Coronary atherosclerosis scoring with semiquantitative CCTA risk scores for prediction of major adverse cardiac events: propensity score-based analysis of diabetic and non-diabetic patients
Open accessAbstract
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.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The SSS and SIS have demonstrated clinical validity in detecting major adverse cardiac events in multiple populations.
“The SSS and SIS have demonstrated clinical validity in detecting major adverse cardiac events in multiple populations.15–19”
From Lifelong endurance exercise and its relation with coronary atherosclerosis (2023) · cites this paper as [19]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Roffi, M., Patrono, C., Collet, J.-P., Mueller, C., Valgimigli, M., Andreotti, F., Bax, J. J., Borger, M. A., Brotons, C., Chew, D. P., et al. (2016) · European Heart Journal · doi:10.1093/eurheartj/ehv320 · Cited by 8,261 · see citing works
Self-citationHaffner, S. M., Lehto, S., Rönnemaa, T., Pyörälä, K., & Laakso, M. (1998) · New England Journal of Medicine · doi:10.1056/nejm199807233390404 · Cited by 7,000 · see citing works
HEART DISEASE AND STROKE STATISTICS–2014 UPDATE: A REPORT FROM THE AMERICAN HEART ASSOCIATION
Tarver, T. (2014) · Journal of Consumer Health on the Internet · doi:10.1080/15398285.2014.902284 · Cited by 5,595 · see citing works
Heart Disease and Stroke Statistics—2013 Update: A Report From the American Heart Association
Go, A. S., Mozaffarian, D., Roger, V. L., Benjamin, E. J., Berry, J. D., Borden, W. B., Bravata, D. M., Dai, S., Ford, E. S., Fox, C. S., et al. (2013) · Circulation · doi:10.1161/cir.0b013e31828124ad · Cited by 5,292 · see citing works
Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference
Ho, D. E., Imai, K., King, G., & Stuart, E. (2007) · Political Analysis · doi:10.1093/pan/mpl013 · Cited by 4,411 · see citing works
<b>MatchIt</b> : Nonparametric Preprocessing for Parametric Causal Inference
Ho, D. E., Imai, K., King, G., & Stuart, E. A. (2011) · Journal of Statistical Software · doi:10.18637/jss.v042.i08 · Cited by 4,385 · see citing works
Diabetes and cardiovascular disease. The Framingham study
Kannel, W. B. (1979) · JAMA · doi:10.1001/jama.241.19.2035 · Cited by 3,958 · see citing works
Wg, A., Edwards, J., Frye, R., Gg, G., Gott, V. L., Griffith, L., McGoon, D. C., Murphy, M., & Roe, B. B. (1975) · Circulation · doi:10.1161/01.cir.51.4.5 · Cited by 3,255 · see citing works
Diabetes and Cardiovascular Disease: The Framingham Study
Kannel, W. B. (1979) · JAMA · doi:10.1001/jama.1979.03290450033020 · Cited by 2,936 · see citing works
Heart disease and stroke statistics--2013 update: a report from the American Heart Association.
