A simple statistical model for prediction of acute coronary syndrome in chest pain patients in the emergency department

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 simple statistical model for ACS prediction that could be used in routine care at a busy ED. METHODS: Multivariable analysis and logistic regression were used on data from 634 ED visits for chest pain. Only data immediately available at patient presentation were used. To make ACS prediction stable and the model useful for personnel inexperienced in electrocardiogram (ECG) reading, simple ECG data suitable for computerized reading were included. RESULTS: Besides ECG, eight variables were found to be important for ACS prediction, and included in the model: age, chest discomfort at presentation, symptom duration and previous hypertension, angina pectoris, AMI, congestive heart failure or PCI/CABG. At an ACS prevalence of 21% and a set sensitivity of 95%, the negative predictive value of the model was 96%. CONCLUSION: The present prediction model, combined with the clinical judgment of ED personnel, could be useful for the early discharge of chest pain patients in populations with a low prevalence of ACS

Ruling out coronary heart disease in primary care patients with chest pain: a clinical prediction score

Chest pain raises concern for the possibility of coronary heart disease. Scoring methods have been developed to identify coronary heart disease in emergency settings, but not in primary care. Data were collected from a multicenter Swiss clinical cohort study including 672 consecutive patients with chest pain, who had visited one of 59 family practitioners' offices. Using delayed diagnosis we derived a prediction rule to rule out coronary heart disease by means of a logistic regression model. Known cardiovascular risk factors, pain characteristics, and physical signs associated with coronary heart disease were explored to develop a clinical score. Patients diagnosed with angina or acute myocardial infarction within the year following their initial visit comprised the coronary heart disease group. The coronary heart disease score was derived from eight variables: age, gender, duration of chest pain from 1 to 60 minutes, substernal chest pain location, pain increasing with exertion, absence of tenderness point at palpation, cardiovascular risks factors, and personal history of cardiovascular disease. Area under the receiver operating characteristics curve was of 0.95 with a 95% confidence interval of 0.92; 0.97. From this score, 413 patients were considered as low risk for values of percentile 5 of the coronary heart disease patients. Internal validity was confirmed by bootstrapping. External validation using data from a German cohort (Marburg, n = 774) revealed a receiver operating characteristics curve of 0.75 (95% confidence interval, 0.72; 0.81) with a sensitivity of 85.6% and a specificity of 47.2%. This score, based only on history and physical examination, is a complementary tool for ruling out coronary heart disease in primary care patients complaining of chest pain

Scoping Review on Use of Drugs Targeting Interleukin 1 Pathway in DIRA and DITRA

Deficiencies in interleukin (IL)-1 receptor (IL-R) antagonist (DIRA) and IL-36R antagonist (DITRA) are rare genetic autoinflammatory diseases related to alterations in antagonists of the IL-1 pathway. IL-1 antagonists may represent therapeutic alternatives. Here, we aim to provide a scoping review of knowledge on use of IL-1-targeting drugs in DIRA and DITRA. An a priori protocol was published, and the study was conducted using the methodology described in the Joanna Briggs Institute Reviewer's Manual and the recently published PRISMA Extension for Scoping Review statement. A three-step search using MEDLINE and EMBASE databases until March 2018 with additional hand searching was performed. Data charting was performed. The search, article selection, and data extraction were carried out by two researchers independently. Twenty-four studies on use of anti-IL-1 drugs were included [15 studies including patients with diagnosis of DIRA (n = 19) and 9 studies including patients with diagnosis of DITRA (n = 9)]. Most studies followed a multicenter observational design. Among all patients who received treatment with anti-IL-1 drugs, nine and four mutations in IL1RN and IL36RN were found, respectively. Patients with DIRA were treated with anakinra (n = 17), canakinumab (n = 2), or rinolacept (n = 6). All patients with DITRA were treated with anakinra, and only one case was also treated with canakinumab. Time-to-response frequencies were evaluated as immediate, short, and medium-long term for DIRA (17/17, 15/17, and 9/10, respectively) and DITRA (7/9, 3/9, and 2/9, respectively). Most DITRA patients in whom anti-IL-1 treatment failed experienced good response to anti-tumor necrosis factor alpha or anti-IL-12/23 drugs. The safety profiles of treatments were similar in both diseases. Evidence on use of anti-IL-1 drugs in DIRA and DITRA is scarce and based on observational studies. Larger studies with better methodological quality are needed to increase confidence in use of these drugs in patients with DIRA and DITRA