Sarah Feger1, Paolo Ibes1, Adriane E Napp1, Alexander Lembcke1, Michael Laule1, Henryk Dreger1, Björn Bokelmann1, Gershan K Davis2,3, Giles Roditi4, Ignacio Diez5, Stephen Schröder6, Fabian Plank7, Pal Maurovich-Horvat8, Radosav Vidakovic9, Josef Veselka10, Malgorzata Ilnicka-Suckiel11, Andrejs Erglis12, Teodora Benedek13, José Rodriguez-Palomares14,15, Luca Saba16, Klaus F Kofoed17, Matthias Gutberlet18, Filip Ađić19, Mikko Pietilä20, Rita Faria21, Audrone Vaitiekiene22, Jonathan D Dodd23, Patrick Donnelly24, Marco Francone25, Cezary Kepka26, Balazs Ruzsics27, Jacqueline Müller-Nordhorn28, Peter Schlattmann29, Marc Dewey30,31,32. 1. Charité - Universitätsmedizin Berlin, Humboldt-Universität and Freie Universität zu Berlin, Berlin, Germany. 2. Department of Cardiology, Aintree University Hospital, Liverpool, UK. 3. University of Central Lancashire, Liverpool, UK. 4. Institute of Cardiovascular and Medical Sciences, Glasgow University, Glasgow, UK. 5. Department of Cardiology, Basurto University Hospital Bilbao, Bilbao, Spain. 6. Department of Cardiology, ALB FILS KLINIKEN, Goeppingen, Germany. 7. Department of Radiology and Department of Cardiology, Medical University Innsbruck, Innsbruck, Austria. 8. Department of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary. 9. Department of Cardiology, Clinical Hospital Center "Zemun", Faculty of Medicine, University of Belgrade, Zemun, Belgrade, Serbia. 10. Department of Cardiology, Motol University Hospital and 2nd School of Medicine, Charles University, Prague, Czech Republic. 11. Department of Cardiology, Wojewodzki Szpital Specjalistyczny We Wroclawiu, Wrocław, Poland. 12. Latvian Centre of Cardiology, Pauls Stradins Clinical University Hospital, Riga, Latvia. 13. Department of Cardiology, Cardio Med Medical Center Targu-Mures, Târgu Mureș, Romania. 14. Hospital Universitari Vall d´Hebron, Department of Cardiology. Vall d'Hebron Institut de Recerca (VHIR). Universitat Autònoma de Barcelona, Barcelona, Spain. 15. Centro de Investigación Biomédica en Red-CV, CIBER CV, Barcelona, Spain. 16. Department of Radiology, Azienda Ospedaliero Universitaria di Cagliari, Cagliari, Italy. 17. Department of Cardiology and Radiology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark. 18. Department of Diagnostic and Interventional Radiology, UNIVERSITY LEIPZIG -Heart Center Leipzig, Leipzig, Germany. 19. Department of Cardiology, Institute for Cardiovascular Diseases of Vojvodina, Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia. 20. Turku PET Centre and Heart Centre, Turku University Hospital, Turku, Finland. 21. Department of Cardiology, Centro Hospitalar de Vila Nova de Gaia, Vila Nova de Gaia, Portugal. 22. Department of Cardiology, Lithuanian University of Health Sciences, Kaunas, Lithuania. 23. Department of Radiology, St. Vincent's University hospital, School of Medicine, University College Dublin, Dublin, Ireland. 24. Department of Cardiology, Southeastern Health and Social Care Trust, Belfast, Ireland. 25. Department of Radiological, Pathological and Oncological Sciences, Sapienza University of Rome, Rome, Italy. 26. Dept. of Coronary and Structural Heart Diseases, Institute of Cardiology, Warsaw, Poland. 27. Royal Liverpool and Broadgreen University Hospital, Liverpool, UK. 28. Berlin School of Public Health Berlin, Berlin, Germany. 29. Institut für Statistik, Medizinische Informatik, Datenwissenschaften Universitätsklinikum Jena, Leipzig, Germany. 30. Charité - Universitätsmedizin Berlin, Humboldt-Universität and Freie Universität zu Berlin, Berlin, Germany. dewey@charite.de. 31. Charité-Universitätsmedizin Berlin Department of Radiology, Berlin Institute of Health, Berlin, Germany. dewey@charite.de. 32. DZHK (German Centre for Cardiovascular Research), partner site Berlin, Germany. dewey@charite.de.
