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A Clinical Prediction Model to Estimate Risk for 30-Day Adverse Events in Emergency Department Patients With Symptomatic Atrial Fibrillation  Tyler W.

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Presentation on theme: "A Clinical Prediction Model to Estimate Risk for 30-Day Adverse Events in Emergency Department Patients With Symptomatic Atrial Fibrillation  Tyler W."— Presentation transcript:

1 A Clinical Prediction Model to Estimate Risk for 30-Day Adverse Events in Emergency Department Patients With Symptomatic Atrial Fibrillation  Tyler W. Barrett, MD, MSCI, Amy R. Martin, MD, Alan B. Storrow, MD, Cathy A. Jenkins, MS, Frank E. Harrell, PhD, Stephan Russ, MD, MPH, Dan M. Roden, MD, Dawood Darbar, MD  Annals of Emergency Medicine  Volume 57, Issue 1, Pages 1-12 (January 2011) DOI: /j.annemergmed Copyright © 2010 American College of Emergency Physicians Terms and Conditions

2 Figure 1 Thirty-day adverse event prediction rule nomogram. Points are assigned for each of the 12 predictors. The total points correspond to an absolute predicted risk for 30-day adverse events. This nomogram should not be used in clinical practice until an independent validation is completed. Annals of Emergency Medicine  , 1-12DOI: ( /j.annemergmed ) Copyright © 2010 American College of Emergency Physicians Terms and Conditions

3 Figure 2 Histogram of predicted probabilities of 30-day adverse events. This figure illustrates the histogram of predicted probabilities from the model and shows that 3.4% of subjects had predicted probabilities greater than 0.50 and 5.8% had predicted probabilities less than 0.10. Annals of Emergency Medicine  , 1-12DOI: ( /j.annemergmed ) Copyright © 2010 American College of Emergency Physicians Terms and Conditions

4 Figure 3 Calibration plot for atrial fibrillation clinical prediction model. This plot illustrates the calibration accuracy of the original model (“Apparent”) and the bootstrap model (“Bias-corrected”) for 30-day adverse events with locally weighted scatterplot smoothing used to model the relationship between actual and predicted probabilities. As can be seen, the model's calibration function estimate is slightly nonlinear, with the corrected calibration showing good agreement with the apparent calibration. Annals of Emergency Medicine  , 1-12DOI: ( /j.annemergmed ) Copyright © 2010 American College of Emergency Physicians Terms and Conditions


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