Specific age-related NICMs and Pp were more common among HIV-infected patients than in the general population. The prevalence of Pp in HIV-infected persons anticipated Pp prevalence observed in the general population among persons who were 10 years older, and HIV-specific cofactors (lower nadir CD4 cell count and more prolonged ART exposure) were identified as risk factors. These data support the need for earlier screening for NICMs in HIV-infected patients.

Background and Aim:: The magnitude of the risk of incident type 2 diabetes (T2D) and metabolic syndrome (MetS) among patients with nonalcoholic fatty liver disease (NAFLD) is poorly known. We gauged the risk of developing T2D and MetS in patients with NAFLD diagnosed by either serum liver enzymes (aminotransferases or gamma-glutamyltransferase [GGT]) or ultrasonography. Methods:: Pertinent prospective studies were identified through extensive electronic database research, and studies fulfilling enrolment criteria were included in the meta-analysis. Results: Overall, in a pooled population of 117020 patients (from 20 studies), who were followed-up for a median period of 5years (range: 3-14.7years), NAFLD was associated with an increased risk of incident T2D with a pooled relative risk of 1.97 (95% confidence interval [CI], 1.80-2.15) for alanine aminotransferase, 1.58 (95% CI, 1.43-1.74) for aspartate aminotransferase, 1.86 (95% CI, 1.71-2.03) for GGT (last vs first quartile or quintile), and 1.86 (95% CI, 1.76-1.95) for ultrasonography, respectively. Overall, in a pooled population of 81411 patients (from eight studies) who were followed-up for a median period of 4.5years (range: 3-11years), NAFLD was associated with an increased risk of incident MetS with a pooled relative risk of 1.80 (95% CI, 1.72-1.89) for alanine aminotransferase (last vs first quartile or quintile), 1.98 (95% CI, 1.89-2.07) for GGT, and 3.22 (95% CI, 3.05-3.41) for ultrasonography, respectively. Conclusions:: Nonalcoholic fatty liver disease, as diagnosed by either liver enzymes or ultrasonography, significantly increases the risk of incident T2D and MetS over a median 5-year follow-up

While conjugate Bayesian inference in decomposable Gaussian graphical models is largely solved, the non-decomposable case still poses diculties concerned with the speci®cation of suitable priors and the evaluation of normalizing constants. In this paper we derive the DY-conjugate prior (Diaconis & Ylvisaker, 1979) for non-decomposable models and show that it can be regarded as a generalization to an arbitrary graph G of the hyper inverse Wishart distribution (Dawid & Lauritzen, 1993). In particular, if G is an incomplete prime graph it constitutes a non-trivial generalization of the inverse Wishart distribution. Inference based on marginal likelihood requires the evaluation of a normalizing constant and we propose an importance sampling algorithm for its computation. Examples of structural learning involving nondecomposable models are given. In order to deal eciently with the set of all positive de®nite matrices with non-decomposable zero-pattern we introduce the operation of triangular completion of an incomplete triangular matrix. Such a device turns out to be extremely useful both in the proof of theoretical results and in the implementation of the Monte Carlo procedure.

The androgen receptor (AR) has two polymorphic sites in exon 1, characterized by different numbers of CAG and GGC repeats resulting in variable lengths of polyglutamine and polyglycine stretches. Longer CAG repeats result in a reduced AR transcriptional activity, whereas the role of the GGC triplets is less clear. A relationship between decreased spermatogenesis and moderate expansion in the CAG tract has been found in some studies, but not in others. Furthermore, the joint distribution of CAG and GGC repeats in male infertility has never been reported before. We analysed CAG and GGC repeat lengths in a group of 163 men with idiopathic infertility compared with 115 fertile normozoospermic men. No difference was found between patients and controls in the mean and median values, and in distribution of CAG and GGC, when considered separately. However, the analysis of the joint distribution of CAG and GGC showed that the distribution of particular haplotypes is significantly different between patients and controls. In particular, two CAG/GGC haplotypes seem to increase susceptibility to infertility (CAG = 21/GGC = 18 and CAG >/=21/GGC >/=18, relative risk 2.47 and 1.6), while one haplotype (CAG >/=23/GGC

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