Electronic Medical Records and Genomics
This trial is active, not recruiting.
|Sponsor||University of Sao Paulo General Hospital|
|Collaborator||Ministry of Health, Brazil|
|Start date||August 2012|
|End date||July 2015|
|Trial size||700 participants|
|Trial identifier||NCT02043431, EMR-01|
The purpose of this study is to develop a biobank containing samples of 2,000 patients treated in a tertiary cardiology hospital containing electronic medical records and genetic data in genome-wide scale for performing genetic association studies for validation and development of medical decision routines that help the clinical management of heart failure patients.
all cause mortality
time frame: six month
time frame: six month
Male or female participants from 18 years up to 80 years old.
Inclusion Criteria: - Age between 18 and 80 years old - Heart failure diagnosis of different etiologies - Left ventricular ejection fraction < 50% in the past 2 years Exclusion Criteria: - Patients with impaired cognition due to advanced dementia syndrome or severe psychiatric disorder - Patients without telephone access - Patients that refused to participate
|Official title||Genetic and Electronic Medical Records to Predict Outcomes in Heart Failure Patients|
|Principal investigator||Alexandre C Pereira, MD, PhD|
|Description||Patients between 18 and 80 years old with heart failure diagnosis of different etiologies and left ventricular ejection fraction < 50% in the past 2 years will be eligible for enrollment on the cohort. After consent, patients will be submitted to clinical baseline, echocardiographic, cardiography impedance and biochemical evaluation. Study data will be collected and managed using Research Electronic Data Capture (REDCap) tools. The follow up will take place every 6 months to assess cardiovascular outcomes (all-cause mortality, cardiovascular mortality, hospitalization for worsening heart failure and current medication use). Initial analytical strategy will focus on the establishment of the accuracy of electronic medical records extraction protocols for main predictor factors of morbidity and mortality in heart failure.|
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