J
John P. Boehmer
Researcher at Penn State Milton S. Hershey Medical Center
Publications - 162
Citations - 16317
John P. Boehmer is an academic researcher from Penn State Milton S. Hershey Medical Center. The author has contributed to research in topics: Heart failure & Cardiac resynchronization therapy. The author has an hindex of 42, co-authored 145 publications receiving 15087 citations. Previous affiliations of John P. Boehmer include University of Alabama at Birmingham & Rush University Medical Center.
Papers
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Journal ArticleDOI
Biventricular pacing in congestive heart failure: a boost toward finer living.
Jerry C. Luck,Deborah L. Wolbrette,John P. Boehmer,Paula J. Ulsh,David H. Silber,Gerald V. Naccarelli +5 more
TL;DR: The acute hemodynamic studies suggest that resynchronization pacing therapy may predict a positive long-term benefit for many patients with congestive heart failure.
Journal ArticleDOI
Comparison of pierce-donachy (pd) and tci left ventricular assist systems as bridge to transplant – an institutional experience
Sanjay M. Mehta,D Souza,John P. Boehmer,David H. Silber,Dawn Christensen,Walter E. Pae,Benjamin Sun +6 more
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Utilization of remote monitoring among patients receiving cardiac resynchronization therapy and comparison between Asia and the Americas
Niraj Varma,Yusuke Kondo,Seung-Jung Park,Angelo Auricchio,M. Gold,John P. Boehmer,Ulhas M. Pandurangi,Eiichi Watanabe,Kwang Ho Lee,Jagmeet P. Singh +9 more
TL;DR: In this article , the authors proposed a method for remote monitoring of patients with cardiac implantable electronic devices (i.e., pacemakers) in order to improve patient outcomes and reduce global health inequities.
Journal ArticleDOI
Adjudication of mortality events in a heart failure-arrhythmia trial by a multiparameter descriptive method: comparison with methods used in heart failure trials and methods used in arrhythmia trials.
John P. Boehmer,Mark D. Carlson,Teresa De Marco,Brian E. Jaski,Steven L. Higgins,Charles Kennergren,Andrew E. Epstein +6 more
TL;DR: A descriptive method for the classification of death retains more data and allows for comparison among trials using different classification schemes, which may allow greater mechanistic insight into study populations that have diverse and frequently multiple etiologies of death.