Multiparameter diagnostic sensor measurements during clinically stable periods and worsening heart failure in ambulatory patients

Abstract

Aims This study aims to characterize the range of implantable device-based sensor values including heart sounds, markers of ventilation, thoracic impedance, activity, and heart rate for patients with heart failure (HF) when patients were deemed to be in clinically stable periods against the time course of acute decompensation and recovery from HF events. Methods and results The MultiSENSE trial followed 900 patients implanted with a COGNIS CRT-D for up to 1 year. Chronic, ambulatory diagnostic sensor data were collected and evaluated during clinically stable periods (CSP: unchanged NYHA classification, no adverse events, and weight change ≤2.27 kg), and in the timeframe leading up to and following HF events (HF admissions or unscheduled visits with intravenous HF treatment). Physiologic sensor data from 1667 CSPs occurring in 676 patients were compared with those data leading up to and following 192 HF events in 106 patients. Overall, the mean age was 66.6 years, and the population were predominantly male (73%). Patients were primarily in NYHA II (67%), with a mean LVEF of 29.6% and median NT-proBNP of 754.5 pg/mL. Sensor values during CSP were poorer in patients who had HF events during the study period than those without HF events, including first heart sound (S1: 2.18 ± 0.84 mG vs. 2.62 ± 0.95 mG,

Decongestive treatment adjustments in heart failure patients remotely monitored with a multiparametric implantable defibrillators algorithm

“…Confirming previous findings, 12 we showed that, at the time of device detection of the HF event, the sensed parameters that contribute to the calculation of the HeartLogic index presented changes from their baseline reference values. In the present analysis, the accelerometer‐based third heart sound, a surrogate of filling pressure, 16 significantly increased, as did the respiratory rate, which is known to facilitate the identification of patients at risk of worsening HF 17 .…”

“…Normality of distribution was tested by means of the Kolmogorov–Smirnov test. The time course of HeartLogic index and sensor changes surrounding the decongestive treatment adjustment were evaluated at four time‐points, as in a previous study 12 . A 30‐day baseline was compared both with a 7‐day preaction state measured up until the day before the diuretic augmentation, and with the state on the first day of the augmented therapy.…”

“…The time course of HeartLogic index and sensor changes surrounding the decongestive treatment adjustment were evaluated at four time‐points, as in a previous study. 12 A 30‐day baseline was compared both with a 7‐day preaction state measured up until the day before the diuretic augmentation, and with the state on the first day of the augmented therapy. Moreover, recovery was evaluated by recording sensor values over a 2‐week period beginning 2 weeks after diuretic augmentation and comparing these with the baseline values.…”

New auscultation: can we detect heart failure by auscultation ?

“…The first heart sound (S1) is caused by the closure of the atrioventricular valves, its amplitude is affected by the pressure gradient across the atrioventricular valve [7]. The previous studies showed that its amplitude was correlated with myocardial contractility…”

Performance of a HeartLogicTM Based Care Path in the Management of a Real-World Chronic Heart Failure Population

“…Apart from the MultiSENSE study (and several post hoc analyses from this study), data on the performance of the HeartLogic TM algorithm are scarce. A few studies showed that patients in alert status have an increased risk of congestion as compared to patients not in alert status (10)(11)(12)(13). HeartLogic TM alerts are frequently actionable and clinical action seemed to lower the decompensated heart failure event rate compared to a wait and see strategy (10,14).…”