Go, A. S., Mozaffarian, D., Roger, V. L., Benjamin, E. J., Berry, J. D., Blaha, M. J., Dai, S., Ford, E. S., Fox, C. S., Franco, S., et al. (2013) · eScholarship (California Digital Library) · Cited by 2,601 · see citing works
Authors Task Force Members, Rydén, L., Grant, P. J., Anker, S. D., Berne, C., Cosentino, F., Danchin, N., Deaton, C., Escaned, J., Hammes, H., et al. (2013) · European Heart Journal · doi:10.1093/eurheartj/eht108 · Cited by 1,958 · see citing works
Self-citationDiagnostic Accuracy of 64-Slice Computed Tomography Coronary Angiography
Meijboom, W. B., Meijs, M. F. L., Schuijf, J. D., Cramer, M. J., Mollet, N. R., van Mieghem, C. A. G., Nieman, K., van Werkhoven, J. M., Pundziūtė, G., Weustink, A. C., et al. (2008) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2008.08.058 · Cited by 1,236 · see citing works
Self-citationMin, J. K., Shaw, L. J., Devereux, R. B., Okin, P. M., Weinsaft, J. W., Russo, D. J., Lippolis, N. J., Berman, D. S., & Callister, T. Q. (2007) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2007.03.067 · Cited by 1,055 · see citing works
Self-citationMcClelland, R. L., Chung, H., Detrano, R., Post, W., & Kronmal, R. A. (2006) · Circulation · doi:10.1161/circulationaha.105.580696 · Cited by 885 · see citing works
Mortality in adults with and without diabetes in a national cohort of the U.S. population, 1971–1993
Gu, K., Cowie, C. C., & Harris, M. I. (1998) · Diabetes Care · doi:10.2337/diacare.21.7.1138 · Cited by 881 · see citing works
SCCT guidelines for the interpretation and reporting of coronary computed tomographic angiography
Raff, G. L., Chair, Abidov, A., Achenbach, S. S., Berman, D. S., Boxt, L. M., Budoff, M. J., Cheng, V., DeFrance, T., Hellinger, J. C., et al. (2009) · Journal of cardiovascular computed tomography · doi:10.1016/j.jcct.2009.01.001 · Cited by 807 · see citing works
Self-citationAbbara, S., Arbab‐Zadeh, A., Callister, T. Q., Desai, M. Y., Mamuya, W. S., Thomson, L., & Weigold, W. G. (2009) · Journal of cardiovascular computed tomography · doi:10.1016/j.jcct.2009.03.004 · Cited by 578 · see citing works
Self-citationThird Universal Definition of Myocardial Infarction
Thygesen, K. A., Alpert, J. S., Jaffe, A. S., Simoons, M. L., CHAITMAN, B. R., White, H. D., & Writing Group Joint ESC For the Universal Definition of MI (2012) · Global Heart · doi:10.1016/j.gheart.2012.08.001 · Cited by 546 · see citing works
Coronary Atherosclerotic Precursors of Acute Coronary Syndromes
Chang, H., Lin, F. Y.-H., Lee, S., Andreini, D., Bax, J. J., Cademartiri, F., Chinnaiyan, K. M., Chow, B. J. W., Conte, E., Cury, R. C., et al. (2018) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.02.079 · Cited by 495 · see citing works
Self-citationType 2 Diabetes as a “Coronary Heart Disease Equivalent”
Juutilainen, A., Lehto, S., Rönnemaa, T., Pyörälä, K., & Laakso, M. (2005) · Diabetes Care · doi:10.2337/diacare.28.12.2901 · Cited by 452 · see citing works
Fox, C. S., Golden, S. H., Anderson, C., Bray, G. A., Burke, L. E., de Boer, I. H., Deedwania, P., Eckel, R. H., Ershow, A. G., Fradkin, J., et al. (2015) · Circulation · doi:10.1161/cir.0000000000000230 · Cited by 386 · see citing works
Is diabetes a coronary risk equivalent? Systematic review and meta‐analysis
Bulugahapitiya, U., Siyambalapitiya, S., Sithole, J., & IDRIS, I. R. (2008) · Diabetic Medicine · doi:10.1111/j.1464-5491.2008.02640.x · Cited by 377 · see citing works
Optimized Prognostic Score for Coronary Computed Tomographic Angiography
Hadamitzky, M., Achenbach, S. S., Al-Mallah, M. H., Berman, D. S., Budoff, M. J., Cademartiri, F., Callister, T. Q., Chang, H., Cheng, V., Chinnaiyan, K. M., et al. (2013) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2013.04.064 · Cited by 270 · see citing works
Self-citationThe epidemiology of cardiovascular disease in type 2 diabetes mellitus: how sweet it is … or is it?
Nathan, D. M., Meigs, J. B., & Singer, D. E. (1997) · The Lancet · doi:10.1016/s0140-6736(97)90021-0 · Cited by 264 · see citing works
Should Diabetes Be Considered a Coronary Heart Disease Risk Equivalent?
