Multiple cArdiac seNsors for mAnaGEment of Heart Failure (MANAGE-HF) - Phase I Evaluation of the Integration and Safety of the HeartLogic Multisensor Algorithm in Patients With Heart Failure

BACKGROUND

Patients with heart failure and reduced ejection fraction (HFrEF) suffer from a relapsing and remitting disease, where early treatment changes may improve outcomes. We assessed the clinical integration and safety of the HeartLogic multi-sensor index and alerts in heart failure care.

METHODS

The Multiple cArdiac seNsors for mAnaGEment of Heart Failure (MANAGE-HF) study enrolled 200 patients with HFrEF (< 35%), NYHA class II-III symptoms, implanted with a CRT-D or ICD, who had either a hospitalization for HF within 12 months or unscheduled visit for HF exacerbation within 90 days or an elevated natriuretic peptide concentration (BNP≥150 pg/mL or NT-proBNP≥600 pg/mL). This phase included development of an alert management guide and evaluated changes in medical treatment, natriuretic peptide levels, and safety.

RESULTS

Mean age of participants was 67 years, 68% were men, 81% were white, and 61% had a HF hospitalization in prior 12 months. During follow-up there were 585 alert cases with an average of 1.76 alert cases/pt-yr. HF medications were augmented during 74% of the alert cases. HF treatment augmentation within 2 weeks from an initial alert was associated with more rapid recovery of the HeartLogic Index. Five SAEs (0.015 per pt-year) occurred in relation to alert-prompted medication change. NTproBNP levels decreased from median of 1316 pg/mL at baseline to 743 pg/mL at 12 months (p<0.001).

CONCLUSIONS

HeartLogic alert management was safely implemented in HF care and may optimize HF management. This phase supports further evaluation in larger studies.

TRIAL REGISTRATION

ClinicalTrials.gov (NCT03237858).

Multiparameter diagnostic sensor measurements in heart failure patients presenting with SARS-CoV-2 infection

Aims

Implantable device‐based sensor measurements including heart sounds, markers of ventilation, and thoracic impedance have been shown to predict heart failure (HF) hospitalizations. We sought to assess how these parameters changed prior to COVID‐19 (Cov‐19) and how these compared with those presenting with decompensated HF or pneumonia.

Methods and results

This retrospective analysis explores patterns of changes in daily measurements by implantable sensors in 10 patients with Cov‐19 and compares these findings with those observed prior to HF (n = 88) and pneumonia (n = 12) hospitalizations from the MultiSENSE, PREEMPT‐HF, and MANAGE‐HF trials. The earliest sensor changes prior to Cov‐19 were observed in respiratory rate (6 days) and temperature (5 days). There was a three‐fold to four‐fold greater increase in respiratory rate, rapid shallow breathing index, and night heart rate compared with those presenting with HF or pneumonia. Furthermore, activity levels fell more in those presenting with Cov‐19, a change that was often sustained for some time. In contrast, there were no significant changes in 1st or 3rd heart sound (S₁ and S₃) amplitude in those presenting with Cov‐19 or pneumonia compared with the known changes that occur in HF decompensation.

Conclusions

Multi‐sensor device diagnostics may provide early detection of Cov‐19, distinguishable from worsening HF by an extreme and fast rise in respiratory rate along with no changes in S3.

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

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, P = 0.002), third heart sound (S3: 1.13 ± 0.36 mG vs. 0.91 ± 0.30 mG, P < 0.001), thoracic impedance (45.66 ± 8.78 Ohm vs. 50.33 ± 8.43 Ohm, P < 0.001), respiratory rate (19.09 ± 3.10 br/min vs. 17.66 ± 2.39 br/min, P = 0.002), night time heart rate (73.39 ± 8.36 b.p.m. vs. 69.56 ± 8.09 b.p.m., P = 0.001), patient activity (1.69 ± 1.84 h vs. 2.56 ± 2.20 h, P = 0.006), and HeartLogic index (11.07 ± 12.14 vs. 5.31 ± 5.13, P = 0.001). Sensor parameters measured worsening status leading up to HF events with recovery of values following treatment.

Conclusions

Device‐based physiologic sensors not only revealed progressive worsening leading up to HF events but also differentiated patients at increased risk of HF events when presumed to be clinically stable.

Ambulatory respiratory rate trends identify patients at higher risk of worsening heart failure in implantable cardioverter defibrillator and biventricular device recipients: a novel ambulatory parameter to optimize heart failure management

Purpose

Respiratory distress is the primary driver for heart failure (HF) hospitalization. Implantable pacemakers and defibrillators are capable of monitoring respiratory rate (RR) in ambulatory HF patients. We investigated changes in RR prior to HF hospitalizations and its near-term risk stratification power.

Methods

NOTICE-HF was an international multi-center study. Patients were implanted with an implantable cardioverter defibrillator or cardiac resynchronization therapy defibrillator, capable of trending daily maximum, median, and minimum RR (maxRR, medRR, minRR). RR from 120 patients with 9 months of follow-up was analyzed. One-tailed Student’s t test was used to compare RR values prior to HF events to baseline defined as 4 weeks prior to the events. A Cox regression model was used to calculate the hazard ratios (HR) for the 30-day HF hospitalization risk based on RR values in the preceding month.

Results

Daily maxRR, medRR, and minRR were significantly elevated prior to HF events compared to baseline (ΔmaxRR 1.8 ± 3.0; p = 0.02; ΔmedRR, 2.1 ± 2.8; p = 0.007; ΔminRR, 1.5 ± 2.1, p = 0.008). Risk of experiencing HF events within 30-days was increased if the standard deviation of medRR over the preceding month was above 1.0 br/min (HR = 12.3, 95 % confidence interval (CI) 2.57–59, p = 0.002). The risk remained high after adjusting for clinical variables that differed at enrollment.

Conclusion

Ambulatory daily respiratory rate trends may be a valuable addition to standard management for HF patients.