Physical activity measured with implanted devices predicts patient outcome in chronic heart failure

Ambulatory Risk Stratification for Worsening Heart Failure in Patients with Reduced and Preserved Ejection Fraction Using Diagnostic Parameters Available in Implantable Cardiac Monitors

BACKGROUND

Ambulatory risk stratification for worsening heart failure (HF) using diagnostics measured by insertable cardiac monitors (ICM) may depend on the left ventricular ejection fraction (LVEF). We evaluated risk stratification performance in patients with reduced versus preserved LVEF.

METHODS

ICM patients with a history of HF events (HFEs) were included from the Optum® de-identified Electronic Health Record dataset merged with ICM device-collected data during 2007-2021. ICM measures nighttime heart rate (NHR), heart rate variability (HRV), atrial fibrillation (AF) burden, rate during AF, and activity duration (ACT) daily. Each diagnostic was categorized into high, medium, or low risk using previously defined features. HFEs were HF-related inpatient, observation unit, or emergency department stays with IV diuresis administration. Patients were divided into two cohorts: LVEF ≤ 40% and LVEF > 40%. A marginal Cox proportional hazards model compared HFEs for different risk groups.

RESULTS

A total of 1020 ICM patients with 18,383 follow-up months and 301 months with HFEs (1.6%) were included. Monthly evaluations with a high risk were 2.3, 4.2, 5.0, and 4.5 times (p < 0.001 for all) more likely to have HFEs in the next 30 days compared to those with a low risk for AF, ACT, NHR, and HRV, respectively. HFE rates were higher for patients with LVEF > 40% compared to LVEF ≤ 40% (2.0% vs. 1.3%), and the relative risk between high-risk and low-risk for each diagnostic parameter was higher for patients with LVEF ≤ 40%.

CONCLUSIONS

Diagnostics measured by ICM identified patients at risk for impending HFEs. Patients with preserved LVEF showed a higher absolute risk, and the relative risk between risk groups was higher in patients with reduced LVEF.

PRecision Event Monitoring for PatienTs with Heart Failure using HeartLogic (PREEMPT-HF) study design and enrolment

AIMS

The HeartLogic multisensor index has been found to be a sensitive predictor of worsening heart failure (HF). However, there is limited data on this index's association and its constituent sensors with HF readmissions.

METHODS AND RESULTS

The PREEMPT-HF study is a global, multicentre, prospective, observational, single-arm, post-market study. HF patients with an implantable defibrillator device or cardiac resynchronization therapy with defibrillator with HeartLogic capabilities were eligible if sensor data collection was turned on and the HeartLogic feature was not enabled. Thus, the HeartLogic Index/alert and heart sounds sensor trends were unavailable via the LATITUDE remote monitoring system to clinicians (blinded). Evaluation of subject medical records at 6 months and a final in-clinic visit at 12 months was required for collection of all-cause hospitalizations and HF outpatient visits. The purpose of this study is exploratory, no formal hypothesis tests are planned, and no adjustment for multiple testing will be performed. A total of 2183 patients were enrolled at 103 sites between June 2018 and June 2020. A significant proportion of the patients were implanted with implantable defibrillator devices (39%) versus cardiac resynchronization therapy with defibrillator (61%); were female (27%); over 65 (61%); New York Heart Association class I (13%), II (53%), and III (33%); ejection fraction < 25% (21%); ischaemic (50%); and with a history of renal dysfunction (23%).

CONCLUSIONS

The PREEMPT study will provide clinical data and blinded sensor trends for the characterization of sensor changes with HF readmission, tachyarrhythmias, and event subgroups. These data may help to refine the clinical use of HeartLogic and to improve patient outcomes.

Wearable sensors for prediction of intraamniotic infection in women with preterm premature rupture of membranes: a prospective proof of principle study

PURPOSE

To evaluate the use of wearable sensors for prediction of intraamniotic infection in pregnant women with PPROM.

MATERIALS AND METHODS

In a prospective proof of principle study, we included 50 patients diagnosed with PPROM at the University Hospital Zurich between November 2017 and May 2020. Patients were instructed to wear a bracelet during the night, which measures physiological parameters including wrist skin temperature, heart rate, heart rate variability, and breathing rate. A two-way repeated measures ANOVA was performed to evaluate the difference over time of both the wearable device measured parameters and standard clinical monitoring values, such as body temperature, pulse, leucocytes, and C-reactive protein, between women with and without intraamniotic infection.