Whiteley, L., Padmanabhan, S., Hole, D. J., & Isles, C. (2005) · Diabetes Care · doi:10.2337/diacare.28.7.1588 · Cited by 219 · see citing works
de Graaf, F. R., Schuijf, J. D., van Velzen, J. E., Kroft, L. J. M., Roos, A., Reiber, J. H. C., Boersma, E. H., Schalij, M. J., Spanó, F., Jukema, J. W., et al. (2010) · European Heart Journal · doi:10.1093/eurheartj/ehp571 · Cited by 200 · see citing works
Self-citationRana, J. S., Dunning, A. M., Achenbach, S. S., Al-Mallah, M. H., Budoff, M. J., Cademartiri, F., Callister, T. Q., Chang, H., Cheng, V., Chinnaiyan, K. M., et al. (2012) · Diabetes Care · doi:10.2337/dc11-2403 · Cited by 176 · see citing works
Self-citationMin, J. K., Dunning, A. M., Lin, F. Y.-H., Achenbach, S. S., Al-Mallah, M. H., Berman, D. S., Budoff, M. J., Cademartiri, F., Callister, T. Q., Chang, H., et al. (2011) · Journal of cardiovascular computed tomography · doi:10.1016/j.jcct.2011.01.007 · Cited by 171 · see citing works
Self-citationvan Werkhoven, J. M., Schuijf, J. D., Gaemperli, O., Jukema, J. W., Kroft, L. J. M., Boersma, E. H., Pazhenkottil, A. P., Valenta, I., Pundziūtė, G., Roos, A., et al. (2009) · European Heart Journal · doi:10.1093/eurheartj/ehp272 · Cited by 159 · see citing works
Self-citationLong-Term Prognostic Effect of Coronary Atherosclerotic Burden
Mushtaq, S., Gonçalves, P. D. A., García‐García, H. M., Pontone, G., Bartorelli, A. L., Bertella, E., Campos, C. M., Pepi, M., Serruys, P. W. J. C., & Andreini, D. (2015) · Circulation Cardiovascular Imaging · doi:10.1161/circimaging.114.002332 · Cited by 152 · see citing works
Self-citationCarrigan, T. P., Nair, D. R., Schoenhagen, P., Curtin, R. J., Popović, Z., Halliburton, S. S., Kuzmiak, S. A., White, R. D., Flamm, S. D., & Desai, M. Y. (2008) · European Heart Journal · doi:10.1093/eurheartj/ehn605 · Cited by 145 · see citing works
van Rosendael, A. R., Shaw, L. J., Xie, J. X., Dimitriu‐Leen, A. C., Smit, J. M., Scholte, A. J. H. A., van Werkhoven, J. M., Callister, T. Q., DeLago, A. J., Berman, D. S., et al. (2019) · JACC. Cardiovascular imaging · doi:10.1016/j.jcmg.2018.10.024 · Cited by 115 · see citing works
Self-citationKim, U., Leipsic, J. A., Sellers, S., Shao, M., Blanke, P., Hadamitzky, M., Kim, Y.-J., Conte, E., Andreini, D., Pontone, G., et al. (2018) · JACC. Cardiovascular imaging · doi:10.1016/j.jcmg.2018.04.009 · Cited by 96 · see citing works
Self-citationHadamitzky, M., Hein, F., Meyer, T., Bischoff, B., Martinoff, S., Schömig, A., & Hausleiter, J. (2010) · Diabetes Care · doi:10.2337/dc09-2104 · Cited by 90 · see citing works
Self-citationDiabetes: Prognostic Value of CT Coronary Angiography—Comparison with a Nondiabetic Population
van Werkhoven, J. M., Cademartiri, F., Seitun, S., Maffei, E., Palumbo, A., Martini, C., Tarantini, G., Kroft, L. J. M., Roos, A., Weustink, A. C., et al. (2010) · Radiology · doi:10.1148/radiol.1090600 · Cited by 78 · see citing works
Self-citationAndreini, D., Pontone, G., Mushtaq, S., Gransar, H., Conte, E., Bartorelli, A. L., Pepi, M., Opolski, M. P., Hartaigh, B. Ó., Berman, D. S., et al. (2016) · International Journal of Cardiology · doi:10.1016/j.ijcard.2016.12.137 · Cited by 75 · see citing works
Self-citationKim, J.-J., Hwang, B., Choi, I. J., Choo, E. H., Lim, S., Kim, J. K., Koh, Y., Kim, D., Jang, S.-W., Cho, E. J., et al. (2015) · European Heart Journal - Cardiovascular Imaging · doi:10.1093/ehjci/jev106 · Cited by 72 · see citing works
Self-citationStress Testing Versus CT Angiography in Patients With Diabetes and Suspected Coronary Artery Disease
