Oral prednisolone induced acute generalized exanthematous pustulosis due to corticosteroids of group A confirmed by epicutaneous testing and lymphocyte transformation tests

BACKGROUND: Acute generalized exanthematous pustulosis (AGEP) is a rare cutaneous eruption which is often provoked by drugs. CASE REPORT: We report 2 cases of AGEP which showed rapidly spreading pustular eruptions accompanied by malaise, fever and neutrophilia after the administration of systemic prednisolone (corticosteroid of group A, hydrocortisone type). The histological examination showing neutrophilic subcorneal spongiform pustules was consistent with the diagnosis of AGEP. In both cases the rash cleared within a week upon treatment with topical steroids (corticosteroid of group D1, betamethasonedipropionate type and corticosteroid of group D2, hydrocortisone-17-butyrate type). Three months after recovery, the sensitization to corticosteroids of group A was confirmed by epicutaneous testing and positive lymphocyte transformation tests. CONCLUSION: These cases show that systemic corticosteroids can induce AGEP and demonstrate that epicutaneous testing and lymphocyte transformation tests may be helpful in identifying the causative drug. Our data support previous reports indicating an important role for drug-specific T cells in inducing neutrophil inflammation in this disease.

Monotone Constrained Tensor-product B-spline with application to screening studies

When different markers are responsive to different aspects of a disease, combination of multiple markers could provide a better screening test for early detection. It is also resonable to assume that the risk of disease changes smoothly as the biomarker values change and the change in risk is monotone with respect to each biomarker. In this paper, we propose a boundary constrained tensor-product B-spline method to estimate the risk of disease by maximizing a penalized likelihood. To choose the optimal amount of smoothing, two scores are proposed which are extensions of the GCV score (O'Sullivan et al. (1986)) and the GACV score (Ziang and Wahba (1996)) to incorporate linear constraints. Simulation studies are carried out to investigate the performance of the proposed estimator and the selection scores. In addidtion, sensitivities and specificities based ona pproximate leave-one-out estimates are proposed to generate more realisitc ROC curves. Data from a pancreatic cancer study is used for illustration.

Asymptotics for Marginal Generalized Linear Models With Sparse Correlations

Marginal generalized linear models can be used for clustered and longitudinal data by fitting a model as if the data were independent and using an empirical estimator of parameter standard errors. We extend this approach to data where the number of observations correlated with a given one grows with sample size and show that parameter estimates are consistent and asymptotically Normal with a slower convergence rate than for independent data, and that an information sandwich variance estimator is consistent. We present two problems that motivated this work, the modelling of patterns of HIV genetic variation and the behavior of clustered data estimators when clusters are large.

Smooth Estimation of a Monotone Density

We investigate the interplay of smoothness and monotonicity assumptions when estimating a density from a sample of observations. The nonparametric maximum likelihood estimator of a decreasing density on the positive half line attains a rate of convergence at a fixed point if the density has a negative derivative. The same rate is obtained by a kernel estimator, but the limit distributions are different. If the density is both differentiable and known to be monotone, then a third estimator is obtained by isotonization of a kernel estimator. We show that this again attains the rate of convergence and compare the limit distributors of the three types of estimators. It is shown that both isotonization and smoothing lead to a more concentrated limit distribution and we study the dependence on the proportionality constant in the bandwidth. We also show that isotonization does not change the limit behavior of a kernel estimator with a larger bandwidth, in the case that the density is known to have more than one derivative.

Classification Using Generalized Partial Least Squares

The advances in computational biology have made simultaneous monitoring of thousands of features possible. The high throughput technologies not only bring about a much richer information context in which to study various aspects of gene functions but they also present challenge of analyzing data with large number of covariates and few samples. As an integral part of machine learning, classification of samples into two or more categories is almost always of interest to scientists. In this paper, we address the question of classification in this setting by extending partial least squares (PLS), a popular dimension reduction tool in chemometrics, in the context of generalized linear regression based on a previous approach, Iteratively ReWeighted Partial Least Squares, i.e. IRWPLS (Marx, 1996). We compare our results with two-stage PLS (Nguyen and Rocke, 2002A; Nguyen and Rocke, 2002B) and other classifiers. We show that by phrasing the problem in a generalized linear model setting and by applying bias correction to the likelihood to avoid (quasi)separation, we often get lower classification error rates.

Posterior Simulation in the Generalized Linear Model with Semiparmetric Random Effects

Generalized linear mixed models with semiparametric random effects are useful in a wide variety of Bayesian applications. When the random effects arise from a mixture of Dirichlet process (MDP) model, normal base measures and Gibbs sampling procedures based on the Pólya urn scheme are often used to simulate posterior draws. These algorithms are applicable in the conjugate case when (for a normal base measure) the likelihood is normal. In the non-conjugate case, the algorithms proposed by MacEachern and Müller (1998) and Neal (2000) are often applied to generate posterior samples. Some common problems associated with simulation algorithms for non-conjugate MDP models include convergence and mixing difficulties. This paper proposes an algorithm based on the Pólya urn scheme that extends the Gibbs sampling algorithms to non-conjugate models with normal base measures and exponential family likelihoods. The algorithm proceeds by making Laplace approximations to the likelihood function, thereby reducing the procedure to that of conjugate normal MDP models. To ensure the validity of the stationary distribution in the non-conjugate case, the proposals are accepted or rejected by a Metropolis-Hastings step. In the special case where the data are normally distributed, the algorithm is identical to the Gibbs sampler.

