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Journal of Cardiovascular Nursing:
doi: 10.1097/JCN.0b013e3182784106
Articles

Device Diagnostics and Early Identification of Acute Decompensated Heart Failure: A Systematic Review

Leslie Blair, Tara RN, DNP, CHFN

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Abstract

Background: Traditional methods of heart failure (HF) management are based on reactive strategies to treat late indicators of decompensated HF. Advances in monitoring methods have become available with the evolution of implantable cardioverter-defibrillators and cardiac-resynchronization therapy devices. These devices provide new diagnostic data and remote monitoring capabilities that allow clinicians to proactively monitor patients for earlier signs of worsening HF. The integration of data obtained from implantable cardioverter-defibrillator and cardiac-resynchronization therapy technology could improve outpatient HF care, potentially leading to decreased readmission rates and improved patient outcomes.

Objective: This review will synthesize the literature regarding the efficacy of device diagnostic data and the usability of the data in the clinical setting.

Methods: Articles for review were obtained using Cumulative Index to Nursing and Allied Health Literature, MEDLINE, PubMed, and ClinicalTrials.gov.

Results: Device diagnostics showed strong correlation with established HF biomarkers and hemodynamic measures. The findings from this review indicate that device diagnostic parameters predict impending HF much earlier than traditional methods of monitoring do. Device diagnostics are also more accurate in the early prediction of HF when compared with noninvasive objective measures, particularly when multiple parameters are combined and monitored for trends. Device diagnostics possess a distinct advantage over traditional methods of monitoring for HF because they allow clinicians to remotely monitor the status of their HF patients without relying on patient compliance for data entry and reporting.

Conclusions: Studies regarding the efficacy of device diagnostic parameters suggest that their integration into clinical practice will provide a more accurate and reliable mechanism for assisting clinicians in risk stratifying and predicting potential episodes of decompensated HF.

© 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins

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