Journal of cardiac failure
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Observational Study
Electrocardiographic Findings in Coronavirus Disease-19: Insights on Mortality and Underlying Myocardial Processes.
Coronavirus disease 2019 (COVID-19) is a respiratory syndrome with high rates of mortality, and there is a need for easily obtainable markers to provide prognostic information. We sought to determine whether the electrocardiogram (ECG) on hospital presentation provides prognostic information, specifically related to death. ⋯ We found that patients with ECG findings of both left-sided heart disease (atrial premature contractions, intraventricular block, repolarization abnormalities) and right-sided disease (right bundle branch block) have higher odds of death. ST elevation at presentation was rare.
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Surveillance and outcome studies for heart failure (HF) require accurate identification of patients with HF. Algorithms based on International Classification of Diseases (ICD) codes to identify HF from administrative data are inadequate owing to their relatively low sensitivity. Detailed clinical information from electronic medical records (EMRs) is potentially useful for improving ICD algorithms. This study aimed to enhance the ICD algorithm for HF definition by incorporating comprehensive information from EMRs. ⋯ Applying natural language processing and machine learning on the discharge summaries of inpatient EMR data can improve the capture of cases of HF compared with the widely used ICD algorithm. The utility of the HFC algorithm is straightforward, making it easily applied for HF case identification.