AIMS: The assessment of bleeding risk in patients with coronary artery disease (CAD) is clinically important. We recently developed the Total Thrombus-Formation Analysis System (T-TAS) for the quantitative analysis of thrombus formation using microchips with thrombogenic surfaces. Here, we assessed the utility of T-TAS parameters in predicting 1-year bleeding events in patients with CAD. METHODS: The study subjects were 561 consecutive patients who underwent coronary angiography (CAG) between August 2013 and September 2016 for suspected CAD. Blood samples collected at the time of CAG were used for T-TAS to compute the area under the curve (AUC) (AR10-AUC30) in the AR chip. Patients were divided into three groups according to AR10-AUC30 (low: ≤ 1603, intermediate, and high: ＞1765, n=187 each). One-year bleeding events were defined by the Platelet Inhibition and Patient Outcomes criteria. RESULTS: Bleeding occurred in 21 (3.7%) patients and was classified as major (8 [1.4%]) and minor (13 [2.3%]). The AR10-AUC30 levels were significantly lower in the bleeding group than the non-bleeding group (median [interquartile range] 1590 [1442-1734] vs. 1687 [1546-1797], p=0.04). Univariate Cox regression analysis demonstrated that low AR10-AUC30 , high prothrombin time-international normalized ratio levels, and diabetes correlated with bleeding events. Multivariate Cox regression analysis identified low AR10-AUC30 levels as a significant determinant of bleeding events. Kaplan-Meier survival curves showed a higher rate of bleeding events in the low than the high AR10-AUC30 group (p=0.007). CONCLUSIONS: The results highlight the potential usefulness of the AR10-AUC30 levels in the prediction of 1-year bleeding events in patients with CAD treated with various antithrombotic therapies.
AIMS: The assessment of bleeding risk in patients with coronary artery disease (CAD) is clinically important. We recently developed the Total Thrombus-Formation Analysis System (T-TAS) for the quantitative analysis of thrombus formation using microchips with thrombogenic surfaces. Here, we assessed the utility of T-TAS parameters in predicting 1-year bleeding events in patients with CAD. METHODS: The study subjects were 561 consecutive patients who underwent coronary angiography (CAG) between August 2013 and September 2016 for suspected CAD. Blood samples collected at the time of CAG were used for T-TAS to compute the area under the curve (AUC) (AR10-AUC30) in the AR chip. Patients were divided into three groups according to AR10-AUC30 (low: ≤ 1603, intermediate, and high: ＞1765, n=187 each). One-year bleeding events were defined by the Platelet Inhibition and Patient Outcomes criteria. RESULTS:Bleeding occurred in 21 (3.7%) patients and was classified as major (8 [1.4%]) and minor (13 [2.3%]). The AR10-AUC30 levels were significantly lower in the bleeding group than the non-bleeding group (median [interquartile range] 1590 [1442-1734] vs. 1687 [1546-1797], p=0.04). Univariate Cox regression analysis demonstrated that low AR10-AUC30 , high prothrombin time-international normalized ratio levels, and diabetes correlated with bleeding events. Multivariate Cox regression analysis identified low AR10-AUC30 levels as a significant determinant of bleeding events. Kaplan-Meier survival curves showed a higher rate of bleeding events in the low than the high AR10-AUC30 group (p=0.007). CONCLUSIONS: The results highlight the potential usefulness of the AR10-AUC30 levels in the prediction of 1-year bleeding events in patients with CAD treated with various antithrombotic therapies.
Authors: Philippe Gabriel Steg; Kurt Huber; Felicita Andreotti; Harald Arnesen; Dan Atar; Lina Badimon; Jean-Pierre Bassand; Raffaele De Caterina; John A Eikelboom; Dietrich Gulba; Martial Hamon; Gérard Helft; Keith A A Fox; Steen D Kristensen; Sunil V Rao; Freek W A Verheugt; Petr Widimsky; Uwe Zeymer; Jean-Philippe Collet Journal: Eur Heart J Date: 2011-06-29 Impact factor: 29.983
Authors: Roxana Mehran; Stuart Pocock; Eugenia Nikolsky; George D Dangas; Tim Clayton; Bimmer E Claessen; Adriano Caixeta; Frederick Feit; Steven V Manoukian; Harvey White; Michel Bertrand; E Magnus Ohman; Helen Parise; Alexandra J Lansky; A Michael Lincoff; Gregg W Stone Journal: JACC Cardiovasc Interv Date: 2011-06 Impact factor: 11.195
Authors: Gregory Y H Lip; Stephan Windecker; Kurt Huber; Paulus Kirchhof; Francisco Marin; Jurriën M Ten Berg; Karl Georg Haeusler; Giuseppe Boriani; Davide Capodanno; Martine Gilard; Uwe Zeymer; Deirdre Lane; Robert F Storey; Hector Bueno; Jean-Philippe Collet; Laurent Fauchier; Sigrun Halvorsen; Maddalena Lettino; Joao Morais; Christian Mueller; Tatjana S Potpara; Lars Hvilsted Rasmussen; Andrea Rubboli; Juan Tamargo; Marco Valgimigli; Jose L Zamorano Journal: Eur Heart J Date: 2014-08-25 Impact factor: 29.983
Authors: Freek W A Verheugt; Steven R Steinhubl; Martial Hamon; Harald Darius; Philippe Gabriel Steg; Marco Valgimigli; Steven P Marso; Sunil V Rao; Anthony H Gershlick; A Michael Lincoff; Roxana Mehran; Gregg W Stone Journal: JACC Cardiovasc Interv Date: 2011-02 Impact factor: 11.195
Authors: Timothy D Kinnaird; Eugenio Stabile; Gary S Mintz; Cheol Whan Lee; Daniel A Canos; Natalie Gevorkian; Ellen E Pinnow; Kenneth M Kent; Augusto D Pichard; Lowell F Satler; Neil J Weissman; Joseph Lindsay; Shmuel Fuchs Journal: Am J Cardiol Date: 2003-10-15 Impact factor: 2.778
Authors: Lars Wallentin; Richard C Becker; Andrzej Budaj; Christopher P Cannon; Håkan Emanuelsson; Claes Held; Jay Horrow; Steen Husted; Stefan James; Hugo Katus; Kenneth W Mahaffey; Benjamin M Scirica; Allan Skene; Philippe Gabriel Steg; Robert F Storey; Robert A Harrington; Anneli Freij; Mona Thorsén Journal: N Engl J Med Date: 2009-08-30 Impact factor: 91.245