Inge J van den Hoogen1, Alexander R van Rosendael1, Fay Y Lin2, Yao Lu3, Aukelien C Dimitriu-Leen4, Jeff M Smit4, Arthur J H A Scholte4, Stephan Achenbach5, Mouaz H Al-Mallah6, Daniele Andreini7, Daniel S Berman8, Matthew J Budoff9, Filippo Cademartiri10, Tracy Q Callister11, Hyuk-Jae Chang12, Kavitha Chinnaiyan13, Benjamin J W Chow14, Ricardo C Cury15, Augustin DeLago16, Gudrun Feuchtner17, Martin Hadamitzky18, Joerg Hausleiter19, Philipp A Kaufmann20, Yong-Jin Kim21, Jonathon A Leipsic22, Erica Maffei23, Hugo Marques24, Pedro de Araújo Gonçalves24, Gianluca Pontone7, Gilbert L Raff13, Ronen Rubinshtein25, Todd C Villines26, Heidi Gransar27, Erica C Jones2, Jessica M Peña2, Leslee J Shaw2, James K Min2, Jeroen J Bax28. 1. Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands; Dalio Institute of Cardiovascular Imaging, Department of Radiology, New York-Presbyterian Hospital and the Weill Cornell Medical College, New York, NY, USA. 2. Dalio Institute of Cardiovascular Imaging, Department of Radiology, New York-Presbyterian Hospital and the Weill Cornell Medical College, New York, NY, USA. 3. Department of Healthcare Policy and Research, New York-Presbyterian Hospital and the Weill Cornell Medical College, New York, NY, USA. 4. Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands. 5. Department of Cardiology, Friedrich-Alexander-University Erlangen-Nuremburg, Germany. 6. King Saud Bin Abdulaziz University for Health Sciences, King Abdullah International Medical Research Center, King AbdulAziz Cardiac Center, Ministry of National Guard, Health Affairs, Riyadh, Saudi Arabia. 7. Centro Cardiologico Monzino, IRCCS, Milan, Italy. 8. Department of Imaging and Medicine, Cedars Sinai Medical Center, Los Angeles, CA, USA. 9. Department of Medicine, Los Angeles Biomedical Research Institute, Torrance, CA, USA. 10. Cardiovascular Imaging Center, SDN IRCCS, Naples, Italy. 11. Tennessee Heart and Vascular Institute, Hendersonville, TN, USA. 12. Division of Cardiology, Severance Cardiovascular Hospital and Severance Biomedical Science Institute, Yonsei University College of Medicine, Yonsei University Health System, Seoul, South Korea. 13. Department of Cardiology, William Beaumont Hospital, Royal Oak, MI, USA. 14. Department of Medicine and Radiology, University of Ottawa, ON, Canada. 15. Department of Radiology, Miami Cardiac and Vascular Institute, Miami, FL, USA. 16. Capitol Cardiology Associates, Albany, NY, USA. 17. Department of Radiology, Medical University of Innsbruck, Innsbruck, Austria. 18. Department of Radiology and Nuclear Medicine, German Heart Center Munich, Munich, Germany. 19. Medizinische Klinik I der Ludwig-Maximilians-UniversitätMünchen, Munich, Germany. 20. Department of Nuclear Medicine, University Hospital, Zurich, Switzerland and University of Zurich, Switzerland. 21. Seoul National University Hospital, Seoul, South Korea. 22. Department of Medicine and Radiology, University of British Columbia, Vancouver, BC, Canada. 23. Department of Radiology, Area Vasta 1/ASUR Marche, Urbino, Italy. 24. UNICA, Unit of Cardiovascular Imaging, Hospital da Luz, Lisboa, Portugal. 25. Department of Cardiology at the Lady Davis Carmel Medical Center, The Ruth and Bruce Rappaport School of Medicine, Technion-Israel Institute of Technology, Haifa, Israel. 26. Cardiology Service, Walter Reed National Military Center, Bethesda, MD, USA. 27. Department of Imaging, Cedars Sinai Medical Center, Los Angeles, CA, USA. 28. Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands. Electronic address: j.j.bax@lumc.nl.