RESULTS

Altogether, 23 patients (46%) were diagnosed with intraamniotic infection. Regarding the physiological parameters measured with the bracelet, we observed a significant difference in breathing rate (19 vs 16 per min, P < .01) and heart rate (72 vs 67 beats per min, P = .03) in women with intraamniotic infection compared to those without during the 3 days prior to birth. In parallel to these changes standard clinical monitoring values were significantly different in the intraamniotic infection group compared to women without infection in the 3 days preceding birth.

CONCLUSION

Our results suggest that wearable sensors are a promising, noninvasive, patient friendly approach to support the early detection of intraamniotic infection in women with PPROM. However, confirmation of our findings in larger studies is required before implementing this technique in standard clinical management.

Changes in physical activity around the time of major adverse cardiac events in patients with implantable cardioverter-defibrillators

BACKGROUND

With modern implantable cardioverter-defibrillators (ICDs), biometric measures including physical activity have become readily available to physicians. However, despite the increased availability, applications of these data to the clinical setting remain poorly studied. We sought to investigate whether changes in physical activity occur preceding and following cardiac events in patients with ICDs.

METHODS

We reviewed the electronic medical records of patients with ICDs implanted for any indication in 2018 and 2019 in the University of Pennsylvania health system. Patients with ICDs that reported physical activity were included in the study only if they experienced major adverse cardiac event(s) (MACE) that were preceded by at least 6 months without MACE after device implantation.

RESULTS

Seventy-four of the 827 charts reviewed met inclusion criteria. Baseline activity levels from 6 to 2 months prior to MACE were 2.18-2.21 h/day. In the month prior to MACE, average activity decreased significantly to 2.09 h/day, and subsequently decreased again during the calendar month in which MACE occurred to 1.96 h/day. The lowest average monthly activity levels occurred in the month after MACE, with incremental but non-significant recovery occurring over the subsequent 2 months.

CONCLUSIONS

In a cohort of ICD recipients, a significant decrease in physical activity was observed in the month preceding MACE. To our knowledge, this is the first study that observes time-dependent changes in activity in relation to MACE in a generalizable cohort of ICD recipients. ICD activity monitoring in patients at high risk for MACE may enhance patient care.

Effect of Personalized Accelerated Pacing on Quality of Life, Physical Activity, and Atrial Fibrillation in Patients With Preclinical and Overt Heart Failure With Preserved Ejection Fraction: The myPACE Randomized Clinical Trial

Importance

Patients with heart failure with preserved ejection fraction (HFpEF) with a pacemaker may benefit from a higher, more physiologic backup heart rate than the nominal 60 beats per minute (bpm) setting.

Objective

To assess the effects of a moderately accelerated personalized backup heart rate compared with 60 bpm (usual care) in patients with preexisting pacemaker systems that limit pacemaker-mediated dyssynchrony.

Design, Setting, and Participants

This blinded randomized clinical trial enrolled patients with stage B and C HFpEF from the University of Vermont Medical Center pacemaker clinic between June 2019 and November 2020. Analysis was modified intention to treat.

Interventions

Participants were randomly assigned to personalized accelerated pacing or usual care and were followed up for 1 year. The personalized accelerated pacing heart rate was calculated using a resting heart rate algorithm based on height and modified by ejection fraction.

Main Outcomes and Measures

The primary outcome was the serial change in Minnesota Living with Heart Failure Questionnaire (MLHFQ) score. Secondary end points were changes in N-terminal pro-brain natriuretic peptide (NT-proBNP) levels, pacemaker-detected physical activity, atrial fibrillation from baseline, and adverse clinical events.

Results

Overall, 107 participants were randomly assigned to the personalized accelerated pacing (n = 50) or usual care (n = 57) groups. The median (IQR) age was 75 (69-81) years, and 48 (48%) were female. Over 1-year follow-up, the median (IQR) pacemaker-detected heart rate was 75 (75-80) bpm in the personalized accelerated pacing arm and 65 (63-68) bpm in usual care. MLHFQ scores improved in the personalized accelerated pacing group (median [IQR] baseline MLHFQ score, 26 [8-45]; at 1 month, 15 [2-25]; at 1 year, 9 [4-21]; P < .001) and worsened with usual care (median [IQR] baseline MLHFQ score, 19 [6-42]; at 1 month, 23 [5-39]; at 1 year, 27 [7-52]; P = .03). In addition, personalized accelerated pacing led to improved changes in NT-proBNP levels (mean [SD] decrease of 109 [498] pg/dL vs increase of 128 [537] pg/dL with usual care; P = .02), activity levels (mean [SD], +47 [67] minutes per day vs -22 [35] minutes per day with usual care; P < .001), and device-detected atrial fibrillation (27% relative risk reduction compared with usual care; P = .04) over 1-year of follow-up. Adverse clinical events occurred in 4 patients in the personalized accelerated pacing group and 11 patients in usual care.

