IJCS | Volume 32, Nº6, November / December 2019

597 Nicolao et al. Heart failure: morbidity and mortality Int J Cardiovasc Sci. 2019;32(6):596-604 Original Article patients were followed. This follow-up showed that the population affected by HF in the South region is older and the ischemic etiology predominates. 8 However, few studies have considered the morbidity and mortality due to HF in Rio Grande do Sul. This prevents a more comprehensive analysis of HF treatment and outcomes in that region. Nowadays, Rio Grande do Sul has large academic centers linked to hospital institutions, where publications related to the area of Cardiology are among the most published topics. In this perspective, identifying the scenario of morbidity and mortality due to HF over the last years justifies and aids the planning and monitoring of actions focused on the patient, in the context of initiatives that aims at health promotion and reduction of readmissions. Thus, the objective of this study was to assess the evolution of morbidity andmortality in adult HF patients in Brazil, specifically in the state of Rio Grande do Sul and its capital Porto Alegre. Method This is a serious retrospective analysis, performed using public domain data. The scenario of the study is composed of the database of the Brazilian Unified Health System’s ( Sistema Único de Saúde [SUS] ) Department of Informatics (DataSUS). The variables selected from the database were: regions (Brazil, Rio Grande do Sul and Porto Alegre), in-hospital morbidity (ICD-10 morbidity list, diseases of the circulatory system, heart failure (ICD-I50), mortality (proportional mortality), age range, average cost per admission, average length of stay and sex ratio. The ICD-10 included corresponds to the main Hospital Admission Authorization (AIH), in which the information on the reason for hospital admission is provided. The variables selected were collected from January 2007 to December 2016 and gathered in November 2017. Proportional mortality is the measure of importance of a specific cause of death in relation to all causes of death within the same population group. The temporality (2007 to 2016) was defined in virtue of the availability of the data on DATASUS. The use of data from 2007 was intentional because, in the previous 10 years, multiprofessional follow-up strategies were assessed and implemented in that region. With the exception of the variables age range and mortality, temporal delimitation occurred from January 2008 to December 2016 and January 2007 to December 2015, respectively, due to unavailability of the system consulted (DATASUS). The collection of these variables allowed for cross- checking of data, which were saved in the .csv format. Data analysis was temporal, through secondary data, which were organized in a new Microsoft Excel spreadsheet to enable descriptive statistics and graphical analysis. Because this study deals with secondary data published by the Brazilian Ministry of Health (MS), there was no need for submission to the Research Ethics Committee, but all ethical precepts were followed according to the Resolution 466/2012, of the National Health Council. 9 Results Data will be presented according with the variables analyzed, and the percentages of HF admissions will be shown, followed by length of stay, cost, mortality, age range and sex. All variables will be considered by time series in accordance with the three regions studied. Figure 1 shows the percentages of HF admissions from the total number of admissions due to diseases of the circulatory system.We can observe that, during the period investigated, there was a decrease in the percentages of admissions in the three regions. Moreover, we must highlight that the percentages for Porto Alegre are lower than those for RS and Brazil, where percentage change showed a decrease of 15%, 24% and 25%, respectively. Considering age range, patients in their seventies had more hospitalizations in Brazil and in RS. In Porto Alegre, on the other hand, higher hospitalization percentages were observed in patients in their sixties, as shown in Figure 2. When the sex ratio is calculated (males per 100 women), in which a ratio of 100 means there are equal numbers of males and females, if the ratio is above 100, it means there are more males than females; whereas a sex ratio below 100 indicates that there are more females than males. HF admission rates were higher among males, considering the data related to Brazil and Porto Alegre, where the sex ratio was of 117 males per 100 females admitted due to HF in 2016. On the other hand, in Rio Grande do Sul, there was a prevalence of women, with a ratio of 91 males per 100 females (Figure 3). The average length of stay due to HF in Brazil was 6.1 days in 2007, reaching 7.4 in 2016, a percentage change