Abstract
AIMS: We aimed to compare semiquantitative coronary computed tomography angiography (CCTA) risk scores - which score presence, extent, composition, stenosis and/or location of coronary artery disease (CAD) - and their prognostic value between patients with and without diabetes mellitus (DM). Risk scores derived from general chest-pain populations are often challenging to apply in DM patients, because of numerous confounders. METHODS: Out of a combined cohort from the Leiden University Medical Center and the CONFIRM registry with 5-year follow-up data, we performed a secondary analysis in diabetic patients with suspected CAD who were clinically referred for CCTA. A total of 732 DM patients was 1:1 propensity-matched with 732 non-DM patients by age, sex and cardiovascular risk factors. A subset of 7 semiquantitative CCTA risk scores was compared between groups: 1) any stenosis ≥50%, 2) any stenosis ≥70%, 3) stenosis-severity component of the coronary artery disease-reporting and data system (CAD-RADS), 4) segment involvement score (SIS), 5) segment stenosis score (SSS), 6) CT-adapted Leaman score (CT-LeSc), and 7) Leiden CCTA risk score. Cox-regression analysis was performed to assess the association between the scores and the primary endpoint of all-cause death and non-fatal myocardial infarction. Also, area under the receiver-operating characteristics curves were compared to evaluate discriminatory ability. RESULTS: A total of 1,464 DM and non-DM patients (mean age 58 ± 12 years, 40% women) underwent CCTA and 155 (11%) events were documented after median follow-up of 5.1 years. In DM patients, the 7 semiquantitative CCTA risk scores were significantly more prevalent or higher as compared to non-DM patients (p ≤ 0.022). All scores were independently associated with the primary endpoint in both patients with and without DM (p ≤ 0.020), with non-significant interaction between the scores and diabetes (interaction p ≥ 0.109). Discriminatory ability of the Leiden CCTA risk score in DM patients was significantly better than any stenosis ≥50% and ≥70% (p = 0.003 and p = 0.007, respectively), but comparable to the CAD-RADS, SIS, SSS and CT-LeSc that also focus on the extent of CAD (p ≥ 0.265). CONCLUSION: Coronary atherosclerosis scoring with semiquantitative CCTA risk scores incorporating the total extent of CAD discriminate major adverse cardiac events well, and might be useful for risk stratification of patients with DM beyond the binary evaluation of obstructive stenosis alone.
AIMS: We aimed to compare semiquantitative coronary computed tomography angiography (CCTA) risk scores - which score presence, extent, composition, stenosis and/or location of coronary artery disease (CAD) - and their prognostic value between patients with and without diabetes mellitus (DM). Risk scores derived from general chest-pain populations are often challenging to apply in DMpatients, because of numerous confounders. METHODS: Out of a combined cohort from the Leiden University Medical Center and the CONFIRM registry with 5-year follow-up data, we performed a secondary analysis in diabeticpatients with suspected CAD who were clinically referred for CCTA. A total of 732 DMpatients was 1:1 propensity-matched with 732 non-DMpatients by age, sex and cardiovascular risk factors. A subset of 7 semiquantitative CCTA risk scores was compared between groups: 1) any stenosis ≥50%, 2) any stenosis ≥70%, 3) stenosis-severity component of the coronary artery disease-reporting and data system (CAD-RADS), 4) segment involvement score (SIS), 5) segment stenosis score (SSS), 6) CT-adapted Leaman score (CT-LeSc), and 7) Leiden CCTA risk score. Cox-regression analysis was performed to assess the association between the scores and the primary endpoint of all-cause death and non-fatal myocardial infarction. Also, area under the receiver-operating characteristics curves were compared to evaluate discriminatory ability. RESULTS: A total of 1,464 DM and non-DMpatients (mean age 58 ± 12 years, 40% women) underwent CCTA and 155 (11%) events were documented after median follow-up of 5.1 years. In DMpatients, the 7 semiquantitative CCTA risk scores were significantly more prevalent or higher as compared to non-DMpatients (p ≤ 0.022). All scores were independently associated with the primary endpoint in both patients with and without DM (p ≤ 0.020), with non-significant interaction between the scores and diabetes (interaction p ≥ 0.109). Discriminatory ability of the Leiden CCTA risk score in DMpatients was significantly better than any stenosis ≥50% and ≥70% (p = 0.003 and p = 0.007, respectively), but comparable to the CAD-RADS, SIS, SSS and CT-LeSc that also focus on the extent of CAD (p ≥ 0.265). CONCLUSION:Coronary atherosclerosis scoring with semiquantitative CCTA risk scores incorporating the total extent of CAD discriminate major adverse cardiac events well, and might be useful for risk stratification of patients with DM beyond the binary evaluation of obstructive stenosis alone.
Authors: Todd C Villines; Subhi J Al'Aref; Daniele Andreini; Marcus Y Chen; Andrew D Choi; Carlo N De Cecco; Damini Dey; James P Earls; Maros Ferencik; Heidi Gransar; Harvey Hecht; Jonathon A Leipsic; Michael T Lu; Mohamed Marwan; Pál Maurovich-Horvat; Edward Nicol; Gianluca Pontone; Jonathan Weir-McCall; Seamus P Whelton; Michelle C Williams; Armin Arbab-Zadeh; Gudrun M Feuchtner Journal: J Cardiovasc Comput Tomogr Date: 2021-02-22