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 .
Insights from internet-based remote intrathoracic impedance monitoring as part of a heart failure disease management program.
Changes in intrathoracic impedance ( Z ) leading to crossing of a derived fluid index ( FI ) threshold has been associated with heart failure ( HF ) hospitalization . The authors developed a remote monitoring program as part of HF disease management and prospect ively examined the feasibility and re source utilization of monitoring individuals with an implanted device capable of measuring Z. An HF nurse analyzed all transmitted data daily , as they were routinely uploaded as part of quarterly remote device monitoring , and called the patient if the FI crossed the threshold ( arbitrarily defined at 60 Omega ) to identify clinical ly relevant events ( CREs ) that occurred during this period ( eg , worsening dyspnea or increase in edema or weight ) . A total of 400 uploads were completed during the 4-month study period . During this period , 34 patients ( 18 % ) had an FI threshold crossing , averaging 0.52 FI threshold crossings per patient-year . Thirty-two of 34 patients contacted by telephone ( 94 % ) with FI threshold crossing had evidence of CREs during this period . However , only 6 ( 18 % ) had HF hospitalizations , 19 ( 56 % ) had reported changes in HF therapy , and 13 ( 38 % ) reported drug and /or dietary plan nonadherence . The average data analysis time required was 30 min daily when focusing on those with FI threshold crossing , averaging 8 uploads for review per working day and 5 telephone follow-ups per week . Our pilot observations suggested that Internet-based remote monitoring of Z trends from existing device interrogation uploads is feasible as part of a daily routine of HF disease management
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 .