Article

Diagnostic accuracy of clinical prediction rules to exclude acute coronary syndrome in the emergency department setting: A systematic review

Department of Emergency Medicine, University of Ottawa, Ottawa, Ontario.
Canadian Journal of Emergency Medicine (Impact Factor: 1.16). 07/2008; 10(4):373-82.
Source: PubMed

ABSTRACT

We sought to determine the diagnostic accuracy of clinical prediction rules to exclude acute coronary syndrome (ACS) in the emergency department (ED) setting.
We searched MEDLINE, EMBASE, Web of Science and the Cochrane Database of Systematic Reviews. We contacted content experts to identify additional articles for review. Reference lists of included studies were hand searched. We selected articles for review based on the following criteria: 1) enrolled consecutive ED patients; 2) incorporated variables from the history or physical examination, electrocardiogram and cardiac biomarkers; 3) did not incorporate cardiac stress testing or coronary angiography into prediction rule; 4) based on original research; 5) prospectively derived or validated; 6) did not require use of a computer; and 7) reported sufficient data to construct a 2 x 2 contingency table. We assessed study quality and extracted data independently and in duplicate using a standardized data extraction form.
Eight studies met inclusion criteria, encompassing 7937 patients. None of the studies verified the prediction rule with a reference standard on all or a random sample of patients. Six studies did not report blinding prediction rule assessors to reference standard results, and vice versa. Three prediction rules were prospectively validated. Sensitivities and specificities ranged from 94% to 100% and 13% to 57%, and positive and negative likelihood ratios from 1.1 to 2.2 and 0.01 to 0.17, respectively.
Current prediction rules for ACS have substantial methodological limitations and have not been successfully implemented in the clinical setting. Future methodologically sound studies are needed to guide clinical practice.