Conclusions and Relevance

In this study, among patients with HFpEF and pacemakers, treatment with a moderately accelerated, personalized pacing rate was safe and improved quality of life, NT-proBNP levels, physical activity, and atrial fibrillation compared with the usual 60 bpm setting.

Trial Registration

ClinicalTrials.gov Identifier: NCT04721314.

Device-evaluated autonomic nervous function for predicting ventricular arrhythmias and all-cause mortality in patients who underwent cardiac resynchronization therapy-defibrillator

Introduction: Autonomic nervous system (ANS) function quantified by heart rate variability (HRV) was associated with long-term prognosis, but it was rarely used in the evaluation of patients with heart failure, especially those with cardiac resynchronization therapy-defibrillator (CRT-D) implantation. This study aimed to describe the changes in ANS function among patients who underwent CRT-D with remote home monitoring function, and explore predictive value of HRV for ventricular tachyarrhythmias (VTAs) and all-cause mortality. Method: Patients who underwent CRT-D implantation were included. Device-measured all-day HR, night-time HR, and HRV (measured by the standard deviation of the atrial-atrial sensed intervals) were used to quantify ANS function. Multivariate Cox proportional hazards models were fitted to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) of VTAs or all-cause mortality in relation to ANS function at baseline and 6 months post-implantation. The cutoff value was determined using restrictive cubic splines. Multivariable logistic regression was further established to determine factors influencing postoperative HRV. Results: A total of 170 patients treated with CRT-D were eligible for analysis. During a median follow-up period of 50.8 months, 61 patients died and 69 patients experienced at least one spontaneous episode of VTAs. At 6 months after CRT implantation, 114 patients showed improvement in HRV, increasing from 66.4 ± 19.4 ms to 76.7 ± 21.2 ms. The postoperative HRV was associated with both all-cause mortality (HRs: 0.983; 95% CI: 0.968 to 0.998, p = 0.012) and VTAs (HRs: 0.973; 95% CI: 0.954 to 0.993, p = 0.008), and the relative risk would significantly increase when the postoperative HRV lower than 75 ms. After adjusting for basic ANS function and possible influencing factors, patients without diabetes (p = 0.018) and with higher daily physical activity (p = 0.041) could maintain higher postoperative HRV after CRT implantation. Conclusion: More than two-thirds of heart failure patients showed improvement in ANS function following CRT treatment. However, patients with diabetes and low daily physical activity levels have difficulty maintaining a higher postoperative HRV, which is associated with a worse clinical outcome.

The mediation function of resting heart rate in how physical activity improves all-cause mortality: Continuous and automatic measurement via cardiac implantable electronic devices

Background

Physical activity (PA) and resting heart rate (RHR) are connected with all-cause mortality. Moreover, there was an inverse correlation between PA and RHR. However, the causal relationship between PA, RHR, and long-term mortality has been rarely evaluated and quantified, particularly the mediation effect of RHR in the association between PA and all-cause mortality.

Objective

To describe the relationship between PA and RHR when consistently measured via cardiac implantable electronic devices (CIED) and further explore the mediation effect of PA on all-cause mortality through RHR.

Materials and methods

Patients who underwent CIED implantation and received remote home monitoring services were included. During the first 30–60 days after CIED implantation, daily PA and RHR were continuously measured and automatically transmitted by CIED. The primary endpoint was all-cause mortality. The multiple linear regression model was used to confirm the relationship between PA and RHR. The predictive values of both PA and RHR for all-cause mortality were assessed by multivariable Cox proportional hazards models. The causal mediation model was further established to verify and quantify the mediation effect of RHR in the association between PA and all-cause mortality.

