The Role of Device Diagnostic Algorithms in the Assessment and Management of Patients with Systolic Heart Failure: A Review
Author(s) -
Andrew C.T. Ha,
Richard Leather,
Paul Novak,
Laurence D. Sterns,
Anthony Tang
Publication year - 2011
Publication title -
cardiology research and practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 35
eISSN - 2090-8016
pISSN - 2090-0597
DOI - 10.4061/2011/908921
Subject(s) - medicine , exacerbation , heart failure , cardiac resynchronization therapy , intensive care medicine , ambulatory , volume overload , psychological intervention , disease management , algorithm , disease , cardiology , ejection fraction , computer science , psychiatry , parkinson's disease
Hospitalization due to heart failure (HF) exacerbation represents a major burden in health care and portends a poor long-term prognosis for patients. As a result, there is considerable interest to develop novel tools and strategies to better detect onset of volume overload, as HF hospitalizations may be reduced if appropriate interventions can be promptly delivered. One such innovation is the use of device-based diagnostic parameters in HF patients with implantable cardioverter defibrillators (ICD) and/or cardiac resynchronization therapy (CRT) devices. These diagnostic algorithms can effectively monitor and detect changes in patients' HF status, as well as predict one's risk of HF hospitalization. This paper will review the role of these device diagnostics parameters in the assessment and management of HF patients in ambulatory settings. In addition, the integration of these novel algorithms in existing HF disease management models will be discussed
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