2 resultados para Low Impact Urban Design


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Currently, pharmaceutical preparations are serious contributors to liver disease; hepatotoxicity ranking as the most frequent cause for acute liver failure and post-commercialization regulatory decisions. The diagnosis of hepatotoxicity remains a difficult task because of the lack of reliable markers for use in general clinical practice. To incriminate any given drug in an episode of liver dysfunction is a step-by-step process that requires a high degree of suspicion, compatible chronology, awareness of the drug's hepatotoxic potential, the exclusion of alternative causes of liver damage and the ability to detect the presence of subtle data that favors a toxic etiology. This process is time-consuming and the final result is frequently inaccurate. Diagnostic algorithms may add consistency to the diagnostic process by translating the suspicion into a quantitative score. Such scales are useful since they provide a framework that emphasizes the features that merit attention in cases of suspected hepatic adverse reaction as well. Current efforts in collecting bona fide cases of drug-induced hepatotoxicity will make refinements of existing scales feasible. It is now relatively easy to accommodate relevant data within the scoring system and to delete low-impact items. Efforts should also be directed toward the development of an abridged instrument for use in evaluating suspected drug-induced hepatotoxicity at the very beginning of the diagnosis and treatment process when clinical decisions need to be made. The instrument chosen would enable a confident diagnosis to be made on admission of the patient and treatment to be fine-tuned as further information is collected.

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Background: The objective was to investigate the association between BMI and single nucleotide polymorphisms previously identified of obesity-related genes in two Spanish populations. Forty SNPs in 23 obesity-related genes were evaluated in a rural population characterized by a high prevalence of obesity (869 subjects, mean age 46 yr, 62% women, 36% obese) and in an urban population (1425 subjects, mean age 54 yr, 50% women, 19% obese). Genotyping was assessed by using SNPlex and PLINK for the association analysis. Results: Polymorphisms of the FTO were significantly associated with BMI, in the rural population (beta 0.87, p-value <0.001). None of the other SNPs showed significant association after Bonferroni correction in the two populations or in the pooled analysis. A weighted genetic risk score (wGRS) was constructed using the risk alleles of the Tag-SNPs with a positive Beta parameter in both populations. From the first to the fifth quintile of the score, the BMI increased 0.45 kg/m2 in Hortega and 2.0 kg/m2 in Pizarra. Overall, the obesity predictive value was low (less than 1%). Conclusion: The risk associated with polymorphisms is low and the overall effect on BMI or obesity prediction is minimal. A weighted genetic risk score based on genes mainly acting through central nervous system mechanisms was associated with BMI but it yields minimal clinical prediction for the obesity risk in the general population.