Results

A total of 730 patients with CIED were included. The mean daily PA and RHR were 10.7 ± 5.7% and 61.3 ± 9.1 bpm, respectively. During a mean follow-up period of 55.8 months, 187 (26.5%) death was observed. A negative linear relationship between PA and RHR was demonstrated in the multiple regression model (β = −0.260; 95% CI: −0.377 to −0.143, p < 0.001). Multivariable Cox proportional hazards analysis showed that both lower levels of PA (HR = 0.907; 95% CI: 0.878–0.936, p < 0.001) and higher RHR (HR = 1.016; 95% CI: 1.001–1.032, P = 0.031) were independent risk factors of all-cause mortality. Causal mediation analysis further confirmed and quantified the mediation function of RHR in the process of PA improving all-cause mortality (mediation proportion = 3.9%; 95% CI: 0.2–10.0%, p = 0.036).

Conclusion

The effects of the higher level of PA on improving life prognosis may be partially mediated through RHR among patients with CIED. It indicates that changes in the autonomic nervous function during postoperative rehabilitation exercises should get more attention.

Physical Activity in Cardiac Implantable Electronic Device Recipients During the COVID-19 Pandemic

OBJECTIVE

To characterize the physical activity (PA) level in patients with a cardiac implantable electronic device (CIED) during the coronavirus disease 2019 (COVID-19) pandemic and compare PA level during the pandemic in 2020 with the year 2019.

METHODS

We performed a retrospective analysis of PA activity in individuals implanted with a CIED enrolled in the BIOTRONIK CERTITUDE Registry. Mean daily and weekly PA from January to August 2020 was compared with 2019.

RESULTS

A total of 21,660 individuals met eligibility criteria, with mean age of 72.6±11.6 years, and 12,411 (57.3)% were males. A significant decline in daily PA was noted following the pandemic declaration in 2020, with a maximum mean reduction of -24.5±36.3 minutes (P<.0001) observed in April 2020 compared with 2019. PA in 2020 increased from April to May (120.6±67.4 to 129.2±70.9 min/d). PA was lower for all months in 2020 compared with 2019. The decrease in PA was observed in all prespecified groups based on age, sex, type of device, and region of the country.

CONCLUSION

After the declaration of the coronavirus disease 2019 pandemic, a significant decline in daily PA was observed in individuals with a CIED. Future investigation to establish the impact of this reduction on short and long-term cardiovascular outcomes is required.

Developments in Exercise Capacity Assessment in Heart Failure Clinical Trials and the Rationale for the Design of METEORIC-HF

Heart failure with reduced ejection fraction (HFrEF) is a highly morbid condition for which exercise intolerance is a major manifestation. However, methods to assess exercise capacity in HFrEF vary widely in clinical practice and in trials. We describe advances in exercise capacity assessment in HFrEF and a comparative analysis of how various therapies available for HFrEF impact exercise capacity. Current guideline-directed medical therapy has indirect effects on cardiac performance with minimal impact on measured functional capacity. Omecamtiv mecarbil is a novel selective cardiac myosin activator that directly increases cardiac contractility and in a phase 3 cardiovascular outcomes study significantly reduced the primary composite end point of time to first heart failure event or cardiovascular death in patients with HFrEF. The objective of the METEORIC-HF trial (Multicenter Exercise Tolerance Evaluation of Omecamtiv Mecarbil Related to Increased Contractility in Heart Failure) is to assess the effect of omecamtiv mecarbil versus placebo on multiple components of functional capacity in HFrEF. The primary end point is to test the effect of omecamtiv mecarbil compared with placebo on peak oxygen uptake as measured by cardiopulmonary exercise testing after 20 weeks of treatment. METEORIC-HF will provide state-of-the-art assessment of functional capacity by measuring ventilatory efficiency, circulatory power, ventilatory anaerobic threshold, oxygen uptake recovery kinetics, daily activity, and quality-of-life assessment. Thus, the METEORIC-HF trial will evaluate the potential impact of increased myocardial contractility with omecamtiv mecarbil on multiple important measures of functional capacity in ambulatory patients with symptomatic HFrEF. Registration: URL: https://clinicaltrials.gov; Unique identifier: NCT03759392.

Implantable device measured objective daily physical activity as a predictor of long-term all-cause mortality and cardiac death in patients with age > 75 years and high risk of sudden cardiac death: a cohort study : Physical activity and patients over 75 years old

BACKGROUND

To study the relationship between objective daily physical activity (PA), as measured by implantable cardioverter defibrillators (ICDs)/cardiac resynchronization therapy defibrillators (CRTDs), and long-term prognoses in patients with age > 75 years at high risk of sudden cardiac death (SCD).

