Literature DB >> 18308008

Limitations of clinical history for evaluation of patients with acute chest pain, non-diagnostic electrocardiogram, and normal troponin.

Juan Sanchis1, Vicent Bodí, Julio Núñez, Xavier Bosch, Pablo Loma-Osorio, Luis Mainar, Enrique Santas, Gema Miñana, Rocío Robles, Angel Llàcer.   

Abstract

Decision making and risk stratification for patients with acute chest pain, nondiagnostic electrocardiogram results, and normal troponin levels are challenging. The aim of this study was to optimize the clinical history for the evaluation of these patients. A total of 1,011 patients presenting to an emergency department were included. The following data were collected: clinical presentation (pain characteristics and number of pain episodes), coronary risk factors, previous ischemic heart disease, and extracardiac vascular disease (peripheral artery disease, stroke, or creatinine >1.4 mg/dl). Two different predictive models were calculated according to the end points: model 1 for 1-year major events (death or myocardial infarction) and model 2 for 30-day cardiac events (major events or revascularization). For 1-year major events, model 1 showed optimal discrimination capacity (C statistic = 0.80), which was significantly better than that of model 2 (C statistic = 0.77, p = 0.04). With respect to 30-day cardiac events, however, discrimination was lower in the 2 models, without differences between them (C statistic = 0.74 vs 0.75, p = NS). Using model 1, a large low-risk subgroup with <3 predictive variables could be defined, including 442 patients (44% of the total population) with a 1.4% rate of 1-year major events; however, the incidence of 30-day cardiac events (8%) was not negligible, mainly because of revascularizations. In conclusion, in patients with acute chest pain of uncertain coronary origin, clinical predictive models afford good risk stratification for long-term major events. Short-term outcomes, including revascularization, however, are not predicted as well. Therefore, ancillary tools, such as noninvasive stress tests, should be implemented for decision making at initial hospitalization or discharge.

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Year:  2007        PMID: 18308008     DOI: 10.1016/j.amjcard.2007.10.024

Source DB:  PubMed          Journal:  Am J Cardiol        ISSN: 0002-9149            Impact factor:   2.778


  6 in total

Review 1.  Imaging techniques for the assessment of suspected acute coronary syndromes in the emergency department.

Authors:  Devang M Dave; Maros Ferencic; Udo Hoffmann; James E Udelson
Journal:  Curr Probl Cardiol       Date:  2014-05-05       Impact factor: 5.200

2.  Efficacy of coronary revascularization in patients with acute chest pain managed in a chest pain unit.

Authors:  Juan Sanchis; Vicent Bodí; Julio Núñez; Luis Mainar; Eduardo Núñez; Pilar Merlos; Eva Rúmiz; Gema Miñana; Xavier Bosch; Angel Llácer
Journal:  Mayo Clin Proc       Date:  2009-04       Impact factor: 7.616

3.  Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection.

Authors:  Nan Liu; Zhi Xiong Koh; Junyang Goh; Zhiping Lin; Benjamin Haaland; Boon Ping Ting; Marcus Eng Hock Ong
Journal:  BMC Med Inform Decis Mak       Date:  2014-08-23       Impact factor: 2.796

4.  Highly Sensitive Detection of Minimal Cardiac Ischemia using Positron Emission Tomography Imaging of Activated Platelets.

Authors:  Melanie Ziegler; Karen Alt; Brett M Paterson; Peter Kanellakis; Alex Bobik; Paul S Donnelly; Christoph E Hagemeyer; Karlheinz Peter
Journal:  Sci Rep       Date:  2016-12-02       Impact factor: 4.379

Review 5.  Pitfalls in Electrocardiographic Diagnosis of Acute Coronary Syndrome in Low-Risk Chest Pain.

Authors:  Semhar Z Tewelde; Amal Mattu; William J Brady
Journal:  West J Emerg Med       Date:  2017-04-17

6.  A novel cardiovascular risk stratification model incorporating ECG and heart rate variability for patients presenting to the emergency department with chest pain.

Authors:  Micah Liam Arthur Heldeweg; Nan Liu; Zhi Xiong Koh; Stephanie Fook-Chong; Weng Kit Lye; Mark Harms; Marcus Eng Hock Ong
Journal:  Crit Care       Date:  2016-06-11       Impact factor: 9.097

  6 in total

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