CONCLUSIONS Current evidence suggests that D-PA may be useful for assessing physical activity and predicting clinical outcomes in patients with cardiovascular implantable electronic devices when combined with other device parameters .
BACKGROUND  Physical activity  is predictive of cardiovascular outcomes in patients with cardiovascular implantable electronic devices , yet it is not regularly assessed in routine care .
Current-generation cardiovascular implantable electronic devices , however , continuously monitor patient activity through a built-in accelerometer , which provides new opportunities to remotely assess patient activity , detect changes in clinical status , and incorporate these data in risk stratification models .
This review critically examines the literature on device-measured physical activity ( D-PA ) , with a focus on identifying method ological issues that may affect interpretation of study results .
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 )
CONCLUSIONS Current evidence suggests that D-PA may be useful for assessing physical activity and predicting clinical outcomes in patients with cardiovascular implantable electronic devices when combined with other device parameters .
BACKGROUND  Physical activity  is predictive of cardiovascular outcomes in patients with cardiovascular implantable electronic devices , yet it is not regularly assessed in routine care .
Current-generation cardiovascular implantable electronic devices , however , continuously monitor patient activity through a built-in accelerometer , which provides new opportunities to remotely assess patient activity , detect changes in clinical status , and incorporate these data in risk stratification models .
This review critically examines the literature on device-measured physical activity ( D-PA ) , with a focus on identifying method ological issues that may affect interpretation of study results .