METHODS

In total, 133 patients with age > 75 years old (age 79.52 ± 3.68 years) in the SUMMIT study were retrospectively analysed. The major endpoint was all-cause mortality, and the minor endpoint was cardiac death.

RESULTS

The mean follow-up time was 57.1 ± 24.2 months (range: from 4 to 96 months). In total, 46 all-cause mortality and 23 cardiac death events occurred. The receiver operating characteristic curve indicated a baseline PA cut-off value of 6.47% (93 min/day) can predict all-cause mortality in patients with age > 75 years, with an area under the curve of 0.670 (95% confidence interval (CI): 0.573-0.767, P = 0.001). The sensitivity was 67.4%, and the specificity was 66.7%. Patients with baseline PA ≤ 6.47% had higher rates of all-cause mortality (51.7% vs 20.5%, P < 0.001) and cardiac death (25.0% vs 11.0%, P = 0.040). The estimated Kaplan-Meier survival curves showed that patients with PA ≤ 6.47% had an increased cumulative incidence of all-cause mortality (Log-rank P < 0.0001) and cardiac death (Log-rank P = 0.0067). Multivariate Cox regression analysis showed that PA ≤ 6.47% was an independent predictor of all-cause mortality (hazard ratio (HR) 3.137, 95% CI: 1.667-5.904, P < 0.001) and cardiac death (HR value 3.345, 95% CI: 1.394-8.028, P = 0.007).

CONCLUSIONS

Daily PA of about 1.5 h was associated with lower all-cause mortality and cardiac death risk in patients with age > 75 years and high risk of SCD with ICDs/CRTDs. PA monitoring may aid in long-term management of older patients at high risk of SCD.

Objectively measured physical activity in patients with heart failure: a sub-analysis from the HF-Wii study

AIMS

Physical activity (PA) is important in patients with heart failure (HF) to improve health outcomes. The adherence to PA is low, and therefore, novel approaches are necessary to increase PA. We aimed to determine the difference in PA in patients with HF who have access to exergaming compared to patients who received motivational support and to explored predictors of a clinically relevant change in non-sedentary time between baseline and 3 months.

METHODS AND RESULTS

In total, 64 patients (mean age 69 ± 9 years, 27% female) wore an accelerometer 1 week before and 1 week after the intervention. Data were analysed using logistic regression analysis. Patients spent 9 h and 43 min (±1 h 23 min) during waking hours sedentary. There were no significant differences in PA between patients who received an exergame intervention or motivational support. In total, 30 of 64 patients achieved a clinically relevant increase in non-sedentary time. Having grandchildren [odds ratio (OR) 7.43 P = 0.03], recent diagnosis of HF (OR 0.93 P = 0.02), and higher social motivation (OR 2.31 P = 0.03) were independent predictors of a clinically relevant increase of non-sedentary time.

CONCLUSION

Clinicians should encourage their patients to engage in alternative approaches to improve PA and reduce sedentary habits. Future exergaming interventions should target individuals with chronic HF who have low social motivation and a low level of light PA that may benefit most from exergaming. Also (non-familial), intergenerational interaction is important to enabling patients in supporting patients in becoming more active.

Multiparameter Monitoring with a Wearable Cardioverter Defibrillator

A wearable cardioverter-defibrillator (WCD) is a temporary treatment option for patients at high risk for sudden cardiac death (SCD) and for patients who are temporarily not candidates for an implantable cardioverter defibrillator (ICD). In addition, the need for telemedical concepts in the detection and treatment of heart failure (HF) and its arrhythmias is growing. The WCD has evolved from a shock device detecting malignant ventricular arrhythmias (VA) and treating them with shocks to a heart-failure-monitoring device that captures physical activity and cardioacoustic biomarkers as surrogate parameters for HF to help the treating physician surveil and guide the HF therapy of each individual patient. In addition to its important role in preventing SCD, the WCD could become an important tool in heart failure treatment by helping prevent HF events by detecting imminent decompensation via remote monitoring and monitoring therapy success.

Association of device-measured physical activity with peak oxygen consumption measured by cardiopulmonary exercise testing in patients with cardiac implantable electronic devices

PURPOSE

Cardiac implantable electronic devices (CIEDs) offer diagnostic information such as device-measured physical activity (PA). Peak oxygen consumption (VO₂) measured by cardiopulmonary exercise testing (CPET) is the most objective variable showing exercise capacity. The purpose of this study was to investigate the relationship between these 2 variables.

