All the main air pollutants, with the exception of ozone, were significantly associated with a near-term increase in MI risk.

The aim of this study was to assess the factors, including surgical portosystemic shunts, which affect survival in adults with Budd-Chiari syndrome. Multivariate retrospective analysis was performed using characteristics recorded at the time of diagnosis in 120 patients admitted from 1970 to 1992, of whom 82 were treated with surgical portosystemic shunts and 38 received only medical therapy. The 1-, 5-, and 10-year survival rates were 77 ؎ 4%, 64 ؎ 5%, and 57 ؎ 6%, respectively. Survival was significantly better in the subgroup of patients diagnosed after versus before 1985. In both subgroups, and in patients with, as well as in patients without surgical shunts, 4 factors were found to be inversely and independently related to survival: age, response of ascites to diuretics, Pugh score, and serum creatinine. In patients diagnosed since 1985, an index combining these 4 factors allowed to differentiate patients with a good outcome (5-year survival 95%) from those with a poor outcome (5-year survival 62%; P F .05). There was no statistically significant and independent influence of surgical portosystemic shunts on survival. In conclusion, age, severity of liver failure, and presence of refractory ascites are the main prognostic factors in Budd-Chiari syndrome. Increased survival in recent years is consistent with improved management of hypercoagulable states as well as improved general care. It is uncertain whether surgical portosystemic shunting favorably modifies survival. Therefore, we recommend that surgical shunting should be restricted to management of refractory ascites or variceal bleeding in patients with otherwise good prognostic factors. (HEPATOLOGY 1999;30:84-89.)

SummaryIt is now widely accepted that haplotypic information can be of great interest for investigating the role of a candidate gene in the etiology of complex diseases. In the absence of family data, haplotypes cannot be deduced from genotypes, except for individuals who are homozygous at all loci or heterozygous at only one site. Statistical methodologies are therefore required for inferring haplotypes from genotypic data and testing their association with a phenotype of interest. Two maximum likelihood algorithms are often used in the context of haplotype-based association studies, the Newton-Raphson (NR) and the Expectation-Maximisation (EM) algorithms. In order to circumvent the limitations of both algorithms, including convergence to local minima and saddle points, we here described how a stochastic version of the EM algorithm, referred to as SEM, could be used for testing haplotypephenotype association. Statistical properties of the SEM algorithm were investigated through a simulation study for a large range of practical situations, including small/large samples and rare/frequent haplotypes, and results were compared to those obtained by use of the standard NR algorithm. Our simulation study indicated that the SEM algorithm provides results similar to those of the NR algorithm, making the SEM algorithm of great interest for haplotype-based association analysis, especially when the number of polymorphisms is quite large.

No abstract