AI Article Synopsis

  • Hospitalizations for heart failure (HF) worsen patients' long-term health outcomes and increase healthcare costs.
  • There is a growing focus on developing new methods to detect early signs of volume overload to potentially reduce HF hospitalizations through timely intervention.
  • This paper explores how device-based diagnostics in implantable cardioverter defibrillators (ICDs) and cardiac resynchronization therapy (CRT) devices can help monitor HF status and predict hospitalization risks, along with their integration into current management strategies for HF patients.

Article Abstract

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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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3088115PMC
http://dx.doi.org/10.4061/2011/908921DOI Listing

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