The demographic-epidemiological study of a disease allows for a more accurate characterization of situations involving the care of this pathology and a better distribution of resources, often scarce, thereby optimizing patient care. In a scenario of general lack of financial, technological, and professional resources, it is necessary to develop a program that addresses all processes, streamlining the care network flow and,m consequently, that produces a positive impact on the outcome. Continuous reassessment of methods and criteria are necessary in order to evaluate the need for the reorganization and redirection of resources.

When treating congenital heart disease (CHD), the estimated prevalence may seem insignificant, when compared to other more prevalent cardiac pathologies, such as coronary artery disease. In Brazil, a prevalence of 12:1,000 live births with CHD has been estimated, corresponding to 25,757 new cases per year. These were responsible for 6% of all deaths in children < 1 year of age, according to data from Pinto Jr., Salim et al., observed that the main cause of death in young people under 20 years of age between 2000 and 2015 was circulatory system malformation. The clinical presentation of diseases is extremely variable, with symptoms that can start from the fetal period to adulthood and the correct diagnosis at an appropriate time is a determining factor for better therapeutic management and success. Lopes et al. demonstrated a lethality of 64.7% for critical CHD, which proved to be higher during the neonatal period. However, data on mortality must be interpreted in the context of available medical care in the studied region.

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Congenital Heart Disease (CHD) comprises any change in the anatomy of the heart and its blood vessels. The incidence of CHD is 8 to 10 per 1,000 live births, that is or one in one hundred births. In Brazil, 28,900 children are born with CHD per year (1% of the total births), of which about 80% (23,800) require cardiac surgery, and half of them, within the first year of life. Congenital malformations represent the second main cause of mortality in children under one year of age. CHD is the most frequent and the one with the highest mortality in the first year of life in Brazil, and the second cause of death in up to 30 days of life. Congenital heart disease manifestations are very variable and may occur soon after birth or appear later in childhood or adolescence.

Brazil is a continental country, where the diversity observed both in the diagnosis and in treatment of congenital heart diseases is very large among the macro-regions. It is a fact that there has been a gradual improvement in diagnosis, after the more active dissemination of the oximetry test, with technological advances and the diffusion of echocardiography throughout the country, even so a low survival rate is still observed in the neonatal period. Lopes et al. demonstrated a lethality of 64.7% for critical congenital heart disease and a 28-day survival rate reduced by almost 70% in these newborns, signaling a great need for investment in assistive technology and trained professionals for this among this population.

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It is a current research method to evaluate the outcome of diseases over decades, mainly in most prevalent diseases such as myocardial infarction, a public health issue with a significant toll in morbidity and mortality of the population. In addition to evolving over time, local conditions may also contribute to differences in outcome, mainly in countries with continental dimensions as Brazil is, as well as with large populations (206.081.432 habitants in 2016; 210.147.125 habitants in 2019). Other epidemiologic variables, such as age, sex, access to treatment, co-morbidities, etc. – are part of the continuous spectrum of health care and risk factors for cardiovascular diseases.

In the current study authors evaluated mortality data from a National Database System on Mortality in five geographic Brazilian regions between 1996 and 2016. Researchers corrected obtained from death certificates adjusting for: a) ill defined causes of death; b) codes-garbage without meaning for a causality study; c) correction for under registry or notification. The analysis was made in time series with segmented linear regression.

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