Percorrer por autor "Hadamitzky, Martin"
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- Prognostic value of aI-based quantitative coronary CTA vs human reader-based visual assessment: results from the CONFIRM2 registryPublication . Rosendael, Alexander van; Nakanishi, Rine; Bax, Jeroen J.; Pontone, Gianluca; Mushtaq, Saima; Buechel, Ronny R.; Gräni, Christoph; Feuchtner, Gudrun; Lacaita, Pietro G.; Patel, Amit R.; Singulane, Cristiane C.; Choi, Andrew D.; Al-Mallah, Mouaz; Andreini, Daniele; Karlsberg, Ronald P.; Cho, Geoffrey W.; Rochitte, Carlos E.; Alasnag, Mirvat; Hamdan, Ashraf; Cademartiri, Filippo; Maffei, Erica; Marques, Hugo; Gonçalves, Pedro de Araújo; Gupta, Himanshu; Hadamitzky, Martin; Khalique, Omar; Kalra, Dinesh; Mills, James D.; Nurmohamed, Nick S.; Knaapen, Paul; Budoff, Matthew; Shaikh, Kashif; Martin, Enrico; German, David M.; Ferencik, Maros; Oehler, Andrew C.; Deaño, Roderick; Nagpal, Prashant; Assen, Marly van; Cecco, Carlo N. de; Kamperidis, Vasileios; Foldyna, Borek; Brendel, Jan M.; Cheng, Victor Y.; Branch, Kelley R.; Bittencourt, Marcio; Bhatti, Sabha; Polsani, Venkateshwar; Wesbey, George; Cardoso, Rhanderson; Blankstein, Ron; Delago, Augustin; Pursnani, Amit; Alsaid, Amro; Singh, Vasvi; Aquino, Melissa; Park, Jisuk; Danad, IbrahimBackground: The severity and extent of whole heart coronary plaque volume and stenosis can be reliably measured by artificial intelligence–guided quantitative coronary computed tomography angiography (AI-QCT). Limited data are available on the potential incremental prognostic value compared with currently recommended qualitative coronary computed tomography angiography (CTA) reads and the coronary artery calcium score (CACS). Objectives: The aim of this study was to evaluate the prognostic value of AI-QCT compared with human coronary CTA reads, including the CAD-RADS (Coronary Artery Disease–Reporting and Data System), CACS, and the modified Duke Index. Methods: CONFIRM2 (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) is a multicenter, international, observational cohort study of patients undergoing clinically indicated coronary CTA with follow-up for major adverse cardiac events (MACE). Asymptomatic patients and those with cardiac history were excluded. Coronary artery disease presence, extent, and composition were quantified by AI-QCT across the coronary tree, yielding 24 patient-, vessel-, and plaque-level variables. On the basis of prior analyses, noncalcified plaque burden and diameter stenosis were identified as the strongest predictors and combined for statistical modeling as “AI-QCT.” Comparator computed tomography scores included CAD-RADS, CACS, and the modified Duke Index, whereas clinical predictors were summarized in the risk factor–weighted clinical likelihood score. Area under the curve (AUC) and continuous net reclassification index (NRI) were calculated to assess the incremental value. The primary endpoint was MACE (death, myocardial infarction [MI], stroke, heart failure, late revascularization, or hospital stay for unstable angina), and the secondary endpoint was death or MI. Results: In 1,916 patients with all risk scores available, 87 (4.5%) MACE and 27 (1.4%) death/MI events occurred during 3 years of follow-up. There was a stepwise risk increase with higher coronary artery disease classifications with CAD-RADS and CACS. The addition of AI-QCT significantly improved risk stratification for MACE compared with CAD-RADS (AUC: 0.81 vs 0.79; P < 0.001 and NRI: 0.47; P < 0.001), CACS (AUC: 0.79 vs 0.70; P < 0.001 and NRI 0.61; P < 0.001), the modified Duke Index (AUC: 0.81 vs 0.76; P < 0.001 and NRI: 0.52; P < 0.001), and CAD-RADS + CACS model (AUC: 0.81 vs 0.79; P = 0.004 and NRI: 0.54; P < 0.001). AI-QCT also improved discrimination when results were adjusted for the risk factor–weighted clinical likelihood and for the prediction of death/MI. Excluding 195 patients with severe stenosis (?70%), in a multivariable model of CAD-RADS and AI-QCT, only AI-QCT was significantly associated with MACE and death/MI, and AI-QCT significantly improved risk stratification compared with CAD-RADS for MACE (AUC: 0.77 vs 0.72; P < 0.001 and NRI: 0.54; P < 0.001) and death/MI (AUC: 0.81 vs 0.73; P = 0.011 and NRI: 0.69; P = 0.001). Conclusions: AI-QCT provided incremental prognostic information compared with CAD-RADS 2.0, CACS, and the modified Duke Index for the prediction of MACE as well as the secondary endpoint of death or nonfatal MI.
