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 .
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
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 .
Randomized trial of a daily electronic home monitoring system in patients with advanced heart failure: the Weight Monitoring in Heart Failure (WHARF) trial.
BACKGROUND Heart failure treatment guidelines emphasize daily weight monitoring for patients with heart failure , but data to support this practice are lacking . Using a technology-based heart failure monitoring system , we determined whether daily reporting of weight and symptoms in patients with advanced heart failure would reduce rehospitalization and mortality rates despite aggressive guideline -driven heart failure care . METHODS This was a r and omized , controlled trial . Patients hospitalized with New York Heart Association class III or IV heart failure , with a left ventricular ejection fraction < or = 35 % were r and omized to receive heart failure program care or heart failure program care plus the AlereNet system ( Alere Medical , Reno , Nev ) and followed-up for 6 months . The primary end point was 6-month hospital readmission rate . Secondary end points included mortality , heart failure hospitalization readmission rate , emergency room visitation rate , and quality of life . RESULTS Two hundred eighty patients from 16 heart failure centers across the United States were r and omized : 138 received the  AlereNet system and 142 received st and ard care .  Mean age was 59 + /- 15 years and 68 % were male . The population had very advanced heart failure , New York Heart Association class III ( 75 % ) or IV ( 25 % ) , as evidence d by serum norepinepherine levels , 6-minute walk distance and outcomes .  No differences in hospitalization rates were observed . There was a 56.2 % reduction in mortality ( P < .003 ) for patients r and omized to the AlereNet group . CONCLUSIONS This is the largest multicenter , r and omized trial of a technology-based daily weight and symptom-monitoring system for patients with advanced heart failure . Despite no difference in the primary end point of rehospitalization rates , mortality was significantly reduced for patients r and omized to the AlereNet system without an increase in utilization , despite specialized and aggressive heart failure care in both groups
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 .
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
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 .