02–1.03). Further analyses for interactions demonstrated different time trends for different ages and different levels of comorbidity for nonvariceal hemorrhage (likelihood ratio tests for interactions of both age and comorbidity with year, P < .001) but not for variceal hemorrhage (year and age, P = .29; year and

comorbidity, P = .67). Consequently, the age-specific stratum average annual changes in odds of mortality for nonvariceal hemorrhage are presented in Table 4. The annual improvement in odds of mortality was minimal for those presenting 80 years and older compared with all the other age groups. Further stratifying the model by age and comorbidity ( Table 5) demonstrated that, within each age-specific stratum, the improvement in mortality did not differ by the level of comorbidity. Therefore, the final model of a linear trend Selumetinib manufacturer in 28-day

mortality for nonvariceal hemorrhage is the model shown in Table 4, with confounding by comorbidity adjusted for by logistic regression and effect modification demonstrated by stratifying the results by age. The final model of Gefitinib mouse a linear trend in 28-day mortality for variceal hemorrhage demonstrated only confounding by both comorbidity and age with no effect modification. The failure of previous studies to demonstrate improvements in mortality after upper gastrointestinal hemorrhage at the population level calls into question the value of therapeutic changes that are of proven benefit to individuals. In an increasingly challenging economic environment, clinicians will need to be able to demonstrate that increased therapeutic expenditure really does bring benefits. That 28-day mortality for equivalent patients, following hospital admission for both nonvariceal and variceal upper gastrointestinal hemorrhage, has reduced by 2% and 3%, respectively, year on year in England over the period 1999 to 2007 is therefore of great importance. The demonstration that this can be shown through the analysis of routinely collected data may be of great value in the assessment of other conditions. When, as in this case, a study’s findings differ from the previous literature, we must ask whether this is because the

current or previous studies were in error or whether they are in reality observing different things. The data source chosen for our study Cyclin-dependent kinase 3 provides key advantages. The study is the largest to date of mortality after hospital admission for gastrointestinal hemorrhage and therefore has power to demonstrate trends that would be missed in smaller studies. It also has power to demonstrate variations in trends between subgroups of the population such as the smaller reduction in mortality in those over 80 years old with nonvariceal hemorrhage. The provision within the dataset of information on the previously suggested confounders of age and comorbidity is also of great benefit and has allowed us to clearly show and correct for this confounding.