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 .
Efficacy of fluid assessment based on intrathoracic impedance monitoring in patients with systolic heart failure.
BACKGROUND Previous studies have demonstrated that intrathoracic impedance monitoring ( IIM ) is associated with fluid overload . However , it remains unclear whether this new technology can predict heart failure ( HF ) before deterioration . Whether fluid status based on IIM predicts HF in patients with left ventricular ( LV ) systolic dysfunction was investigated . METHODS AND RESULTS A prospect i ve clinical observational study of 123 patients implanted with IIM-capable cardiac devices  was carried out . The primary endpoint was the positive predictive value ( PPV ) at 12 months . Secondary endpoints were a correlation between onset of HF and IIM , optimal threshold of fluid index and duration between the alert and HF . Complete follow-up clinical data were obtained from 111 patients . During the observational period , 168 alerts were confirmed from 68 patients . In patient-based analysis ( alert-based analysis ) , PPV was 33.8 % ( 33.9 % ) . Sensitivity , specificity and false positive was 67.6 % ( 83.8 % ) , 49.4 % ( 28.4 % ) and 50.6 % ( 71.6 % ) , respectively . Mean duration between the alert and HF event was 21.4 ± 6.1 days . On multivariate logistic analysis , maximum fluid index , LV ejection fraction and atrial fibrillation were independent predictors of HF events . The optimal cut-off value determined by receiver operating characteristic curve was 114-ohm·day with sensitivity and specificity of 89.5 % and 73.0 % , respectively . CONCLUSIONS IIM-based fluid index in patients with HF due to LV systolic dysfunction was effective in predicting worsening HF
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 .