METHODS

We retrospectively studied consecutive patients with CIEDs undergoing CPET between April 1, 2018, and January 31, 2021. These patients were divided into 2 groups: patients with peak VO₂ ≤ 14 ml/kg/min (low peak VO₂ group) and those showing peak VO₂ > 14 ml/kg/min (high peak VO₂ group). The peak device-measured PA was compared between the 2 groups. The relationship between the peak device-measured PA and peak VO₂ was also investigated.

RESULTS

There were 50 and 51 patients in the low and high peak VO₂ groups, respectively. The peak device-measured PA, which was expressed in units of hours/day, was significantly lower in the low peak VO₂ group than in the high peak VO₂ group (3.06, interquartile range [2.43-4.00] vs. 5.50, interquartile range [4.04-6.70] p < 0.01). The peak device-measured PA and peak VO₂ showed a significant positive correlation (Spearman's ρ = 0.53; p < 0.01). Furthermore, receiver operating characteristic curve analysis showed that a peak device-measured PA > 3.87 h/day could predict high peak VO₂ (80.4%, sensitivity; 72.0%, specificity). In multivariate linear regression analysis, peak device-measured PA was an independent predictor of peak VO₂ (regression coefficient, 0.61; 95% confidence interval, 0.33-0.89; p < 0.01).

CONCLUSIONS

Peak device-measured PA was significantly associated with peak VO₂.

Evaluation of Medicare Claims for the Development of Heart Failure Diagnostics

BACKGROUND

Although claims data provide a large and efficient source of clinical events, validation is needed prior to use in heart failure (HF) diagnostic development.

METHODS AND RESULTS

Data from the Multisensor Chronic Evaluations in Ambulatory Heart Failure Patients (MultiSENSE) study, used to create the HeartLogic HF diagnostic, were linked with fee-for-service (FFS) Medicare claims. Events were matched by patient ID and date, and agreement was calculated between claims primary HF diagnosis codes and study event adjudication. HF events (HFEs) were defined as inpatient visits, or outpatient visits with intravenous decongestive therapy. Diagnostic performance was measured as HFE-detection sensitivity and false-positive rate (FPR). Linkage of 791 MultiSENSE subjects returned 320 FFS patients with an average follow-up duration of 0.94 years. Although study and claims deaths matched exactly (n = 14), matching was imperfect between study hospitalizations and acute inpatient claims events. Of 239 total events, 165 study hospitalizations (69%) matched inpatient claims events, 28 hospitalizations matched outpatient claims events (12%), 14 hospitalizations were study-unique (6%), and 32 inpatient events were claims-unique (13%). Inpatient HF classification had substantial agreement with study adjudication (κ = 0.823). Diagnostic performance was not different between claims and study events (sensitivity = 75.6% vs 77.6% and FPR = 1.539 vs 1.528 alerts/patient-year). HeartLogic-detected events contributed to > 90% of the HFE costs used for evaluation.

CONCLUSIONS

Acceptable event matching, good agreement of claims diagnostic codes with adjudication, and equivalent diagnostic performance support the validity of using claims for HF diagnostic development.

Wearable Cardioverter-Defibrillator-Measured Step Count for the Surveillance of Physical Fitness during Cardiac Rehabilitation

Background: The wearable cardioverter–defibrillator (WCD) has a built-in accelerometer, which allows tracking of patients’ physical activity by remote monitoring. It is unclear whether WCD-measured physical activity, step count, and heart rate correlate with established tools for the assessment of cardiopulmonary fitness such as the 6-min walk test (6MWT). Objective: To correlate measurements of patient physical activity through the WCD with a supervised 6MWT during in-patient cardiac rehabilitation (CR) and to allow their use as surrogate parameters of cardiopulmonary fitness in an out-patient setting. Methods: Consecutive patients with a history of WCD use treated at our center and an in-patient CR following an index hospitalization were included. Baseline characteristics, measurements of WCD accelerometer (median daily step count, median daily activity level), median daily heart rate, and clinically supervised 6MWT at admission and discharge of CR were obtained. Results: Forty-one patients with a mean age of 55.5 (±11.5) years were included. Thirty-five patients (85.4%) were male and 28 patients (68%) had a primary prophylactic WCD-indication. The most common underlying heart diseases were ischemic heart disease (24 patients 58.6%) and dilated cardiomyopathy (13 patients, 31.7%). Median CR duration was 20 (IQR 19.75–26.25) days. 6MWT distance increased from a mean of 329 m (±107) to 470 m (±116) during CR (p < 0.0001). The median daily step count and activity level increased significantly, from 5542 steps (IQR 3718–7055) to 8778 (IQR 6229–12,920, p < 0.0001) and median 117 × 10⁶ (IQR 96 × 10⁶–142 × 10⁶) threshold value exceedance (TVE) to 146 × 10⁶ TVE (IQR 110 × 10⁶–169 × 10⁶, p < 0.0001), respectively. The median heart rate was 74.9 bpm (IQR 65.8–84.5) and 70.2 (IQR 64.1–77.3, p = 0.09) at admission and discharge, respectively. Of all three parameters, median daily step count showed the best correlation to the results of the 6MWT at admission and discharge (r = 0.32, p = 0.04 and 0.37, p = 0.02, respectively). Conclusions: Remote monitoring of median daily step count as assessed by the WCD’s accelerometer showed positive correlation with the 6MWT and could serve as a surrogate for cardiopulmonary exercise capacity. Assessment of daily step count and activity level measured remotely by the WCD could help to tailor optimal exercise instruction for patients not attending CR.