- Risk factors based vessel-specific prediction for stages of coronary artery disease using Bayesian quantile regression machine learning method: results from the PARADIGM registryPublication . Park, Hyung Bok; Lee, Jina; Hong, Yongtaek; Byungchang, So; Kim, Wonse; Lee, Byoung K.; Lin, Fay Y.; Hadamitzky, Martin; Kim, Yong Jin; Conte, Edoardo; Andreini, Daniele; Pontone, Gianluca; Budoff, Matthew J.; Gottlieb, Ilan; Chun, Eun Ju; Cademartiri, Filippo; Maffei, Erica; Marques, Hugo; Gonçalves, Pedro de A.; Leipsic, Jonathon A.; Shin, Sanghoon; Choi, Jung H.; Virmani, Renu; Samady, Habib; Chinnaiyan, Kavitha; Stone, Peter H.; Berman, Daniel S.; Narula, Jagat; Shaw, Leslee J.; Bax, Jeroen J.; Min, James K.; Kook, Woong; Chang, Hyuk JaeBackground and Hypothesis: The recently introduced Bayesian quantile regression (BQR) machine-learning method enables comprehensive analyzing the relationship among complex clinical variables. We analyzed the relationship between multiple cardiovascular (CV) risk factors and different stages of coronary artery disease (CAD) using the BQR model in a vessel-specific manner. Methods: From the data of 1,463 patients obtained from the PARADIGM (NCT02803411) registry, we analyzed the lumen diameter stenosis (DS) of the three vessels: left anterior descending (LAD), left circumflex (LCx), and right coronary artery (RCA). Two models for predicting DS and DS changes were developed. Baseline CV risk factors, symptoms, and laboratory test results were used as the inputs. The conditional 10%, 25%, 50%, 75%, and 90% quantile functions of the maximum DS and DS change of the three vessels were estimated using the BQR model. Results: The 90th percentiles of the DS of the three vessels and their maximum DS change were 41%–50% and 5.6%–7.3%, respectively. Typical anginal symptoms were associated with the highest quantile (90%) of DS in the LAD; diabetes with higher quantiles (75% and 90%) of DS in the LCx; dyslipidemia with the highest quantile (90%) of DS in the RCA; and shortness of breath showed some association with the LCx and RCA. Interestingly, High-density lipoprotein cholesterol showed a dynamic association along DS change in the per-patient analysis. Conclusions: This study demonstrates the clinical utility of the BQR model for evaluating the comprehensive relationship between risk factors and baseline-grade CAD and its progression.
- Sex and age-specific interactions of coronary atherosclerotic plaque onset and prognosis from coronary computed tomographyPublication . Rosendael, Sophie E. Van; Bax, A. Maxim; Lin, Fay Y.; Achenbach, Stephan; Andreini, Daniele; Budoff, Matthew J.; Cademartiri, Filippo; Callister, Tracy Q.; Chinnaiyan, Kavitha; Chow, Benjamin J. W.; Cury, Ricardo C.; DeLago, Augustin J.; Feuchtner, Gudrun; Hadamitzky, Martin; Hausleiter, Joerg; Kaufmann, Philipp A.; Kim, Yong Jin; Leipsic, Jonathon A.; Maffei, Erica; Marques, Hugo; Gonçalves, Pedro de Araújo; Pontone, Gianluca; Raff, Gilbert L.; Rubinshtein, Ronen; Villines, Todd C.; Chang, Hyuk Jae; Berman, Daniel S.; Min, James K.; Bax, Jeroen J.; Shaw, Leslee J.; Rosendael, Alexander R. VanAims: The totality of atherosclerotic plaque derived from coronary computed tomography angiography (CCTA) emerges as a comprehensive measure to assess the intensity of medical treatment that patients need. This study examines the differences in age onset and prognostic significance of atherosclerotic plaque burden between sexes. Methods and results: From a large multi-center CCTA registry the Leiden CCTA score was calculated in 24 950 individuals. A total of 11 678 women (58.5 ± 12.4 years) and 13 272 men (55.6 ± 12.5 years) were followed for 3.7 years for major adverse cardiovascular events (MACE) (death or myocardial infarction). The age where the median risk score was above zero was 12 years higher in women vs. men (64-68 years vs. 52-56 years, respectively, P < 0.001). The Leiden CCTA risk score was independently associated with MACE: score 6-20: HR 2.29 (1.69-3.10); score > 20: HR 6.71 (4.36-10.32) in women, and score 6-20: HR 1.64 (1.29-2.08); score > 20: HR 2.38 (1.73-3.29) in men. The risk was significantly higher for women within the highest score group (adjusted P-interaction = 0.003). In pre-menopausal women, the risk score was equally predictive and comparable with men. In post-menopausal women, the prognostic value was higher for women [score 6-20: HR 2.21 (1.57-3.11); score > 20: HR 6.11 (3.84-9.70) in women; score 6-20: HR 1.57 (1.19-2.09); score > 20: HR 2.25 (1.58-3.22) in men], with a significant interaction for the highest risk group (adjusted P-interaction = 0.004). Conclusion: Women developed coronary atherosclerosis approximately 12 years later than men. Post-menopausal women within the highest atherosclerotic burden group were at significantly higher risk for MACE than their male counterparts, which may have implications for the medical treatment intensity.