Abstract P479: Feasibility Study to Compare Heart Failure Risk Prediction Tools in the Emergency Department

Background: In United States (US) emergency departments (ED), ~80% of patients presenting with exacerbation of heart failure (HF) symptoms are admitted to the hospital. However, some patients are at low-risk of adverse outcomes and might be effectively managed as outpatients. While ED HF risk prediction tools guide admission or discharge decisions, they have not been compared, are not routinely used in EDs, and do not include patient-reported outcomes that may be associated with prognosis. Objective: To assess the feasibility of collecting variables for three published ED-based HF risk prediction tools (table) and the capacity to collect participant-reported outcomes. Methods: We screened a convenience sample of patients age ≥20 years with symptoms of HF (e.g. shortness of breath, edema) receiving care in a US ED. We collected information from medical records, and administered a questionnaire to collect patient-reported outcomes and a 3-minute walking test. We developed a safety protocol to identify participants ineligible for the walking test. Results: We screened 66 patients and consented 31 (47%) participants. The average age was 61 years, 6 (19.4%) were female and 28 (90.3%) were admitted. We completed all the questionnaires with an average time of 31 minutes. For the walking test, 15 were ineligible per the safety protocol, 6 completed the test, and 10 did not consent. For the three HF tools, we collected an average of 93.4% of the variables needed per participant (range across tools 91.4%-97.7%; Table). The main missing variables were BMI on ED arrival (n=23) and troponin (due to hemolyzed values, n=5). Conclusion: We obtained complete data for the participant questionnaires, yet there were missing values for variables needed for the HF tools. The Emergency Heart Failure Mortality Risk Grade tool had the most complete data. If a research or clinical study plans to use these tools, the study protocol should include BMI and troponin measurements and consider alternative strategies to collect data, such as by self-report.