| Literature DB >> 28585183 |
Abstract
There are few proven therapies for heart failure with preserved ejection fraction (HFpEF). The lack of therapies, along with increased recognition of the disorder and its underlying pathophysiology, has led to the acknowledgement that HFpEF is heterogeneous and is not likely to respond to a one-size-fits-all approach. Thus, HFpEF is a prime candidate to benefit from a precision medicine approach. For this reason, we have assembled a compendium of papers on the topic of precision medicine in HFpEF in the Journal of Cardiovascular Translational Research. These papers cover a variety of topics relevant to precision medicine in HFpEF, including automated identification of HFpEF patients; machine learning, novel molecular approaches, genomics, and deep phenotyping of HFpEF; and clinical trial designs that can be used to advance precision medicine in HFpEF. In this introductory article, we provide an overview of precision medicine in HFpEF with the hope that the work described here and in the other papers in this special theme issue will stimulate investigators and clinicians to advance a more targeted approach to HFpEF classification and treatment.Entities:
Keywords: Cluster analysis; Heart failure with preserved ejection fraction; Machine learning; Precision medicine; Treatment
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Year: 2017 PMID： 28585183 PMCID： PMC5540576 DOI： 10.1007/s12265-017-9756-y
Source DB: PubMed Journal: J Cardiovasc Transl Res ISSN： 1937-5387 Impact factor: 4.132