Thesis (Ph.D.)--The University of Auckland (New Zealand), 2006. / (UMI)AAI3247607. Advisers: Jane Harding; Chris Williams. Source: Dissertation Abstracts International, Volume: 67-12, Section: B, page: 6999.

Thèse (Ph.D.)--Université de Sherbrooke (Canada), 2008. / Titre de l'écran-titre (visionné le 1 février 2007). In ProQuest dissertations and theses. Publié aussi en version papier.

Thèse (Ph.D.)--Université de Sherbrooke (Canada), 2007. / Titre de l'écran-titre (visionné le 1 février 2007). In ProQuest dissertations and theses. Publié aussi en version papier.

Thèse (M.Sc.)--Université de Sherbrooke (Canada), 2007. / Titre de l'écran-titre (visionné le 1 février 2007). In ProQuest dissertations and theses. Publié aussi en version papier.

Thèse (M.Sc.)--Université de Sherbrooke (Canada), 2008. / Titre de l'écran-titre (visionné le 1 février 2007). In ProQuest dissertations and theses. Publié aussi en version papier.

Thèse (M.Sc.)--Université de Sherbrooke (Canada), 2007. / Titre de l'écran-titre (visionné le 1 février 2007). In ProQuest dissertations and theses. Publié aussi en version papier.

Thèses (M.Sc.)--Université de Sherbrooke (Canada), 2005. / Titre de l'écran-titre (visionné le 22 oct. 2007). In ProQuest dissertations and theses. Publié aussi en version papier.

DISSERTATION (PH.D.)--THE UNIVERSITY OF MICHIGAN

Drug-Drug interactions (DDIs) are an important focus of patient safety because they account for a substantial number of adverse drug events and are preventable. Objective. To study DDIs in a Canadian hospital, a retrospective observational study was completed using the Ottawa Hospital Data Warehouse. Study cohort. Admissions to the Ottawa hospital between January 1, 1999 and September 30, 2005. Methods. Potential drug-drug interactions were identified by examining all co-administered medications for combinations of drugs previously reported to have potential interactions. Poisson regression was used to examine potential patient and hospital factors associated with drug-drug interactions. Results. Between 1999 and 2005, we found at least one DDI in 19.3% of all hospitalizations and 18.8% of hospitalization time. Category 1 (drug combinations to be avoided) and Category 2 (drug combinations usually avoided) interactions were rare, accounting for only 0.022% and 1.4% of hospitalization time, respectively. Category 3 interactions (drug combinations requiring alteration) occurred with 5.7% of all drug orders and were present for 17.4% of hospitalization time. Poisson regression analysis found that DDIs were significantly more likely to occur in patients who were: older; admitted to a surgical service; had a greater number of comorbidities; and were prescribed a greater number of drugs. Conclusion. Drug-Drug interactions occurred frequently during hospitalization. Future study is required to determine if the interactions identified are associated with important clinical outcomes.

Background. The effective use of knowledge related to gene-disease associations relies on the optimal conduct and reporting of research studies. Transparent reporting enables readers to identify the strengths and weaknesses of research studies and subsequently to determine the quality of evidence that they offer. Objective. To investigate the relation between methodological characteristics and the direction and magnitude of effects observed in case-control studies of gene-disease associations. Methods. Articles were randomly selected from a database of published studies on genetic associations and other epidemiologic research pertaining to the human genome (the HuGE Literature Finder). The analysis evaluated 511 articles indexed in HuGENet in 2007. Gene-gene interaction studies and gene-environment interaction studies were excluded. Univariate and multivariate meta-regression analyses using a random effects model were used to assess the relationship between methodological characteristics and the direction and magnitude of genetic associations. Results. The studies included in the analysis had been conducted in a total of 52 countries and were published in 220 journals (median impact factor 5.1). The multivariate meta-regression model of methodological characteristics was able to account for 17.2% of the between-study variance in the magnitude of gene-disease associations. Of the factors included in the multivariate regression model, the following tended to be associated with a smaller magnitude of effect: replication of a previously conducted study; nested case-control study design; individual matching of study participants; and reporting of sample size or of statistical power calculation. Moreover, the magnitude of effect tended to decrease as the number of controls increased. By contrast, studies that did not report the process of selecting control participants or that reported that the genotype distribution departed from Hardy-Weinberg equilibrium tended to be associated with larger magnitudes of effect. Studies conducted in North America, Europe, and China had similar magnitudes of effect. Conclusion. Within the constraints of limitations in reporting, a number of methodological features of gene-disease association studies are associated systematically with the magnitude of effect observed. This provides evidence to direct efforts to improve the reporting of research on genetic associations.