BACKGROUND: The TIMI-AF score predicts poor outcomes in patients with atrial fibrillation (AF) and guides selection of anticoagulant therapy by identifying clinical benefit of direct oral anticoagulants (DOACs) or vitamin K antagonists (VKA). HYPOTHESIS: Our objective was to determine the ability to predict cardiovascular events according to the TIMI-AF score in a real-world population. METHODS: Retrospective observational study of VKA-naïve patients with AF was seen at a cardiology outpatient clinic in Spain between November 2012 and August 2014. We recorded adverse events (myocardial infarction, systemic embolism or stroke, major bleeding, and death). RESULTS: The study population comprised of 426 patients (50.7% men, mean age, 69 ± 14 years). The TIMI-AF score identified 372 patients (87.3%) with a low risk, 50 patients (11.7%) with an intermediate risk, and 4 patients (0.9%) with a high risk. After a mean follow-up of 423.4 ± 200.1 days, 37 patients (9%) experienced an adverse event. Patients with a TIMI-AF score ≥ 7 had a poorer cardiovascular prognosis (HR, 6.1; 95%CI, 3.2-11.7; P < 0.001). The area under the ROC curve of TIMI-AF was 0.755 (95%CI, 0.669-0.840; P < 0.001), which was greater than that of CHA2 DS2 VASc (0.641; 95%CI, 0.559-0.724; P = 0.004), HAS-BLED (0.666; 95%CI, 0.578-0.755; P < 0.001), and SAMeTT2 R2 (0.529; 95%CI, 0.422-0.636; P = 0.565). Similar results were obtained in relation to the net clinical outcome (life-threatening bleeding, disabling stroke, or all-cause mortality). CONCLUSIONS: The TIMI-AF risk score can identify patients who are at greater risk of cardiovascular events and a poor net clinical outcome with a better diagnostic yield than CHA2 DS2 VASc, HAS-BLED, and SAMeTT2 R2 .
BACKGROUND: The TIMI-AF score predicts poor outcomes in patients with atrial fibrillation (AF) and guides selection of anticoagulant therapy by identifying clinical benefit of direct oral anticoagulants (DOACs) or vitamin K antagonists (VKA). HYPOTHESIS: Our objective was to determine the ability to predict cardiovascular events according to the TIMI-AF score in a real-world population. METHODS: Retrospective observational study of VKA-naïve patients with AF was seen at a cardiology outpatient clinic in Spain between November 2012 and August 2014. We recorded adverse events (myocardial infarction, systemic embolism or stroke, major bleeding, and death). RESULTS: The study population comprised of 426 patients (50.7% men, mean age, 69 ± 14 years). The TIMI-AF score identified 372 patients (87.3%) with a low risk, 50 patients (11.7%) with an intermediate risk, and 4 patients (0.9%) with a high risk. After a mean follow-up of 423.4 ± 200.1 days, 37 patients (9%) experienced an adverse event. Patients with a TIMI-AF score ≥ 7 had a poorer cardiovascular prognosis (HR, 6.1; 95%CI, 3.2-11.7; P < 0.001). The area under the ROC curve of TIMI-AF was 0.755 (95%CI, 0.669-0.840; P < 0.001), which was greater than that of CHA2 DS2 VASc (0.641; 95%CI, 0.559-0.724; P = 0.004), HAS-BLED (0.666; 95%CI, 0.578-0.755; P < 0.001), and SAMeTT2 R2 (0.529; 95%CI, 0.422-0.636; P = 0.565). Similar results were obtained in relation to the net clinical outcome (life-threatening bleeding, disabling stroke, or all-cause mortality). CONCLUSIONS: The TIMI-AF risk score can identify patients who are at greater risk of cardiovascular events and a poor net clinical outcome with a better diagnostic yield than CHA2 DS2 VASc, HAS-BLED, and SAMeTT2 R2 .
Authors: Margaret C Fang; Alan S Go; Yuchiao Chang; Leila H Borowsky; Niela K Pomernacki; Natalia Udaltsova; Daniel E Singer Journal: J Am Coll Cardiol Date: 2011-07-19 Impact factor: 24.094
Authors: Ron Pisters; Deirdre A Lane; Robby Nieuwlaat; Cees B de Vos; Harry J G M Crijns; Gregory Y H Lip Journal: Chest Date: 2010-03-18 Impact factor: 9.410
Authors: J Polo García; V Barrios Alonso; C Escobar Cervantes; L Prieto Valiente; J M Lobos Bejarano; D Vargas Ortega; M Á Prieto Díaz; F J Alonso Moreno; A Barquilla García Journal: Semergen Date: 2016-07-13
Authors: Laurent Macle; John Cairns; Kori Leblanc; Teresa Tsang; Allan Skanes; Jafna L Cox; Jeff S Healey; Alan Bell; Louise Pilote; Jason G Andrade; L Brent Mitchell; Clare Atzema; David Gladstone; Mike Sharma; Subodh Verma; Stuart Connolly; Paul Dorian; Ratika Parkash; Mario Talajic; Stanley Nattel; Atul Verma Journal: Can J Cardiol Date: 2016-09-06 Impact factor: 5.223
Authors: Brian F Gage; Yan Yan; Paul E Milligan; Amy D Waterman; Robert Culverhouse; Michael W Rich; Martha J Radford Journal: Am Heart J Date: 2006-03 Impact factor: 4.749
Authors: Jonathan P Piccini; Susanna R Stevens; YuChiao Chang; Daniel E Singer; Yuliya Lokhnygina; Alan S Go; Manesh R Patel; Kenneth W Mahaffey; Jonathan L Halperin; Günter Breithardt; Graeme J Hankey; Werner Hacke; Richard C Becker; Christopher C Nessel; Keith A A Fox; Robert M Califf Journal: Circulation Date: 2012-12-03 Impact factor: 29.690
Authors: A John Camm; Gabriele Accetta; Giuseppe Ambrosio; Dan Atar; Jean-Pierre Bassand; Eivind Berge; Frank Cools; David A Fitzmaurice; Samuel Z Goldhaber; Shinya Goto; Sylvia Haas; Gloria Kayani; Yukihiro Koretsune; Lorenzo G Mantovani; Frank Misselwitz; Seil Oh; Alexander G G Turpie; Freek W A Verheugt; Ajay K Kakkar Journal: Heart Date: 2016-09-19 Impact factor: 5.994
Authors: Daniel E Singer; Yuchiao Chang; Leila H Borowsky; Margaret C Fang; Niela K Pomernacki; Natalia Udaltsova; Kristi Reynolds; Alan S Go Journal: J Am Heart Assoc Date: 2013-06-21 Impact factor: 5.501
Authors: Alejandro Isidoro Pérez Cabeza; Rafael Bravo Marques; Pedro Antonio Chinchurreta Capote; Francisco Ruiz Mateas; Christina L Fanola; Gabriel Rosas Cervantes; Jose Antonio González Correa; Almudena Valle Alberca; Fidel Mesa Prado; Sergio López Tejero; Christian Thomas Ruff Journal: Clin Cardiol Date: 2018-08-20 Impact factor: 2.882