Practical application of the ATOM study: Treatment efficacy of antihypertensive drugs in monotherapy or combination (ATOM metaanalysis according to PRISMA statement); tables for the use of antihypertensive drugs in monotherapy or combination.

BACKGROUND: The response to antihypertensive drugs is predictable. The absence of precise prescription recommendations to treat arterial hypertension (HT) lead to use drugs unable to reduce blood pressure (BP) to target values.We published ATOM study, in which we found significant differences in the ability to reduce BP between the different drugs.The objective of the study was to determine the expected decrease in blood pressure with the use of commercialized doses of the drugs commonly used in the treatment of HT in clinical practice, to avoid the use of drugs or combinations that even with the best response, are unable to obtain the necessary BP decrease to reach the goal. METHODS: The analysis was based on the results of the ATOM study. To convert the mean doses of the different drugs and combinations in commercialized doses, the conclusions of the study by Law et al have been applied. RESULTS: Based on the results, two tables were drawn, one for systolic BP and the other for diastolic BP, where the doses of the different drugs and combinations are classified according to the BP decrease that can be expected from them. In order to favor the use of the tables in clinical practice, the different drugs have been grouped in intervals of 10 millimeters of mercury (mmHg) for the decrease of the systolic BP and of 5 mmHg for the diastolic BP. CONCLUSIONS: Recommendations for the use of antihypertensive treatments should not be limited to pharmacological families. They should also consider differences between drugs or specific combinations. From the data of the ATOM study we have implemented tables that express the effect of the drugs commonly used in clinical practice and that should allow the clinicians to choose with care the treatment to use.

The association between exposure to environmental factors and the occurrence of attention-deficit/hyperactivity disorder (ADHD). A population-based retrospective cohort study.

BACKGROUND: A number of factors contribute to attention deficit hyperactivity disorder (ADHD) and although they are not fully known, the occurrence of ADHD seems to be a consequence of an interaction between multiple genetic and environmental factors. However, apart from pesticides, the evidence is inadequate and inconsistent as it differs not only in the population and time period analysed, but also in the type of study, the control of the confounding variables and the statistical methods used. In the latter case, the studies also differ in the adjustment of spatial and temporal variability. Our objective here, is to provide evidence on an association between environmental factors and ADHD. METHODS: In our study, we used a population-based retrospective cohort in which we matched cases and controls (children free of the disease) by sex and year of birth (n = 5193, 78.9% boys). The cases were children born between 1998 and 2012 and diagnosed with ADHD (n = 116). To evaluate whether there was a geographical pattern in the incidence of ADHD, we first represented the smoothed standardized incidence rates on a map of the region being studied. We then estimated the probability of being a case by using a generalized liner mixed model with a binomial link. As explanatory variables of interest, we included the following environmental variables: distance to agricultural areas, distance to roads (stratified into three categories according to traffic density and intensity), distance to petrol stations, distance to industrial estates, and land use. We control for both observed (individual and family specific variables and deprivation index) and unobserved confounders (in particular, individual and familial heterogeneity). In addition, we adjusted for spatial extra variability. RESULTS: We found a north-south pattern containing two clusters (one in the centre of the study region and another in the south) in relation to the risk of developing ADHD. The results from the multivariate model suggest that these clusters could be related to some of the environmental variables. Specifically, living within 100 m from an agricultural area or a residential street and/or living fewer than 300 m from a motorway, dual carriageway or one of the industrial estates analysed was associated (statistically significant) with an increased risk of ADHD. CONCLUSION: Our results indicate that some environmental factors could be associated with ADHD occurring, particularly those associated with exposure to pesticides, organochlorine compounds and air pollutants because of traffic.