtained by treatment with the insulin analogue lispro has a different effect on plasma concentrations of IGF-I and IGFBP-1 than that seen during treatment with conventional human insulin (regular insulin).DESIGN AND PATIENTS Twelve patients with type 1 diabetes, age 47·8 ± 2·4 years (mean ± SEM), body mass index 26·5 ± 1·0 kg/m2, diabetes duration 30·5 ± 3·2 years participated in this open label randomized cross-over study. IGF-I and IGFBP-1 levels were measured at the end of 6 weeks treatment with each insulin being administered by a continuous subcutaneous insulin infusion. IGF-I was measured fasting while IGFBP-1, free insulin and blood glucose were measured fasting and repeatedly after a morning meal preceded by an insulin bolus dose.RESULTS Lispro gave a marked insulin peak of 135 ± 20 pmol/l 50 minutes after injection. After an initial rapid rise, human regular insulin reached a plateau of approximately 50 pmol/l. The plasma free insulin area under the curve (AUC) from 0710 h to 0910 h was more than twice as large on lispro as on regular insulin (P = 0·01). Plasma IGF-I concentration was 78·8 ± 10·9 µg/l on lispro and 82·3 ± 10·5 µg/l on human regular insulin (not significant). AUC for IGFBP-1 did not show a significant difference even when divided from 0710 h to 0910 h and from 0930 h to 1430 h. Blood glucose AUC after administration of the bolus was significantly lower during treatment with lispro (P = 0·006) but glycosylated haemoglobin (HbA1c) was 6·4 ± 0·2% on both therapies.CONCLUSIONS Our results indicate that the effect of lispro on IGF-I and IGFBP-1 in patients with type 1 diabetes does not differ from that of human regular insulin.
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- Maack, Heidrun Petursdottir, et al.
(författare)
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Maternal body mass index moderates antenatal depression effects on infant birthweight
- 2019
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 6213-
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Tidskriftsartikel (refereegranskat)abstract
- Obesity and depression are two common medical problems that pregnant women present with in antenatal care. Overweight and obesity at the beginning of the pregnancy, and excessive weight gain during pregnancy, are independent explanatory variables for fetal birthweight and independent risk factors for giving birth to a large for gestational age (LGA) infant. However, the effect of co-morbid depression has received little attention. This study set out to investigate if maternal body mass index (BMI) in early pregnancy moderates antenatal depression effects on infant birthweight. 3965 pregnant women participated in this longitudinal cohort study, where cases (n = 178) had Edinburgh Postnatal Depression Scale (EPDS) score ≥ 17 in gestational week 17 or 32, and remaining women (n = 3787) were used as controls. The influence of maternal BMI and antenatal depressive symptoms on standardized birthweight was evaluated by analysis of covariance, with adjustment for relevant confounders. Depressed women with BMI 25.0 kg/m2 or more gave birth to infants with significantly greater standardized birthweight than non-depressed overweight women, whereas the opposite pattern was noted in normal weight women (BMI by antenatal depressive symptoms interaction; F(1,3839) = 6.32; p = 0.012. The increased birthweight in women with co-prevalent overweight and depressive symptoms was not explained by increased weight gain during the pregnancy. Maternal BMI at the beginning of pregnancy seems to influence the association between antenatal depressive symptoms and infant birthweight, but in opposite directions depending on whether the pregnant women is normal weight or overweight. Further studies are needed to confirm our finding.
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- Orre, R., et al.
(författare)
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A Bayesian recurrent neural network for unsupervised pattern recognition in large incomplete data sets
- 2005
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Ingår i: International Journal of Neural Systems. - Singapore : World Scientific. - 0129-0657 .- 1793-6462. ; 15:3, s. 207-222
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Tidskriftsartikel (refereegranskat)abstract
- A recurrent neural network, modified to handle highly incomplete training data is described. Unsupervised pattern recognition is demonstrated in the WHO database of adverse drug reactions. Comparison is made to a well established method, AutoClass, and the performances of both methods is investigated on simulated data. The neural network method performs comparably to AutoClass in simulated data, and better than AutoClass in real world data. With its better scaling properties, the neural network is a promising tool for unsupervised pattern recognition in huge databases of incomplete observations.
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- Orre, R., et al.
(författare)
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Bayesian neural networks with confidence estimations applied to data mining
- 2000
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Ingår i: Computational Statistics & Data Analysis. - 0167-9473 .- 1872-7352. ; 34:4, s. 473-493
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Tidskriftsartikel (refereegranskat)abstract
- An international database of case reports, each one describing a possible case of adverse drug reactions (ADRs), is maintained by the Uppsala Monitoring Centre (UMC), for the WHO international program on drug safety monitoring. Each report can be seen as a row in a data matrix and consists of a number of variables, like drugs used, ADRs, and other patient data. The problem is to examine the database and find significant dependencies which might be signals of potentially important ADRs, to be investigated by clinical experts. We propose a method by which estimated frequencies of combinations of variables are compared with the frequencies that would be predicted assuming there were no dependencies. The estimates of significance are obtained with a Bayesian approach via the variance of posterior probability distributions. The posterior is obtained by fusing a prior distribution (Dirichlet of dimension 2(n-1)) with a batch of data, which is also the prior used when the next batch of data arrives. To decide whether the joint probabilities of events are different fi-om what would follow from the independence assumption, the information component log(P-ij/(PiPj)) plays a crucial role, and one main technical contribution reported here is an efficient method to estimate this measure, as well as the variance of its posterior distribution, for large data matrices. The method we present is fundamentally an artificial neural network denoted Bayesian confidence propagation neural network (BCPNN). We also demonstrate an efficient way of finding complex dependencies. The method is now (autumn 1998) being routinely used to produce warning signals on new unexpected ADR associations.
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- Possnert, G, et al.
(författare)
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Oxygen content and depth profiling in silicon surface technology studied by the 16O(α, α)16O resonance at 3.045 MeV
- 1978
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Ingår i: Physica Scripta. - 0031-8949 .- 1402-4896. ; 18, s. 353-356
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Tidskriftsartikel (refereegranskat)abstract
- The use of the t6O(o,o)160 elastic scattering resonance reaction forthe study of low concentration of oxygen such as found in interfacesin silicon technology is described. We have investigated the depth resolution and the limit of the sensitivity that can be obtained with thismethod. The method has been applied to the study of AlrQ{r "sandwich" film structures and to Au and amorphous Ge contacts to silicon.
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- Rasmussen, E, et al.
(författare)
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An abnormal chest radiograph
- 1998
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Ingår i: Journal of cardiothoracic and vascular anesthesia. - : Elsevier BV. - 1053-0770. ; 12:1, s. 118-119
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Tidskriftsartikel (refereegranskat)
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