Biological Database for genomic and clinical data to support decision making processes in the treatment of patients with cardiac insufficiency.

Studies that make use of electronic medical data recording and genomic information are becoming increasingly popular. This novel research field allows studying how genetic variability influences the susceptibility to chronic diseases and can ultimately lead to an improvement of the patient�s treatment.

Nowadays, it has become clear to the scientific community that these new strategies play an essential role in the prevention and treatment of chronic diseases, such as cardiac insufficiency. The peculiar epidemiological conditions described for Latin America, in comparison to other regions, pose the need for more detailed studies.

Having in mind this scenario, the specific goal of this project is to develop a database containing biological data of about 2000 patients suffering cardiac insufficiency. These patients are to be treated in a highly specialized cardiologic hospital, with electronically recorded data and biological sampling suitable for carrying out genomic association studies. These studies will allow developing and validating medical decision-making routines that aim to improve the clinical course of patients.

Methodology

Patients between 18 and 80 years with a diagnosis for cardiac insufficiency with different etiology and with left ventricular ejection fraction lower than 50% for the last two years will be included in the study. After written consent, a study of the general clinical condition of the patient will be performed, including an echocardiography and biochemical examinations. The collected data will be recorded and managed using electronic tools for data capturing. The patients will be followed during 6 months in order to evaluate the eventual evolution of cardiovascular pathologies. Parameters to be assessed are mortality, mortality due to cardiovascular complications, hospitalization due to worsen cardiac insufficiency and a register of drugs being currently taken. The initial analytic strategy will concentrate on the evaluating the accuracy of information extraction protocols on identifying the leading factors for the prediction of morbidity and mortality caused by cardiac insufficiency, extracted from the constructed database.

Impact

The adequate large-scale usage of genomic data, associated to electronically record medical data should accelerate the discovery of genetic factors associated to complex diseases, such as cardiac insufficiency. This methodology should also support the creation of routines to support medical procedures and assistance in cardiology departments of hospitals.