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 .
Sensitivity and positive predictive value of implantable intrathoracic impedance monitoring as a predictor of heart failure hospitalizations: the SENSE-HF trial.
AIMS Early recognition of impending decompensation and timely intervention may prevent heart failure ( HF ) hospitalization . We investigated the performance of OptiVol ® intrathoracic fluid monitoring for the prediction of HF events in chronic HF patients newly implanted with a device ( implantable cardioverter-defibrillator with or without cardiac resynchronization therapy ) . METHODS AND RESULTS SENSE-HF was a prospect i ve , multi-centre study that enrolled 501 patients . Phase I ( double blinded , 6 months ) determined the sensitivity and positive predictive value ( PPV ) of the OptiVol data in predicting HF hospitalizations . Of 58 adjudicated HF hospitalizations that occurred during the first 6 months in Phase I , 12 were predicted by OptiVol ( sensitivity = 20.7 % ) . Sensitivity appeared to be dynamic in nature and at the end of Phase I , had increased to 42.1 % . With 253 OptiVol detections , PPV for Phase I was 4.7 % . Phase II/III ( unblinded , 18 months ) determined the PPV of the first OptiVol Patient Alert for detection of worsening HF status with signs and /or symptoms of pulmonary congestion . A total of 233 patients noted such an OptiVol alert and for 210 , HF status was evaluated within 30 days . Heart failure status had worsened for 80 patients ( PPV = 38.1 % ) . CONCLUSIONS An intrathoracic impedance-derived fluid index had low sensitivity and PPV in the early period after implantation of a device in chronic HF patients  . Sensitivity improved within the first 6 months after implant . Further studies are needed to assess the place of this monitoring technology in the clinical management of patients with 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 .