Robert J H Miller1,2, Alan Rozanski1,3,4, Piotr J Slomka1, Donghee Han1, Heidi Gransar1, Sean W Hayes1, John D Friedman1, Louise E J Thomson1, Daniel S Berman5. 1. Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA. 2. Libin Cardiovascular Institute of Alberta, University of Calgary, Calgary, AB, Canada. 3. Division of Cardiology and Department of Medicine, Mount Sinai Morningside Hospital, Mount Sinai Heart and the Icahn School of Medicine at Mount Sinai, New York, NY, USA. 4. Division of Cardiac Sciences, Mount Sinai Morningside Hospital, Mount Sinai Heart and the Icahn School of Medicine at Mount Sinai, New York, NY, USA. 5. Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA. bermand@cshs.org.
Abstract
BACKGROUND: The likelihood of ischemia on myocardial perfusion imaging is central to physician decisions regarding test selection, but dedicated risk scores are lacking. We derived and validated two novel ischemia risk scores to support physician decision making. METHODS: Risk scores were derived using 15,186 patients and validated with 2,995 patients from a different center. Logistic regression was used to assess associations with ischemia to derive point-based and calculated ischemia scores. Predictive performance for ischemia was assessed using area under the receiver operating characteristic curve (AUC) and compared with the CAD consortium basic and clinical models. RESULTS: During derivation, the calculated ischemia risk score (0.801) had higher AUC compared to the point-based score (0.786, p < 0.001). During validation, the calculated ischemia score (0.716, 95% CI 0.684- 0.748) had higher AUC compared to the point-based ischemia score (0.699, 95% CI 0.666- 0.732, p = 0.016) and the clinical CAD model (AUC 0.667, 95% CI 0.633- 0.701, p = 0.002). Calibration for both ischemia scores was good in both populations (Brier score < 0.100). CONCLUSIONS: We developed two novel risk scores for predicting probability of ischemia on MPI which demonstrated high accuracy during model derivation and in external testing. These scores could support physician decisions regarding diagnostic testing strategies.
BACKGROUND: The likelihood of ischemia on myocardial perfusion imaging is central to physician decisions regarding test selection, but dedicated risk scores are lacking. We derived and validated two novel ischemia risk scores to support physician decision making. METHODS: Risk scores were derived using 15,186 patients and validated with 2,995 patients from a different center. Logistic regression was used to assess associations with ischemia to derive point-based and calculated ischemia scores. Predictive performance for ischemia was assessed using area under the receiver operating characteristic curve (AUC) and compared with the CAD consortium basic and clinical models. RESULTS: During derivation, the calculated ischemia risk score (0.801) had higher AUC compared to the point-based score (0.786, p < 0.001). During validation, the calculated ischemia score (0.716, 95% CI 0.684- 0.748) had higher AUC compared to the point-based ischemia score (0.699, 95% CI 0.666- 0.732, p = 0.016) and the clinical CAD model (AUC 0.667, 95% CI 0.633- 0.701, p = 0.002). Calibration for both ischemia scores was good in both populations (Brier score < 0.100). CONCLUSIONS: We developed two novel risk scores for predicting probability of ischemia on MPI which demonstrated high accuracy during model derivation and in external testing. These scores could support physician decisions regarding diagnostic testing strategies.
Authors: Daniel S Berman; Piotr J Slomka; Donghee Han; Alan Rozanski; Heidi Gransar; Evangelos Tzolos; Robert J H Miller; Tali Sharir; Andrew J Einstein; Mathews B Fish; Terrence D Ruddy; Philipp A Kaufmann; Albert J Sinusas; Edward J Miller; Timothy M Bateman; Sharmila Dorbala; Marcelo Di Carli; Joanna X Liang; Lien-Hsin Hu; Damini Dey Journal: J Nucl Cardiol Date: 2021-11-10 Impact factor: 3.872
Authors: Cvetan Trpkov; Alexei Savtchenko; Zhiying Liang; Patrick Feng; Danielle A Southern; Stephen B Wilton; Matthew T James; Erin Feil; Ilias Mylonas; Robert J H Miller Journal: Int J Cardiol Heart Vasc Date: 2021-06-19
Authors: Evann Eisenberg; Robert J H Miller; Lien-Hsin Hu; Richard Rios; Julian Betancur; Peyman Azadani; Donghee Han; Tali Sharir; Andrew J Einstein; Sabahat Bokhari; Mathews B Fish; Terrence D Ruddy; Philipp A Kaufmann; Albert J Sinusas; Edward J Miller; Timothy M Bateman; Sharmila Dorbala; Marcelo Di Carli; Joanna X Liang; Yuka Otaki; Balaji K Tamarappoo; Damini Dey; Daniel S Berman; Piotr J Slomka Journal: J Nucl Cardiol Date: 2021-07-06 Impact factor: 3.872
Authors: Ibrahim Danad; Jackie Szymonifka; Jos W R Twisk; Bjarne L Norgaard; Christopher K Zarins; Paul Knaapen; James K Min Journal: Eur Heart J Date: 2017-04-01 Impact factor: 35.855