Sharma, A., Coles, A., Sekaran, N. K., Pagidipati, N. J., Lu, M. T., Mark, D. B., Lee, K. L., Al-Khalidi, H. R., Hoffmann, U., & Douglas, P. S. (2019) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.11.056 · Cited by 72 · see citing works
Computed tomography for detecting coronary artery plaques: A meta-analysis
Gao, D., Ning, N., Guo, Y., Ning, W., Niu, X., & Yang, J. Z. (2011) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2011.08.022 · Cited by 48 · see citing works
Diabetes as “Coronary Artery Disease Risk Equivalent”: A Historical Perspective
Hajar, R. (2017) · Heart Views · doi:10.4103/heartviews.heartviews_37_17 · Cited by 37 · see citing works
Gonçalves, P. D. A., García‐García, H. M., Carvalho, M. S., Dores, H., Sousa, P. J., Marques, H., Ferreira, A. M., Cardim, N. M., Teles, R. C., Raposo, L., et al. (2012) · International journal of cardiac imaging · doi:10.1007/s10554-012-0168-4 · Cited by 35 · see citing works
Self-citationPrognostic value of coronary CT angiography in diabetic patients: a 5-year follow up study
Nadjiri, J., Hausleiter, J., Deseive, S., Will, A., Hendrich, E., Martinoff, S., & Hadamitzky, M. (2016) · The International Journal of Cardiovascular Imaging · doi:10.1007/s10554-015-0785-9 · Cited by 21 · see citing works
Self-citationMaffei, E., Seitun, S., Martini, C., Guaricci, A. I., Tarantini, G., van Pelt, N., Weustink, A. C., Mollet, N. R., Berti, E., Grilli, R. G., et al. (2010) · Insights into Imaging · doi:10.1007/s13244-010-0053-4 · Cited by 18 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Lifelong endurance exercise and its relation with coronary atherosclerosis
De Bosscher, R., Dausin, C., Claus, P., Bogaert, J., Dymarkowski, S., Goetschalckx, K., Ghekiere, O., Van De Heyning, C. M., Van Herck, P., Paelinck, B., et al. (2023) · European Heart Journal · doi:10.1093/eurheartj/ehad152 · Cited by 140 · see citing works
Lee, J. W., Kim, J. Y., Han, K., Im, D. J., Lee, K. H., Kim, T. H., Park, C. H., & Hur, J. (2021) · Radiology · doi:10.1148/radiol.2021204704 · Cited by 30 · see citing works
Imaging biomarkers in cardiac CT: moving beyond simple coronary anatomical assessment
Cundari, G., Marchitelli, L., Pambianchi, G., Catapano, F., Conia, L., Stancanelli, G., Catalano, C., & Galea, N. (2024) · La radiologia medica · doi:10.1007/s11547-024-01771-5 · Cited by 28 · see citing works
Tesche, C., Bauer, M. J., Straube, F., Rogowski, S., Baumann, S., Renker, M., Fink, N., Schoepf, U. J., Hoffmann, E., & Ebersberger, U. (2022) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2022.10.006 · Cited by 24 · see citing works
Corti, A., Iacono, F. L., Ronchetti, F., Mushtaq, S., Pontone, G., Colombo, G. I., & Corino, V. (2024) · Trends in Cardiovascular Medicine · doi:10.1016/j.tcm.2024.06.003 · Cited by 22 · see citing works
Self-citationPrognostic Value of Stress CMR in Symptomatic Patients With Coronary Stenosis on CCTA
Pezel, T., Hovasse, T., Lefèvre, T., Sanguineti, F., Unterseeh, T., Champagne, S., Benamer, H., Neylon, A. M., Toupin, S., Garot, P., et al. (2022) · JACC. Cardiovascular imaging · doi:10.1016/j.jcmg.2022.03.008 · Cited by 22 · see citing works
Transitioning From Stenosis to Plaque Burden in the Cardiac CT Era
Villines, T. C., & Lozano, P. R. (2020) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2020.10.030 · Cited by 16 · see citing works
Self-citationPezel, T., Unterseeh, T., Hovasse, T., Asselin, A., Lefèvre, T., Chevalier, B., Neylon, A. M., Benamer, H., Champagne, S., Sanguineti, F., et al. (2021) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2021.760120 · Cited by 14 · see citing works