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    • "CVD: Clinical vascular disease Note that probabilities are rounded to 0 decimal places, so a probability of 0 % does not imply impossibility(Based on the tool by Björk et al.[33]) Note: Estimations for patients without congestive heart failure, previous myocardial infarction, previous CABG or signs of acute coronary syndrome in the ECG HTN Hypertension, AP pectoris within previous month, Cd Chest discomfort at arrival to hospital have an effect on the external validity of each individual one. Previous systematic reviews on the value of the clinical assessment of patients with suspected CAD have focused on studies based in Emergency departments[17,24,43], have reported the prognostic value of individual signs and symptoms[13,14,23], or include predictors not available on clinical history or examination, such as biomarkers[17,18]. However, clinicians working in primary and secondary care base their decisions on combinations of signs and symptoms and in many cases are not supported by laboratory or radiology tests. "
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    ABSTRACT: Background The clinical assessment of patients with chest pain of recent onset remains difficult. This study presents a critical review of clinical predictive tools for the assessment of patients with chest pain. Methods Systematic review of observational studies and estimation of probabilities of coronary artery disease (CAD) in patients with chest pain. Searches were conducted in PubMed, Embase, Scopus, and Web of Science to identify studies reporting tools, with at least three variables from clinical history, physical examination or ECG, produced with multivariate analysis, to estimate probabilities of CAD in patients with chest pain of recent onset, published from inception of the database to the 31st July 2015. The references of previous relevant reviews were hand searched. The methodological quality was assessed with standard criteria. Since the incidence of CAD has changed in the past few decades, the date of publication was acknowledged to be relevant in order to use the tool in clinical practice, and more recent papers were considered more relevant. Probabilities of CAD according to the studies of highest quality were estimated and the evidence provided was graded. Results Twelve papers were included out of the 19126 references initially identified. The methodological quality of all of them was high. The clinical characteristics of the chest pain, age, past medical history of cardiovascular disease, gender, and abnormalities in the ECG were the predictors of CAD most commonly reported across the studies. The most recent papers, with highest methodological quality, and most practical for use in clinical settings, reported prediction or exclusion of CAD with area under the curve 0.90 in Primary Care, 0.91 in Emergency department, and 0.79 in Cardiology. These papers provide evidence of high level (1B) and the recommendation to use their results in the management of patients with chest pain is strong (A). Conclusions The risk of CAD can be estimated on clinical grounds in patients with chest pain in different clinical settings with high accuracy. The estimation of probabilities of CAD presented in these studies could be used for a better management of patients with chest pain and also in the development of future predictive tools.
    Full-text · Article · Dec 2016 · BMC Cardiovascular Disorders
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    • "However, experts agree that it is very difficult to get the risk of missed ACS below 1%, and, pending malpractice reform, most emergency physicians in the United States are unwilling to accept even a 1% miss rate [24]. Despite showing a correlation with the risk of ACS and adverse outcome, none of these risk stratification systems have gained widespread acceptance in clinical practice [25]. Preliminary results of a prospective validation of the HEART score were reported at the 2010 Congress of the European Society of Cardiology [26]. "
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    ABSTRACT: Background: Studies have individually reported the relationship of age, cardiac risk factors, and history of preexisting coronary artery disease (CAD) for predicting acute coronary syndromes in chest pain patients undergoing cardiac stress testing. In this study, we investigate the interplay of all these factors on the incidence of acute coronary syndromes to develop a tool that may assist physicians in the selection of appropriate chest pain patients for stress testing. Methods: Retrospective analysis of a prospectively acquired database of consecutive chest pain patients undergoing nuclear stress testing. Backward stepwise logistic regression was used to develop a model for predicting risk of 30-day acute coronary events (ACE) using information obtained from age, sex, cardiac risk factors, and history of preexisting CAD. Results: A total of 800 chest pain patients underwent nuclear stress testing. ACE occurred in 74 patients (9.3%). Logistic regression analysis found only 6 factors predictive of ACE: age, male sex, preexisting CAD, diabetes, and hyperlipidemia. Area under the receiver operator characteristic curve of this model for predicting ACE was 0.767 (95% confidence interval, 0.719-0.815). There were no cases of ACE in the 173 patients with predicted probability estimates ≤2.5% (95% confidence interval, 0%-2.1%). Conclusions: A regression model using age, sex, preexisting CAD, diabetes, and hyperlipidemia is predictive of 30-day ACE in chest pain patients undergoing nuclear stress testing. Prospective studies need to be performed to determine whether this model can assist physicians in the selection of appropriate low-to-intermediate risk chest pain patients for nuclear stress testing.
    Full-text · Article · Dec 2012 · Critical pathways in cardiology
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    • "However, experts agree that it is very difficult to get the risk of missed ACS below 1%, and, pending malpractice reform, most emergency physicians in the United States are unwilling to accept even a 1% miss rate [24]. Despite showing a correlation with the risk of ACS and adverse outcome, none of these risk stratification systems have gained widespread acceptance in clinical practice [25]. Preliminary results of a prospective validation of the HEART score were reported at the 2010 Congress of the European Society of Cardiology [26]. "
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    ABSTRACT: BACKGROUND: The HEART score uses elements from patient History, Electrocardiogram, Age, Risk Factors, and Troponin to obtain a risk score on a 0- to 10-point scale for predicting acute coronary syndromes (ACS). This investigation seeks to improve on the HEART score by proposing the HEARTS(3) score, which uses likelihood ratio analysis to give appropriate weight to the individual elements of the HEART score as well as incorporating 3 additional "S" variables: Sex, Serial 2-hour electrocardiogram, and Serial 2-hour delta troponin during the initial emergency department valuation. METHODS: This is a retrospective analysis of a prospectively acquired database consisting of 2148 consecutive patients with non-ST-segment elevation chest pain. Interval analysis of likelihood ratios was performed to determine appropriate weighting of the individual elements of the HEART(3) score. Primary outcomes were 30-day ACS and myocardial infarction. RESULTS: There were 315 patients with 30-day ACS and 1833 patients without ACS. Likelihood ratio analysis revealed significant discrepancies in weight of the 5 individual elements shared by the HEART and HEARTS(3) score. The HEARTS(3) score outperformed the HEART score as determined by comparison of areas under the receiver operating characteristic curve for myocardial infarction (0.958 vs 0.825; 95% confidence interval difference in areas, 0.105-0.161) and for 30-day ACS (0.901 vs 0.813; 95% confidence interval difference in areas, 0.064-0.110). CONCLUSION: The HEARTS(3) score reliably risk stratifies patients with chest pain for 30-day ACS. Prospective studies need to be performed to determine if implementation of this score as a decision support tool can guide treatment and disposition decisions in the management of patients with chest pain.
    Full-text · Article · May 2012 · The American journal of emergency medicine
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