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OBJECTIVE Patients with suspicion of acute coronary syndrome (ACS) are difficult to diagnose and they represent a very heterogeneous group. Some require immediate treatment while others, with only minor disorders, may be sent home. Detecting ACS patients using a machine learning approach would be advantageous in many situations. METHODS AND MATERIALS(More)
BACKGROUND Chest pain is one of the most common complaints in the Emergency Department (ED), but the cost of ED chest pain patients is unclear. The aim of this study was to describe the direct hospital costs for unselected chest pain patients attending the emergency department (ED). METHODS 1,000 consecutive ED visits of patients with chest pain were(More)
BACKGROUND Several models for prediction of acute coronary syndrome (ACS) among chest pain patients in the emergency department (ED) have been presented, but many models predict only the likelihood of acute myocardial infarction, or include a large number of variables, which make them less than optimal for implementation at a busy ED. We report here a(More)
BACKGROUND Assessment and treatment of the acutely ill patient have improved by introducing systematic assessment and accelerated protocols for specific patient groups. Triage systems are widely used, but few studies have investigated the ability of the triage systems in predicting outcome in the unselected acute population. The aim of this study was to(More)
Artificial neural network (ANN) ensembles have long suffered from a lack of interpretability. This has severely limited the practical usability of ANNs in settings where an erroneous decision can be disastrous. Several attempts have been made to alleviate this problem. Many of them are based on decomposing the decision boundary of the ANN into a set of(More)
This paper aims to identify and review new and unproven emergency department (ED) methods for improved evaluation in cases of suspected acute coronary syndrome (ACS). Systematic news coverage through PubMed from 2000 to 2006 identified papers on new methods for ED assessment of patients with suspected ACS. Articles found described decision support models,(More)
BACKGROUND Evaluation of emergency department (ED) performance remains a difficult task due to the lack of consensus on performance measures that reflects high quality, efficiency, and sustainability. AIM To describe, map, and critically evaluate which performance measures that the published literature regard as being most relevant in assessing overall ED(More)
INTRODUCTION The aim of this study was to compare different methods to predict acute coronary syndrome (ACS) using only data from a single electrocardiogram (ECG) in the emergency department (ED). METHOD We compared the ACS prediction abilities of classical ECG criteria, human expert ECG interpretation, a logistic regression model and an artificial neural(More)
BACKGROUND Pre-hospital electrocardiogram (ECG) transmission to an expert for interpretation and triage reduces time to acute percutaneous coronary intervention (PCI) in patients with ST elevation Myocardial Infarction (STEMI). In order to detect all STEMI patients, the ECG should be transmitted in all cases of suspected acute cardiac ischemia. The aim of(More)
BACKGROUND The prognostic value of blood lactate as a predictor of adverse outcome in the acutely ill patient is unclear. The aim of this study was to investigate if a peripheral venous lactate measurement, taken at admission, is associated with in-hospital mortality in acutely ill patients with all diagnosis. Furthermore, we wanted to investigate if the(More)