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 .
Combined heart failure device diagnostics identify patients at higher risk of subsequent heart failure hospitalizations: results from PARTNERS HF (Program to Access and Review Trending Information and Evaluate Correlation to Symptoms in Patients With Heart Failure) study.
OBJECTIVES We sought to determine the utility of combined heart failure ( HF ) device diagnostic information to predict clinical deterioration of HF in patients with systolic left ventricular dysfunction . BACKGROUND Some implantable devices continuously monitor HF device diagnostic information , but data are limited on the ability of combined HF device diagnostics to predict HF events . METHODS The PARTNERS HF ( Program to Access and Review Trending Information and Evaluate Correlation to Symptoms in Patients With Heart Failure ) was a prospect i ve , multicenter observational study in patients receiving cardiac resynchronization therapy ( CRT ) implantable cardioverter-defibrillators .  HF events were independently adjudicated . A combined HF device diagnostic algorithm was developed on an independent data set . The algorithm was considered positive if a patient had 2 of the following abnormal criteria during a 1-month period : long atrial fibrillation duration , rapid ventricular rate during atrial fibrillation , high ( > or = 60 ) fluid index , low patient activity , abnormal autonomics ( high night heart rate or low heart rate variability ) , or notable device therapy ( low CRT pacing or implantable cardioverter-defibrillator shocks ) , or if they only had a very high ( > or = 100 ) fluid index . We used univariate and multivariable analyses to determine predictors of subsequent HF events within a month . RESULTS We analyzed data from 694 CRT defibrillator patients who were followed for 11.7 + /- 2 months . Ninety patients had 141 adjudicated HF  hospitalizations with pulmonary congestion  at least 60 days after implantation . Patients with a positive combined HF device diagnostics had a 5.5-fold increased risk of HF hospitalization with pulmonary signs or symptoms within the next month ( hazard ratio : 5.5 , 95 % confidence interval : 3.4 to 8.8 , p < 0.0001 ) , and the risk remained high after adjusting for clinical variables ( hazard ratio : 4.8 , 95 % confidence interval : 2.9 to 8.1 , p < 0.0001 ) . CONCLUSIONS Monthly review of HF device diagnostic data identifies patients at a higher risk of HF hospitalizations within the subsequent month . ( PARTNERS HF : Program to Access and Review Trending Information and Evaluate Correlation to Symptoms in Patients With Heart Failure ; NCT00279955 )
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 .