Abstract 223: Patients With Cardiac Comorbidities Carry Worse Outcome as Identified by Our SELF Risk Stratification Pathway: An ACAP-SELF Syncope Dataset Analysis

Autor: Balaji Pratap, Joseph Bastawrose, Chaithanya K Pamidimukala, Dipen Patel, Prachi Kalamkar, Archana Lingannan, Narmadha Panneerselvam, Adilaxmi Gurram, Suketu Patel, Matthew Pierce, Himagna Ghosh, Eyal Herzog, Emad Aziz
Rok vydání: 2014
Předmět:
Zdroj: Circulation: Cardiovascular Quality and Outcomes. 7
ISSN: 1941-7705
1941-7713
Popis: Background: According to the design of published and validated SELF pathway, patients with syncope are stratified according to the SELF-1 criteria (Short period, Early-rapid onset, Loss of consciousness, Full recovery) and SELF-2 Criteria (Structural heart disease, abnormal electrocardiogram, and arrhythmia/AFib/AFl). Methods: 3044 patients were prospectively followed after presenting to our emergency department for the evaluation of syncope. Patients were divided into four groups: Group A (SELF +/+) who met both SELF-1 and 2 criteria, Group B (SELF +/-) who met SELF-1 criteria but not SELF-2, Group C (SELF -/+) who met SELF-2 criteria but not SELF-1 and Group D (SELF -/-) who met neither SELF criteria. The primary endpoint was a composite of readmission for syncope, myocardial infarction (MI), stroke or death. Follow-up was 5 years. Results: Group A included 1001 patients (33%), Group B included 359 patients (12%), Group C had 880 patients (29%) and Group D had 804 patients (26%). Patients who met SELF-2 criteria, i.e., patients in Groups A and C, had significantly worse outcome (Group A: HR 1.85; 95% CI: 1.47-2.36; p Conclusions: Using the SELF-pathway for patients presenting with syncope effectively identifies high risk patients who merit hospitalization and close follow-up post-discharge. These include patients with structural heart disease, abnormal EKG and abnormal telemetry, as well as patients with diabetes, CAD and CHF. This has important implications for the evaluation of a common disease that poses a significant economic burden on healthcare systems.
Databáze: OpenAIRE
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