Emergency physician high pretest probability for acute coronary syndrome correlates with adverse cardiovascular outcomes.


OBJECTIVES: The value of unstructured physician estimate of risk for disease processes, other than acute coronary syndrome (ACS), has been demonstrated. The authors sought to evaluate the predictive value of unstructured physician estimate of risk for ACS in emergency department (ED) patients without obvious initial evidence of a cardiac event. METHODS: This was a post hoc secondary analysis of the Internet Tracking Registry for Acute Coronary Syndromes (i*trACS), a prospectively collected multicenter data registry of patients over the age of 18 years presenting to the ED with symptoms of ACS between 1999 and 2001. In this registry, following patient history, physical exam, and electrocardiogram (ECG), the unstructured treating physician estimate of risk was recorded. A 30-day follow-up and a medical record review were used to determine rates of adverse cardiac events, death, myocardial infarction (MI), or revascularization procedure. The analysis included all patients with nondiagnostic ECG changes, normal initial biomarkers, and a non-MI initial impression from the registry and excluded those without complete data or who were lost to follow-up. Data were stratified by unstructured physician risk estimate: noncardiac, low risk, high risk, or unstable angina. RESULTS: Of 15,608 unique patients in the registry, 10,145 met inclusion/exclusion criteria. Patients were defined as having unstable angina in 6.0% of cases; high risk, 23.5% of cases; low risk, 44.2%; and noncardiac, 26.3% of cases. Adverse cardiac event rates had an inverse relationship, decreasing from 22.0% (95% confidence interval [CI] = 18.8% to 25.6%) for unstable angina, 10.2% (95% CI = 9.0% to 11.5%) for those stratified as high risk, 2.2% (95% CI = 1.8% to 2.6%) for low risk, and to 1.8% (95% CI = 1.4% to 2.4%) for noncardiac. The relative risk (RR) of an adverse cardiac event for those with an initial label of unstable angina compared to those with a low-risk designation was 10.2 (95% CI = 8.0 to 13.0). The RR of an event for those with a high-risk initial impression compared to those with a low-risk initial impression was 4.7 (95% CI = 3.8 to 5.9). The risk of an event among those with a low-risk initial impression was the same as for those with a noncardiac initial impression (RR = 0.83, 95% CI = 0.6 to 1.2). CONCLUSIONS: In ED patients without obvious initial evidence of a cardiac event, unstructured emergency physician (EP) estimate of risk correlates with adverse cardiac outcomes.





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Publication Info

Chandra, Abhinav, Christopher J Lindsell, Alexander Limkakeng, Deborah B Diercks, James W Hoekstra, Judd E Hollander, J Douglas Kirk, W Frank Peacock, et al. (2009). Emergency physician high pretest probability for acute coronary syndrome correlates with adverse cardiovascular outcomes. Academic emergency medicine : official journal of the Society for Academic Emergency Medicine, 16(8). 10.1111/j.1553-2712.2009.00470.x Retrieved from https://hdl.handle.net/10161/16687.

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Christopher Lindsell

Professor of Biostatistics & Bioinformatics

As Director, Chris Lindsell, PhD leads the visionary strategic planning, development, and execution of state-of-the-art research for DCRI to achieve its scientific goals. He also serves as a member of the Senior Management Team and, along with Dr. Laine Thomas, will partner with Jack Shostak, Director of Statistical Operations, to execute research.

Lindsell has served as the Institute for Clinical and Translational Research Methods program Director, co-Director of the Center for Health Data Science, and professor of biostatistics and biomedical informatics at Vanderbilt University. He is a leader in the application of rigorous methods in the acute care environment, and to the intersection between emergency care and public health. He has led data coordinating centers for numerous multi-center clinical trials, including FDA-regulated trials, and epidemiological studies. His experience spans mechanistic studies, network trials, pragmatic trials, embedded trials, and more.

Lindsell holds patents for using clinical information, biomarkers and transcriptomics for prognosis and prediction in sepsis and septic shock with a goal of precision therapy in critical illness. He has contributed to data standards for CONNECTS, NHLBI’s network of networks for COVID-19 research, and to the DAQCORD guidelines for data collection and curation in observational studies. He has published over 350 peer-reviewed papers, and most recently, he has been leading multiple major data center efforts during the Covid-19 pandemic including TREAT NOW, ACTIV6 and the IVY Network.


Alexander Tan Limkakeng

Professor of Emergency Medicine

Dr. Alexander T. Limkakeng, Jr., MD, MHSc, FACEP is a Professor of Emergency Medicine, Vice Chair of Clinical Research, Director of the Acute Care Research Team, and Director of the Resident Research Fellowship for the Department of Emergency Medicine in the Duke University School of Medicine in Durham, North Carolina.

Dr. Limkakeng has served as chair of the American College of Emergency Physicians (ACEP) Research Committee, and been the Course Director of the ACEP Research Forum from 2016-2018, the largest emergency medical research platform in the nation. He is also the Assistant Director of ACEP’s Emergency Medicine Basic Research Skills course. He was elected to the Nominating Committee of the Society of Academic Emergency Medicine.

As a researcher, Dr. Limkakeng has led multiple clinical trials and interdepartmental sponsored projects and is author on over 100 peer-reviewed manuscripts. These include studies in emergency conditions such as COVID-19, traumatic brain injury, hypertension, heart failure, thrombosis, stroke, envenomations, and septic shock. His research has been funded by grants and contracts totaling over $9 million dollars. He has lectured internationally on acute coronary syndrome, responsible conduct of research, design of clinical trials, and precision medicine in emergency care. He has led Duke’s involvement in NIH-funded research networks and in industry-funded work that led to FDA approval for multiple high-sensitivity cardiac troponin assays and point-of-care COVID-19 diagnostic tests. He has servesd as Co-PI for the Duke U24 Hub in the NIH Early Phase Pain Investigation Clinical Network (EPPIC-Net) (1U24NS114416) and now serves as a co-PI on the Duke U24 Hub award (1U24NS129498) in the NIH Strategies to Innovate Emergency Care Clinical Trials (SIREN) Network and in the NIH NINDS Strokenet network (1U24NS135250)

His personal research interest is finding new ways to diagnose acute coronary syndrome. In particular, he is interested in novel biomarkers and precision medicine approaches to this problem. The common element throughout this work is a focus on time-sensitive health conditions.

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