An Individualized, Alert-based Heartlogic Management Strategy Can Identify Patients At Risk For Impending Heart Failure Events

Abstract

Background HeartLogic is a diagnostic tool that uses multiple sensors (heart sounds, thoracic impedance, respiration, heart rate, patient activity) to track physiologic trends and combine them into one composite index designed to alert clinicians of patients at risk for impending heart failure events (HFE). While prior studies have shown an alert threshold of 16 to be predictive of HFE, there is currently no standard treatment protocol to manage these alerts. Objective To design a management algorithm and assess the utility of HeartLogic alerts in predicting HFE among patients with chronic systolic heart failure. Methods All patients with activated HeartLogic devices at a large academic center were followed prospectively for three months and monitored for elevated HeartLogic index defined as 16 or greater. All alerts were managed by the heart failure clinical team who assessed each patient via telephone call. Diuretic changes were made at the discretion of the clinical team. HFE, defined as unscheduled visits or heart failure hospitalizations occurring within 6 weeks after the initial alert were recorded. Results We identified a total of 80 patients with activated HeartLogic devices. A total of 38 patients (48%) had at least one HeartLogic alert during the study period. Of these, 26 patients (68%) appeared to have false positive alerts and did not require diuretic change nor had HFE, while 12 (32%) had heart failure symptoms requiring diuretic adjustment or urgent follow-up. Three of these 12 patients failed outpatient diuretic augmentation and were admitted for decompensated heart failure. Among the 42 patients (52%) who did not have an alert, only one patient had a HFE. Overall, HeartLogic demonstrated a sensitivity of 92%, specificity of 61%, positive predictive value of 32% and negative predictive value of 98%. Increasing HeartLogic alert threshold to >20 in this cohort would improve specificity to 90% and positive predictive value to 56%, thereby reducing staff burden, with an acceptable sensitivity (69%) and negative predictive value (94%). Conclusion This is the first study to evaluate the effects of an individualized HeartLogic threshold in an alert-based follow-up management strategy. This strategy identified actionable alerts leading to change in diuretic management. We do not recommend a standardized diuretic change algorithm for alerts given the heterogeneity of the index value and high false positive rate of alerts. Future studies are needed to determine if this management strategy leads to decrease in heart failure admissions. HeartLogic is a diagnostic tool that uses multiple sensors (heart sounds, thoracic impedance, respiration, heart rate, patient activity) to track physiologic trends and combine them into one composite index designed to alert clinicians of patients at risk for impending heart failure events (HFE). While prior studies have shown an alert threshold of 16 to be predictive of HFE, there is currently no standard treatment protocol to manage these alerts. To design a management algorithm and assess the utility of HeartLogic alerts in predicting HFE among patients with chronic systolic heart failure. All patients with activated HeartLogic devices at a large academic center were followed prospectively for three months and monitored for elevated HeartLogic index defined as 16 or greater. All alerts were managed by the heart failure clinical team who assessed each patient via telephone call. Diuretic changes were made at the discretion of the clinical team. HFE, defined as unscheduled visits or heart failure hospitalizations occurring within 6 weeks after the initial alert were recorded. We identified a total of 80 patients with activated HeartLogic devices. A total of 38 patients (48%) had at least one HeartLogic alert during the study period. Of these, 26 patients (68%) appeared to have false positive alerts and did not require diuretic change nor had HFE, while 12 (32%) had heart failure symptoms requiring diuretic adjustment or urgent follow-up. Three of these 12 patients failed outpatient diuretic augmentation and were admitted for decompensated heart failure. Among the 42 patients (52%) who did not have an alert, only one patient had a HFE. Overall, HeartLogic demonstrated a sensitivity of 92%, specificity of 61%, positive predictive value of 32% and negative predictive value of 98%. Increasing HeartLogic alert threshold to >20 in this cohort would improve specificity to 90% and positive predictive value to 56%, thereby reducing staff burden, with an acceptable sensitivity (69%) and negative predictive value (94%). This is the first study to evaluate the effects of an individualized HeartLogic threshold in an alert-based follow-up management strategy. This strategy identified actionable alerts leading to change in diuretic management. We do not recommend a standardized diuretic change algorithm for alerts given the heterogeneity of the index value and high false positive rate of alerts. Future studies are needed to determine if this management strategy leads to decrease in heart failure admissions.