Abstract 258: Incidence and Predictors of Cardiac Arrest in Cerebrovascular Diseases

Abstract

Background and purpose: Large scale studies of cardiac arrest in hospitalized patients with cerebrovascular accident (CVA) are lacking. We sought to describe the incidence, demographics and hospital characteristics of cardiac arrest in CVA. Additionally, we aimed to indentify predictors of cardiac arrest in patients with CVA. Methods: We analyzed the data from the Nationwide Inpatient Sample (NIS) of Healthcare Cost and Utilization Project for years 2005-2009. NIS is a discharge level 20% stratified sample of all non-federal hospitals in the US. We used International Classification of Diseases-9 (ICD-9) codes to select cases of CVA. Comparisons were made by using χ2 and student-t tests. Multivariate logistic regression was used to identify independent predictors of cardiac arrest. Results: We included 672,161 cases of CVA [ischemic stroke: 58.2%, transient ischemic attack (TIA):28.2%, intracerebral hemorrhage (ICH): 9.7%, and subarachnoid hemorrhage (SAH): 3.9%] in our analysis. Of these, 3,154 (0.467%) also had cardiac arrest. Compared to ischemic stroke (0.413%), incidence of cardiac arrest was higher in ICH (1.221%) and SAH (2.523%) and was lower in TIA (0.038%). Patients with cardiac arrest were younger (mean age±SD: 67.8±16.4 vs. 70.5±15.7 years, p<0.001) and were less likely of female gender (51.8% vs. 55.7%, p<0.001). There was a significant difference in the incidence of cardiac arrest between various ethnic groups (Caucasian: 0.415% vs. African-American: 0.563% vs. Hispanic: 0.633% vs. Asian/Pacific Islander: 0.722%, p<0.001). Compared to the rest, patients in lowest income quartile had higher incidence of cardiac arrest (0.526% vs. 0.437%, p<0.001). Significant differences based on the hospital characteristics were as follows: 1. Bedsize: small (0.349%) vs. medium (0.443%) vs. large (0.498%), p<0.001; 2. Location: rural (0.354%) vs. urban (0.485%), p<0.001; 3. Academic status: teaching (0.553%) vs. non-teaching (0.403%), p<0.001; and 4. Region: northeast (0.399%) vs. midwest (0.403%) vs. south (0.489%) vs. west (0.553%), p<0.001. In multivariate analysis, factors associated with cardiac arrest are shown in the table. Conclusion: This is one of the largest studies to describe the predictors of cardiac arrest in CVA. The patients with ICH and SAH are at significantly higher risk of cardiac arrest. The association of hospital characteristics and the incidence of cardiac arrest warrants further exploration into the contributing factors. The patients with higher risk profile as per the predictor model should warrant closer monitoring.