Comprehensive plaque assessment with serial coronary CT angiography: translation to bedside
Lakshmanan, S., Rezvanizadeh, V., & Budoff, M. J. (2020) · International journal of cardiac imaging · doi:10.1007/s10554-020-01849-x · Cited by 13 · see citing works
Self-citationCoronary volume to left ventricular mass ratio in patients with diabetes mellitus
Kuneman, J. H., Mahdiui, M. E., van Rosendael, A. R., van den Hoogen, I. J., Patel, M. R., Nørgaard, B. L., Fairbairn, T. A., Nieman, K., Akasaka, T., Berman, D. S., et al. (2022) · Journal of cardiovascular computed tomography · doi:10.1016/j.jcct.2022.01.004 · Cited by 12 · see citing works
Self-citationLiu, Z., Ding, Y., Dou, G., Wang, X., Shan, D., He, B., Jing, J., Chen, Y., & Yang, J. (2022) · Korean Journal of Radiology · doi:10.3348/kjr.2022.0115 · Cited by 10 · see citing works
The Journal of Cardiovascular Computed Tomography: 2020 Year in review
Villines, T. C., Alaref, S. J., Andreini, D., Chen, M. Y., Choi, A. D., Cecco, C. N. D., Dey, D., Earls, J. P., Ferencik, M., Gransar, H., et al. (2021) · Journal of cardiovascular computed tomography · doi:10.1016/j.jcct.2021.02.004 · Cited by 9 · see citing works
Self-citationThe long-term prognostic value provided by Coronary CT angiography
Mohammadi, T., & Mohammadi, B. (2022) · European Journal of Internal Medicine · doi:10.1016/j.ejim.2022.10.020 · Cited by 8 · see citing works
Tesche, C., Baquet, M., Bauer, M. J., Straube, F., Hartl, S., Leonard, T. J., Jochheim, D., Fink, D., Brandt, V., Baumann, S., et al. (2021) · Journal of Thoracic Imaging · doi:10.1097/rti.0000000000000626 · Cited by 7 · see citing works
Predicting vulnerable coronary arteries: A combined radiomics-biomechanics approach
Corti, A., Stefanati, M., Leccardi, M., FILIPPO, O. D., Depaoli, A., Cerveri, P., Migliavacca, F., Corino, V., Matas, J. F. R., Mainardi, L. T., et al. (2024) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2024.108552 · Cited by 6 · see citing works
Dai, Y., Ouyang, C., Luo, G., Cao, Y., Peng, J., Gao, A., & Zhou, H. (2023) · PeerJ · doi:10.7717/peerj.15797 · Cited by 6 · see citing works
Jiang, Y., Yang, Z., Wang, J., Jiang, L., Han, P., Shi, R., & Li, Y. (2024) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2024.1372519 · Cited by 5 · see citing works
Kato, S., Azuma, M., Horita, N., & Utsunomiya, D. (2024) · Radiology Advances · doi:10.1093/radadv/umae007 · Cited by 5 · see citing works
Ding, Y., Liu, Z., Dou, G., Yang, X., Wang, X., Shan, D., He, B., Jing, J., Chen, Y., & Yang, J. (2021) · Journal of Diabetes Research · doi:10.1155/2021/5597467 · Cited by 4 · see citing works
“[17] evaluated the per-segment and per-patient weight scores to determine the contribution of the stenosis, composition, and location of CAD to the total score.”
BackgroundClinical Relevance of Coronary Computed Tomography Angiography Beyond Coronary Artery Stenosis
Meah, M. N., & Williams, M. C. (2021) · RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren · doi:10.1055/a-1395-7905 · Cited by 4 · see citing works
“A variety of semi-quantitative scores have been proposed which aim to summarize the results of CCTA into a single metric that communicates plaque burden (▶ Table 1) [21].”
BackgroundLiu, Z., Ding, Y., Dou, G., Yang, X., Wang, X., Shan, D., He, B., Jing, J., Chen, Y., & Yang, J. (2021) · Atherosclerosis Plus · doi:10.1016/j.athplu.2021.07.021 · Cited by 4 · see citing works
“The assessment of atherosclerotic extent may also produce incremental prognostic value over the evaluation of plaque stenosis, especially in DM patients [25].”
