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Kim A. Eagle

Researcher at University of Michigan

Publications -  852
Citations -  85694

Kim A. Eagle is an academic researcher from University of Michigan. The author has contributed to research in topics: Aortic dissection & Myocardial infarction. The author has an hindex of 129, co-authored 823 publications receiving 75160 citations. Previous affiliations of Kim A. Eagle include University of Wisconsin Hospital and Clinics & Spaulding Rehabilitation Hospital.

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Door-to-Balloon Time in Primary Percutaneous Coronary Intervention Is the 90-Minute Gold Standard an Unreachable Chimera?

TL;DR: It is likely that the next decade will be characterized by further expansion of primary PCI for acute STEMI in hospitals with cardiac catheterization laboratories, and time to treatment also plays a key role in survival with primary PCI.
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Comparison of baseline characteristics, management and outcome of patients with non-ST-segment elevation acute coronary syndrome in versus not in clinical trials.

TL;DR: Significant differences persist in baseline characteristics, treatment, and outcomes between patients enrolled and those not enrolled in clinical trials, and generalization of ACS clinical trials over the previous decade to the "real-world" patient may remain in question.
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Prophylactic Coronary Artery Revascularization for Elective Vascular Surgery: Study Design☆

TL;DR: In this paper, the authors describe the design of an ongoing randomized trial intended to test whether patients who require elective vascular surgery would benefit from preoperative coronary artery revascularization prior to the vascular procedure.
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Feasibility of postmortem device acquisition for potential reuse in underserved nations

TL;DR: Device donations from funeral homes and crematories appear to be a potential resource for device reutilization for those in need in underserved nations.
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Screening for cardiac disease in patients having noncardiac surgery

TL;DR: An approach for the cardiac evaluation of the patient having noncardiac surgery is presented, using a Bayesian approach and emphasizing how the information from further testing can be used.