Gauss-Seidel Estimation of Generalized Linear Mixed Models with Application to Poisson Modeling of Spatially Varying Disease Rates

Generalized linear mixed models (GLMMs) provide an elegant framework for the analysis of correlated data. Due to the non-closed form of the likelihood, GLMMs are often fit by computational procedures like penalized quasi-likelihood (PQL). Special cases of these models are generalized linear models (GLMs), which are often fit using algorithms like iterative weighted least squares (IWLS). High computational costs and memory space constraints often make it difficult to apply these iterative procedures to data sets with very large number of cases. This paper proposes a computationally efficient strategy based on the Gauss-Seidel algorithm that iteratively fits sub-models of the GLMM to subsetted versions of the data. Additional gains in efficiency are achieved for Poisson models, commonly used in disease mapping problems, because of their special collapsibility property which allows data reduction through summaries. Convergence of the proposed iterative procedure is guaranteed for canonical link functions. The strategy is applied to investigate the relationship between ischemic heart disease, socioeconomic status and age/gender category in New South Wales, Australia, based on outcome data consisting of approximately 33 million records. A simulation study demonstrates the algorithm's reliability in analyzing a data set with 12 million records for a (non-collapsible) logistic regression model.

Maximum principle preserving high order schemes for convection-dominated diffusion equations

The maximum principle is an important property of solutions to PDE. Correspondingly, it's of great interest for people to design a high order numerical scheme solving PDE with this property maintained. In this thesis, our particular interest is solving convection-dominated diffusion equation. We first review a nonconventional maximum principle preserving(MPP) high order finite volume(FV) WENO scheme, and then propose a new parametrized MPP high order finite difference(FD) WENO framework, which is generalized from the one solving hyperbolic conservation laws. A formal analysis is presented to show that a third order finite difference scheme with this parametrized MPP flux limiters maintains the third order accuracy without extra CFL constraint when the low order monotone flux is chosen appropriately. Numerical tests in both one and two dimensional cases are performed on the simulation of the incompressible Navier-Stokes equations in vorticity stream-function formulation and several other problems to show the effectiveness of the proposed method.

Generalized dilating diathesis in patients with popliteal arterial aneurysm

BACKGROUND: Aim of this study was to analyse the relationship between popliteal artery aneurysm (PAA) and generalized arteriomegaly. PATIENTS AND METHODS: In this consecutive serie, thirty-three patients (1 woman, mean age 69.7 +/- 9.6 years) undergoing PAA repair between 1996 and 2000 agreed to participate in a duplex screening program to assess the diameters of the infrarenal abdominal aorta, common and external iliac, common and superficial femoral and contralateral popliteal arteries as well as common carotid and brachial arteries. RESULTS: The prevalence of arteriomegaly and aneurysmal disease, respectively, was as follows: abdominal aorta 15/33 (45.5%) and 8/33 (24.2%), common iliac artery 34/66 (51.5%) and 23/66 (34.8%), common femoral artery 55/66 (83.3%) and 7/66 (10.6%) as well as contralateral popliteal artery 7/33 (21.2%) 15/33 (45.5%). Significantly larger carotid artery diameters were found comparing PAA patients with age- and body surface adjusted healthy controls (p < 0.001). Furthermore, patients with multiple peripheral arterial aneurysms had significantly larger diameters of the brachial (p < 0.02) and external iliac (p < 0.005). CONCLUSIONS: Our findings support the hypothesis of a diathesis for a generalized arteriomegaly with a predilection for further aneurysms of the abdominal aorta, iliac arteries, femoral and contralateral popliteal arteries in patients with PAA.

Chronic stimulation of the globus pallidus internus for treatment of non-dYT1 generalized dystonia and choreoathetosis: 2-year follow up

OBJECT: The authors studied the long-term efficacy of deep brain stimulation (DBS) of the posteroventral lateral globus pallidus internus up to 2 years postoperatively in patients with primary non-DYT1 generalized dystonia or choreoathetosis. The results are briefly compared with those reported for DBS in DYT1 dystonia (Oppenheim dystonia), which is caused by the DYT1 gene. METHODS: Enrollment in this prospective expanded pilot study was limited to adult patients with severely disabling, medically refractory non-DYT1 generalized dystonia or choreoathetosis. Six consecutive patients underwent follow-up examinations at defined intervals of 3 months, 1 year, and 2 years postsurgery. There were five women and one man, and their mean age at surgery was 45.5 years. Formal assessments included both the Burke-Fahn-Marsden dystonia scale and the recently developed Unified Dystonia Rating Scale. Two patients had primary generalized non-DYT1 dystonia, and four suffered from choreoathetosis secondary to infantile cerebral palsy. Bilateral quadripolar DBS electrodes were implanted in all instances, except in one patient with markedly asymmetrical symptoms. There were no adverse events related to surgery. The Burke-Fahn-Marsden scores in the two patients with generalized dystonia improved by 78 and 71% at 3 months, by 82 and 69% at 1 year, and by 78 and 70% at 2 years postoperatively. This was paralleled by marked amelioration of disability scores. The mean improvement in Burke-Fahn-Marsden scores in patients with choreoathetosis was 12% at 3 months, 29% at 1 year, and 23% at 2 years postoperatively, which was not significant. Two of these patients thought that they had achieved marked improvement at 2 years postoperatively, although results of objective evaluations were less impressive. In these two patients there was a minor but stable improvement in disability scores. All patients had an improvement in pain scores at the 2-year follow-up review. Medication was tapered off in both patients with generalized dystonia and reduced in two of the patients with choreoathetosis. All stimulation-induced side effects were reversible on adjustment of the DBS settings. Energy consumption of the batteries was considerably higher than in patients with Parkinson disease. CONCLUSIONS: Chronic pallidal DBS is a safe and effective procedure in generalized non-DYT1 dystonia, and it may become the procedure of choice in patients with medically refractory dystonia. Postoperative improvement of choreoathetosis is more modest and varied, and subjective ratings of outcome may exceed objective evaluations.