BackgroundXue, R., Ren, Z., Zhao, H., Xu, J., Li, S., Lin, S., Li, J., Wen, D., & Zheng, M. (2023) · European Journal of Radiology · doi:10.1016/j.ejrad.2023.111063 · Cited by 4 · see citing works
Löfmark, H., Ostenfeld, E., Baron, T., Fagman, E., Feldt, K., Markstad, H., Muhrbeck, J., Sandstedt, M., Shahgaldi, K., Zelleroth, E., et al. (2026) · European Heart Journal - Cardiovascular Imaging · doi:10.1093/ehjci/jeag090 · Cited by 3 · see citing works
“19,20 When SIS and CACS were compared, they had similar ability to discriminate between death or MI and MI alone, whereas CACS was superior in predicting all-cause mortality.”
Chen, L., Wu, P., Tu, H., Sheu, M., & Huang, L. (2021) · Radiation Protection Dosimetry · doi:10.1093/rpd/ncab068 · Cited by 2 · see citing works
Jing, M. X., Xi, H., Yang, J., Zhu, H., Sun, Q., Ren, W., Deng, L., Han, T., Zhang, Y., & Zhou, J. (2024) · Clinical Radiology · doi:10.1016/j.crad.2024.02.020 · Cited by 1 · see citing works
Tesche, C., Baquet, M., Bauer, M. J., Straube, F., Hartl, S., Leonard, T. J., Jochheim, D., Fink, D., Brandt, V., Baumann, S., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-276309/v1
“Leiden cCTA risk score, CT Leaman score) [9, 27], we additionally investigated high-risk plaque features that have been demonstrated as independent predictors of adverse cardiovascular outcome and have yet to be investigated in patients with diabetes.”
BackgroundMethodLiu, Z., Ding, Y., Dou, G., Yang, X., Wang, X., Shan, D., He, B., Jing, J., Chen, Y., & Yang, J. (2020) · Research Square · doi:10.21203/rs.3.rs-137386/v1
Giannopoulos, A. A., Rossi, A., Moysidis, D. V., Schaab, J. A., Jurisic, S., Albertini, T., Candreva, A., Stähli, B. E., Benz, D. C., Buechel, R. R., et al. (2025) · The International Journal of Cardiovascular Imaging · doi:10.1007/s10554-025-03520-9
Self-citationTao, X., Hou, X., Liu, Q., Pan, S., Jiang, X., Zhang, M., Qin, R., Wang, H., & Wang, Z. (2025) · Scientific Reports · doi:10.1038/s41598-025-22708-6
“As in previous studies, the extent and severity of lesions assessed by CCTA were significantly higher in DM patients than in non-DM patients 25,26 .”
Singh, N., Bajaj, N., Singh, B., Gupta, A., Sharma, P., Vaidya, R., Ghana, P., Kumar, A., Marwaha, M. P. S., Rao, S. S., et al. (2025) · Indian Journal of Aerospace Medicine · doi:10.25259/ijasm_9_2024
Advancing Coronary Risk Assessment Through Combined Radiomic, Mechanical, and Hemodynamic Analysis
Corti, A., Stefanati, M., Lissoni, V., Leccardi, M., Bruno, F., Depaoli, A., Cerveri, P., Migliavacca, F., Corino, V., Matas, J. F. R., et al. (2026) · Annals of Biomedical Engineering · doi:10.1007/s10439-026-03994-1
“Additionally, several CCTA-based risk scores have been proposed for coronary plaque stratification, based on stenosis degree, plaque composition, burden, or location [12], including the CAD-RADS [13], the CT-adapted Leaman score [14, 15], or the Leiden CCTA score [16].”