Abstract
OBJECTIVES: To test the accuracy of clinical pre-test probability (PTP) for prediction of obstructive coronary artery disease (CAD) in a pan-European setting. METHODS: Patients with suspected CAD and stable chest pain who were clinically referred for invasive coronary angiography (ICA) or computed tomography (CT) were included by clinical sites participating in the pilot study of the European multi-centre DISCHARGE trial. PTP of CAD was determined using the Diamond-Forrester (D+F) prediction model initially introduced in 1979 and the updated D+F model from 2011. Obstructive coronary artery disease (CAD) was defined by one at least 50% diameter coronary stenosis by both CT and ICA. RESULTS: In total, 1440 patients (654 female, 786 male) were included at 25 clinical sites from May 2014 until July 2017. Of these patients, 725 underwent CT, while 715 underwent ICA. Both prediction models overestimated the prevalence of obstructive CAD (31.7%, 456 of 1440 patients, PTP: initial D+F 58.9% (28.1-90.6%), updated D+F 47.3% (34.2-59.9%), both p < 0.001), but overestimation of disease prevalence was higher for the initial D+F (p < 0.001). The discriminative ability was higher for the updated D+F 2011 (AUC of 0.73 95% confidence interval [CI] 0.70-0.76 versus AUC of 0.70 CI 0.67-0.73 for the initial D+F; p < 0.001; odds ratio (or) 1.55 CI 1.29-1.86, net reclassification index 0.11 CI 0.05-0.16, p < 0.001). CONCLUSIONS: Clinical PTP calculation using the initial and updated D+F prediction models relevantly overestimates the actual prevalence of obstructive CAD in patients with stable chest pain clinically referred for ICA and CT suggesting that further refinements to improve clinical decision-making are needed. TRIAL REGISTRATION: https://www.clinicaltrials.gov/ct2/show/NCT02400229 KEY POINTS: • Clinical pre-test probability calculation using the initial and updated D+F model overestimates the prevalence of obstructive CAD identified by ICA and CT. • Overestimation of disease prevalence is higher for the initial D+F compared with the updated D+F. • Diagnostic accuracy of PTP assessment varies strongly between different clinical sites throughout Europe.
OBJECTIVES: To test the accuracy of clinical pre-test probability (PTP) for prediction of obstructive coronary artery disease (CAD) in a pan-European setting. METHODS: Patients with suspected CAD and stable chest pain who were clinically referred for invasive coronary angiography (ICA) or computed tomography (CT) were included by clinical sites participating in the pilot study of the European multi-centre DISCHARGE trial. PTP of CAD was determined using the Diamond-Forrester (D+F) prediction model initially introduced in 1979 and the updated D+F model from 2011. Obstructive coronary artery disease (CAD) was defined by one at least 50% diameter coronary stenosis by both CT and ICA. RESULTS: In total, 1440 patients (654 female, 786 male) were included at 25 clinical sites from May 2014 until July 2017. Of these patients, 725 underwent CT, while 715 underwent ICA. Both prediction models overestimated the prevalence of obstructive CAD (31.7%, 456 of 1440 patients, PTP: initial D+F 58.9% (28.1-90.6%), updated D+F 47.3% (34.2-59.9%), both p < 0.001), but overestimation of disease prevalence was higher for the initial D+F (p < 0.001). The discriminative ability was higher for the updated D+F 2011 (AUC of 0.73 95% confidence interval [CI] 0.70-0.76 versus AUC of 0.70 CI 0.67-0.73 for the initial D+F; p < 0.001; odds ratio (or) 1.55 CI 1.29-1.86, net reclassification index 0.11 CI 0.05-0.16, p < 0.001). CONCLUSIONS: Clinical PTP calculation using the initial and updated D+F prediction models relevantly overestimates the actual prevalence of obstructive CAD in patients with stable chest pain clinically referred for ICA and CT suggesting that further refinements to improve clinical decision-making are needed. TRIAL REGISTRATION: https://www.clinicaltrials.gov/ct2/show/NCT02400229 KEY POINTS: • Clinical pre-test probability calculation using the initial and updated D+F model overestimates the prevalence of obstructive CAD identified by ICA and CT. • Overestimation of disease prevalence is higher for the initial D+F compared with the updated D+F. • Diagnostic accuracy of PTP assessment varies strongly between different clinical sites throughout Europe.
Entities:
Keywords:
Computed tomography angiography; Coronary artery disease; Prevalence; Probability of disease
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