Day-to-day measurement of physical activity and risk of atrial fibrillation

Aims 

The aim of this study was to investigate the association between within-individual changes in physical activity and onset of atrial fibrillation (AF).

Methods and results 

A total of 1410 participants from the general population (46.2% women, mean age 74.7 ± 4.1 years) with risk factors but with no prior AF diagnosis underwent continuous monitoring for AF episodes along with daily accelerometric assessment of physical activity using an implantable loop recorder during ≈3.5 years. The combined duration of monitoring was ≈1.6 million days, where 10 851 AF episodes lasting ≥60 min were detected in 361 participants (25.6%) with a median of 5 episodes (2, 25) each. The median daily physical activity was 112 (66, 168) min/day. A dynamic parameter describing within-individual changes in daily physical activity, i.e. average daily activity in the last week compared to the previous 100 days, was computed and used to model the onset of AF. A 1-h decrease in average daily physical activity was associated with AF onset the next day [odds ratio 1.24 (1.18–1.31)]. This effect was modified by overall level of activity (P < 0.001 for interaction), and the signal was strongest in the tertile of participants with lowest activity overall [low: 1.62 (1.41–1.86), mid: 1.27 (1.16–1.39), and high: 1.10 (1.01–1.19)].

Conclusions 

Within-individual changes in physical activity are associated with the onset of AF episodes as detected by continuous monitoring in a high-risk population. For each person, a 1-h decrease in daily physical activity during the last week increased the odds of AF onset the next day by ≈25%, while the strongest association was seen in the group with the lowest activity overall.

Clinical Trial Registration

ClinicalTrials.gov, identifier: NCT02036450.

A review of smart sensors coupled with Internet of Things and Artificial Intelligence approach for heart failure monitoring

Over the last decade, there has been a huge demand for health care technologies such as sensors-based prediction using digital health. With the continuous rise in the human population, these technologies showed to be potentially effective solutions to life-threatening diseases such as heart failure (HF). Besides being a potential for early death, HF has a significantly reduced quality of life (QoL). Heart failure has no cure. However, treatment can help you live a longer and more active life with fewer symptoms. Thus, it is essential to develop technological aid solutions allowing early diagnosis and consequently, effective treatment with possibly delayed mortality. Commonly, forecasts of HF are based on the generation of vast volumes of data usually collected from an individual patient by different components of the family history, physical examination, basic laboratory results, and other medical records. Though, these data are not effectively useful for predicting this failure, nevertheless, with the aid of advanced medical technology such as interconnected multi-sensory-based devices, and based on several medical history characteristics, the broad data provided machine learning algorithms to predict risk factors for heart disease of an individual is beneficial. There will be many challenges for the next decade of advancements in HF care: exploiting an increasingly growing repertoire of interconnected internal and external sensors for the benefit of patients and processing large, multimodal datasets with new Artificial Intelligence (AI) software. Various methods for predicting heart failure and, primarily the significance of invasive and non-invasive sensors along with different strategies for machine learning to predict heart failure are presented and summarized in the present study.

