Mintu P. Turakhia
Stanford University
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Featured researches published by Mintu P. Turakhia.
Annals of Internal Medicine | 2011
James V. Freeman; Ruo P. Zhu; Douglas K Owens; Alan M. Garber; David W. Hutton; Alan S. Go; Paul J. Wang; Mintu P. Turakhia
BACKGROUND Warfarin reduces the risk for ischemic stroke in patients with atrial fibrillation (AF) but increases the risk for hemorrhage. Dabigatran is a fixed-dose, oral direct thrombin inhibitor with similar or reduced rates of ischemic stroke and intracranial hemorrhage in patients with AF compared with those of warfarin. OBJECTIVE To estimate the quality-adjusted survival, costs, and cost-effectiveness of dabigatran compared with adjusted-dose warfarin for preventing ischemic stroke in patients 65 years or older with nonvalvular AF. DESIGN Markov decision model. DATA SOURCES The RE-LY (Randomized Evaluation of Long-Term Anticoagulation Therapy) trial and other published studies of anticoagulation. The cost of dabigatran was estimated on the basis of pricing in the United Kingdom. TARGET POPULATION Patients aged 65 years or older with nonvalvular AF and risk factors for stroke (CHADS₂ score ≥1 or equivalent) and no contraindications to anticoagulation. TIME HORIZON Lifetime. PERSPECTIVE Societal. INTERVENTION Warfarin anticoagulation (target international normalized ratio, 2.0 to 3.0); dabigatran, 110 mg twice daily (low dose); and dabigatran, 150 mg twice daily (high dose). OUTCOME MEASURES Quality-adjusted life-years (QALYs), costs (in 2008 U.S. dollars), and incremental cost-effectiveness ratios. RESULTS OF BASE-CASE ANALYSIS The quality-adjusted life expectancy was 10.28 QALYs with warfarin, 10.70 QALYs with low-dose dabigatran, and 10.84 QALYs with high-dose dabigatran. Total costs were
Stroke | 2012
Karen L. Furie; Larry B. Goldstein; Gregory W. Albers; Pooja Khatri; Ron Neyens; Mintu P. Turakhia; Tanya N. Turan; Kathryn A. Wood
143 193 for warfarin,
Circulation | 2011
Abhimanyu Uberoi; Nikhil A. Jain; Marco V Perez; Anthony Weinkopff; Euan A. Ashley; David Hadley; Mintu P. Turakhia; Victor F. Froelicher
164 576 for low-dose dabigatran, and
JAMA Cardiology | 2016
Jonathan C. Hsu; Thomas M. Maddox; Kevin F. Kennedy; David F. Katz; Lucas N. Marzec; Steven A. Lubitz; Anil K. Gehi; Mintu P. Turakhia; Gregory M. Marcus
168 398 for high-dose dabigatran. The incremental cost-effectiveness ratios compared with warfarin were
American Heart Journal | 2014
Supriya Shore; Evan P. Carey; Mintu P. Turakhia; Cynthia A. Jackevicius; Fran Cunningham; Louise Pilote; Steven M. Bradley; Thomas M. Maddox; Gary K. Grunwald; Anna E. Barón; John S. Rumsfeld; Paul D. Varosy; Preston M Schneider; Lucas N. Marzec; P. Michael Ho
51 229 per QALY for low-dose dabigatran and
Journal of the American College of Cardiology | 2012
Christine C. Welles; Ivy A. Ku; Damon M. Kwan; Mary A. Whooley; Nelson B. Schiller; Mintu P. Turakhia
45 372 per QALY for high-dose dabigatran. RESULTS OF SENSITIVITY ANALYSIS The model was sensitive to the cost of dabigatran but was relatively insensitive to other model inputs. The incremental cost-effectiveness ratio increased to
Circulation | 2017
Ben Freedman; John Camm; Hugh Calkins; Jeff S. Healey; Mårten Rosenqvist; Jiguang Wang; Christine M. Albert; Craig S. Anderson; Sotiris Antoniou; Emelia J. Benjamin; Giuseppe Boriani; Johannes Brachmann; Axel Brandes; Tze-Fan Chao; David Conen; Johan Engdahl; Laurent Fauchier; David A Fitzmaurice; Leif Friberg; Bernard J. Gersh; David J Gladstone; Taya V. Glotzer; Kylie Gwynne; Graeme J. Hankey; Joseph Harbison; Graham S Hillis; Mellanie True Hills; Hooman Kamel; Paulus Kirchhof; Peter R. Kowey
50 000 per QALY at a cost of
American Heart Journal | 2011
Christine C. Welles; Mary A. Whooley; Beeya Na; Peter Ganz; Nelson B. Schiller; Mintu P. Turakhia
13.70 per day for high-dose dabigatran but remained less than
JAMA | 2015
Supriya Shore; P. Michael Ho; Anne Lambert-Kerzner; Thomas J. Glorioso; Evan P. Carey; Fran Cunningham; Lisa Longo; Cynthia A. Jackevicius; Adam J. Rose; Mintu P. Turakhia
85 000 per QALY over the full range of model inputs evaluated. The cost-effectiveness of high-dose dabigatran improved with increasing risk for stroke and intracranial hemorrhage. LIMITATION Event rates were largely derived from a single randomized clinical trial and extrapolated to a 35-year time frame from clinical trials with approximately 2-year follow-up. CONCLUSION In patients aged 65 years or older with nonvalvular AF at increased risk for stroke (CHADS₂ score ≥1 or equivalent), dabigatran may be a cost-effective alternative to warfarin depending on pricing in the United States. PRIMARY FUNDING SOURCE American Heart Association and Veterans Affairs Health Services Research & Development Service.
Circulation-arrhythmia and Electrophysiology | 2015
Mintu P. Turakhia; Paul D. Ziegler; Susan K. Schmitt; Yuchiao Chang; Jun Fan; Claire T. Than; Edmund K. Keung; Daniel E. Singer
The rate of stroke among adults with atrial fibrillation (AF) varies widely, ranging between 1% and 20% annually (mean 4.5% per year) depending on comorbidities and a patient’s history of prior cerebrovascular events.1 Stratification of stroke risk is important, because the major risk of antithrombotic medications used to lower the incidence of AF-related stroke is bleeding. For warfarin, this involves balancing a bleeding risk of 1% to 12% per year against the risk of ischemic events, with its use generally reserved for individuals at greatest thromboembolic risk.1–3 The advent of several new antithrombotic agents offers alternatives to warfarin and may lower the threshold for thromboembolic risk for initiating therapy in patients with AF. In this update to the American Heart Association/American Stroke Association (AHA/ASA) “Guidelines for the Primary Prevention of Stroke”4 and the prevention of stroke in patients with stroke or transient ischemic attack (TIA),5 we review recent trials testing the safety and efficacy of a thrombin inhibitor (dabigatran) and 2 factor Xa inhibitors (rivaroxaban and apixaban) in preventing stroke in patients with AF, and we revise management recommendations.4,5 Recommendations follow the AHA’s and the American College of Cardiology’s methods of classifying the level of certainty of the treatment effect and the class of evidence (Table 1). View this table: Table 1. Applying Classification of Recommendations and Level of Evidence ### Risk Stratification The absolute risk of stroke varies 20-fold among AF patients according to age and associated vascular comorbidities. Several stroke risk stratification schemes have been developed and validated.6–8 These, however, can yield differing results.9 Current AHA guidelines use the CHADS2 stratification scheme7 (CHADS2 is an acronym for Congestive heart failure, Hypertension, Age ≥75 years, Diabetes mellitus, and prior Stroke or TIA). The CHADS2 score was derived from independent …