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 .
A multicenter randomized controlled evaluation of automated home monitoring and telephonic disease management in patients recently hospitalized for congestive heart failure: the SPAN-CHF II trial.
BACKGROUND We performed a prospect i ve , r and omized investigation assessing the incremental effect of automated health monitoring ( AHM ) technology over and above that of a previously described nurse directed heart failure ( HF ) disease management program . The AHM system measured and transmitted body weight , blood pressure , and heart rate data as well as subjective patient self- assessment s via a st and ard telephone line to a central server . METHODS AND RESULTS A total of 188 consented and eligible patients were r and omized between intervention and control groups in 1:1 ratio . Subjects r and omized to the control arm received the Specialized Primary and Networked Care in Heart Failure ( SPAN-CHF ) heart failure disease management program . Subjects r and omized to the intervention arm received the SPAN-CHF disease management program in conjunction with the AHM system . The primary end point was prespecified as the relative event rate of HF hospitalization between intervention and control groups at 90 days . The relative event rate of HF hospitalization for the intervention group compared with controls was 0.50 ( 95%CI [ 0.25 - 0.99 ] , P = .05 ) . CONCLUSIONS Short-term reductions in the heart failure hospitalization rate were associated with the use of automated home monitoring equipment . Long-term benefits in this model remain to be studied
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 .