Tang, C. X., Zhou, F., Qiao, H. Y., Schoepf, U. J., Liu, T. Y., Liu, Y., & Zhang, L. J. (2026) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2026.07.011
- Authors
- van den Hoogen, I. J., van Rosendael, A. R., Lin, F. Y., Lu, Y., Dimitriu-Leen, A. C., Smit, J. M., Scholte, A. J. H. A., Achenbach, S., Al-Mallah, M. H., Andreini, D., Berman, D. S., Budoff, M. J., Cademartiri, F., Callister, T. Q., Chang, H.-J., Chinnaiyan, K., Chow, B. J. W., Cury, R. C., DeLago, A., Feuchtner, G., Hadamitzky, M., Hausleiter, J., Kaufmann, P. A., Kim, Y.-J., Leipsic, J. A., Maffei, E., Marques, H., de Araújo Gonçalves, P., Pontone, G., Raff, G. L., Rubinshtein, R., Villines, T. C., Gransar, H., Jones, E. C., Peña, J. M., Shaw, L. J., Min, J. K., & Bax, J. J.
- Affiliations
- NewYork–Presbyterian Hospital (US)
- Leiden University Medical Center (NL)
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- King Saud bin Abdulaziz University for Health Sciences (SA)
- Centro Cardiologico Monzino (IT)
- Cedars-Sinai Medical Center (US)
- The Lundquist Institute (US)
- Yonsei University (KR)
- Corewell Health William Beaumont University Hospital (US)
- University of Ottawa (CA)
- Capital Cardiology Associates (US)
- Innsbruck Medical University (AT)
- Deutsches Herzzentrum München (DE)
- University of Zurich (CH)
- Seoul National University Hospital (KR)
- University of British Columbia (CA)
- Hospital da Luz (PT)
- Technion – Israel Institute of Technology (IL)
- Walter Reed National Military Medical Center (US)
- Corresponding author
- Bax, Jeroen J.
- ORCID
- Lin, Fay Y.
- Smit, Jeff M.
- Scholte, Arthur J.H.A.
- Achenbach, Stephan
- Al-Mallah, Mouaz H.
- Andreini, Daniele
- Berman, Daniel S.
- Budoff, Matthew J.
- Cademartiri, Filippo
- Chang, Hyuk-Jae
- Chinnaiyan, Kavitha
- Chow, Benjamin J.W.
- Cury, Ricardo C.
- DeLago, Augustin
- Feuchtner, Gudrun
- Hadamitzky, Martin
- Kaufmann, Philipp A.
- Kim, Yong-Jin
- Leipsic, Jonathon A.
- Maffei, Erica
- Marques, Hugo
- Pontone, Gianluca
- Raff, Gilbert L.
- Villines, Todd C.
- Gransar, Heidi
- Peña, Jessica M.
- Shaw, Leslee J.
- Min, James K.
- Bax, Jeroen J.
- Venue
- Journal of Cardiovascular Computed Tomography
- Publisher
- Elsevier BV
- Published
- 2020-05
- Volume
- 14
- Issue
- 3
- Pages
- 251-257
- ISSN
- 1876-861X (ISSN-L)
- 1934-5925
- OpenAlex
- W2920695315
- Cited by
- 31
- References
- 43
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 6 · 2023: 3 · 2022: 5 · 2021: 8 · 2020: 3
- FWCI
- 2.59
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of cardiovascular computed tomography (publishedVersion)
- PubMed (publishedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
- Leiden Repository (Leiden University) (submittedVersion, cc-by)
- eScholarship (California Digital Library) (submittedVersion)
- mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion, cc-by-nc-nd)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion)
- Funders
- Medtronic
- GE Healthcare
- Dalio Foundation
- Michael Wolk Heart Foundation
- Biotronik
- National Institutes of Health (R01 HL115150)
- Leids Universitair Medisch Centrum
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Cardiac Imaging and Diagnostics
- Health Sciences › Medicine › Surgery › Coronary Interventions and Diagnostics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Keywords
- coronary artery disease, coronary CT angiography, diabetes mellitus, major adverse cardiac events, CAD-RADS, segment involvement score, all-cause mortality, myocardial infarction, propensity score matching, prognostic value, coronary artery stenosis
- MeSH terms
- Computed Tomography Angiography, Aged, Coronary Artery Disease, Diabetes Mellitus, Female, Humans, Male, Middle Aged, Predictive Value of Tests, Prognosis, Registries, Risk Factors, Severity of Illness Index, Case-Control Studies, Coronary Angiography, Disease Progression, Risk Assessment, Coronary Stenosis, Propensity Score, Multidetector Computed Tomography
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
