Objective Rapid determination of acute coronary syndrome (ACS) in the emergency department (ED) is very important for patients presenting with ischemic symptoms. The aim of this study was to determine the predictive value of HEART score for ACS and significant coronary artery stenosis (SCS).
Methods We retrospectively analyzed data of patients who visited the ED with chest discomfort and were admitted to the cardiology department. Enrolled patients were classified into ACS and non-ACS groups according to their discharge diagnosis. Patients who underwent imaging were further divided into SCS and non-SCS groups according to study results. We compared age, sex, vital signs, risk factors, electrocardiogram, troponin, and HEART score for each group. For ACS and SCS predictive performance, the test characteristics of HEART score was calculated using sensitivity, specificity, predictive value, likelihood ratio, and receiver operating characteristic (ROC) curve analysis.
Results Of 207 patients, 112 had ACS. Among enrolled patients, 155 underwent imaging workup, of whom 67 had SCS. HEART score ≤3 had 93% sensitivity for ACS and 97% for SCS. HEART score ≥7 had 82% specificity for ACS and 83% for SCS. HEART score area under ROC curve for ACS was 0.706 (95% confidence interval, 0.627–0.776) and 0.737 (95% confidence interval, 0.660–0.804) for SCS.
Conclusion HEART score was a fair predictor of ACS and SCS in ED patients who presented with chest symptoms and were admitted to the cardiology department. The predictive power of HEART score was better for SCS than for ACS.
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Objective The quick sequential organ failure assessment (qSOFA) score, which includes mentation, systolic blood pressure, and respiratory rate, was developed to identify serious sepsis in out-of-hospital or emergency department (ED) settings. We evaluated the ability of the qSOFA score to predict poor outcome in South Korean ED patients with suspected infection.
Methods The qSOFA score was calculated for adult ED patients with suspected infection. Patients who received intravenous or oral antibiotics in the ED were considered to have infection. In-hospital mortality rate, admission rate, intensive care unit (ICU) admission rate, length of hospital stay (LOS), and lactate levels were compared between the qSOFA score groups. Receiver operating characteristic curves and area under the receiver operating characteristic curve values for in-hospital mortality were calculated according to qSOFA cut-off points and lactate levels.
Results Of 2,698 patients, in-hospital mortality occurred in 134 (5.0%). The mortality rate increased with increasing qSOFA score (2.2%, 6.4%, 17.5%, and 42.4% for qSOFA scores 0, 1, 2, and 3, respectively, P<0.001). The admission rate, ICU admission rate, LOS, and lactate level also increased with increasing qSOFA score (all P<0.001). The area under the receiver operating characteristic curve values for predicting in-hospital mortality associated with qSOFA score, lactate ≥2 mmol/L, and lactate ≥4 mmol/L were 0.719 (95% confidence interval [CI], 0.670 to 0.768), 0.657 (95% CI, 0.603 to 0.710), and 0.632 (95% CI, 0.571 to 0.693), respectively.
Conclusion Patients with a higher qSOFA score had higher admission, ICU admission, and in-hospital mortality rates, longer LOS, and higher lactate level. The qSOFA score showed better performance for predicting poor outcome than lactate level.
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Objective The aim of this study was to elucidate the epidemiology of pediatric patients transported by the National 119 Rescue Services in Korea.
Methods We enrolled all pediatric patients (<16 years old) who used the National 119 Rescue Services in Korea between January 2006 and December 2008, and analyzed the 119 ambulance patient care record databases.
Results The total number of the cases was 238,644 for 3 years. The median age was 6 years old and 59.0% were male, and the 2- to 5-year-old group was the largest (31.0%). The peak transport times were in the afternoon (from 12:00 p.m. to 17:59 p.m., 36.3%), on Saturday and Sunday (15.9% and 15.7%), and in summer (June to August, 27.3%). The ratio of disease versus injury as the cause of the transports was 42.3% vs. 57.7%. Among the 16 metropolitan cities and provinces, Gyeonggi (25.7%), Seoul (17.6%), and Incheon (7.0%) account for almost half of the all transported children. Regarding the annual transport rates per 100,000 children standardized by age, and gender to the Korean child population, Jeju was the largest (1,650.2) followed by Gangwon (1,201.3), and Jeonnam (1,178.1).
Conclusion This report presents comprehensive epidemiologic data of pediatric patients transported by 119 rescue services in Korea.
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