Early Increased Physical Activity, Cardiac Rehabilitation, and Survival After Implantable Cardioverter-Defibrillator Implantation

BACKGROUND

Increased physical activity (PA) through cardiac rehabilitation (CR) improves outcomes in patients with heart failure and coronary disease, but CR referral remains infrequent. Implantable cardioverter-defibrillators (ICDs) can provide daily PA measurements to patients that may motivate them to increase PA, but it remains unclear if increased ICD measured PA is associated with improved outcomes with and without CR.

METHODS

This is a retrospective observational study of 41 731 Medicare beneficiaries with ICD implantation between January 1, 2014 and December 31, 2016. We linked daily ICD PA measurements and Medicare claims data to determine if increased PA is associated with a reduction in the likelihood of death or heart failure hospitalization. To determine if CR participation altered the effect of PA on outcomes, we performed two additional analyses matching CR participants and nonparticipants using propensity scores. The first match included demographics, comorbidities, and baseline PA measurements. The second match also included the change in PA measured during CR or the same time frame after ICD implant among nonparticipants.

RESULTS

The mean age was 75 (SD, 10) years, 30 182 beneficiaries (72.3%) were male, and 1324 (3%) participated in CR. Increased ICD detected PA was associated with improved survival. CR participants had a mean PA change of +9.7 (SD, 57.8) min/d, whereas nonparticipants had a mean change of -1.0 (SD, 59.7) min/d (P<0.001). After matching for demographics, comorbidities and baseline PA, CR participants had significantly lower 1- to 3-year mortality (hazard ratio, 0.76 [95% CI, 0.69-0.85], P=0.03). After additionally matching for the ICD measured change in PA during CR there were no differences in mortality with and without CR (hazard ratio, 1.00 [95% CI, 0.82-1.21], P=0.87). Every 10 minutes of increased daily PA was associated with a 1.1% reduction in all-cause mortality in both groups.

CONCLUSIONS

Among Medicare beneficiaries with ICDs, small increases in PA were associated with significant reductions in all-cause mortality.

Lockdown, slow down: impact of the COVID-19 pandemic on physical activity-an observational study

Aims

In response to the COVID-19 pandemic, the UK was placed under strict lockdown measures on 23 March 2020. The aim of this study was to quantify the effects on physical activity (PA) levels using data from the prospective Triage-HF Plus Evaluation study.

Methods

This study represents a cohort of adult patients with implanted cardiac devices capable of measuring activity by embedded accelerometery via a remote monitoring platform. Activity data were available for the 4 weeks pre-implementation and post implementation of ‘stay at home’ lockdown measures in the form of ‘minutes active per day’ (min/day).

Results

Data were analysed for 311 patients (77.2% men, mean age 68.8, frailty 55.9%. 92.2% established heart failure (HF) diagnosis, of these 51.2% New York Heart Association II), with comorbidities representative of a real-world cohort.

Post-lockdown, a significant reduction in median PA equating to 20.8 active min/day was seen. The reduction was uniform with a slightly more pronounced drop in PA for women, but no statistically significant difference with respect to age, body mass index, frailty or device type. Activity dropped in the immediate 2-week period post-lockdown, but steadily returned thereafter. Median activity week 4 weeks post-lockdown remained significantly lower than 4 weeks pre-lockdown (p≤0.001).

Conclusions

In a population of predominantly HF patients with cardiac devices, activity reduced by approximately 20 min active per day in the immediate aftermath of strict COVID-19 lockdown measures.

Trial registration number

NCT04177199.

Utility of cardiovascular implantable electronic device-derived patient activity to predict clinical outcomes

BACKGROUND

The role of cardiovascular implantable electronic device (CIED)-derived activity to predict implantable cardioverter-defibrillator (ICD) therapy or death is not known.

OBJECTIVE

We aimed to assess CIED-derived activity to predict clinical outcomes.

METHODS

In 1500 patients enrolled in MADIT-RIT, CIED-derived patient activity was acquired daily, then averaged for the first 30 days following randomization to predict inappropriate/appropriate therapy or death. Kaplan-Meier analysis and Cox proportional regression models were used to evaluate inappropriate/appropriate therapy, heart failure, or death by 30-day CIED-derived patient activity quintiles.

RESULTS

There were 1463 patients with CIED activity data (98%). Patients in the highest quintile (Q5) of activity (more active) had the highest rate of inappropriate therapy, 21% at 2 years, as compared to 7%-11% in the other 4 quintiles (P < .001), a 1.75 times higher risk (95% confidence interval [CI]: 1.23-2.50, P = .002). However, patients in the lowest quintile of activity (Q1, 1 hour/day) had the highest risk of mortality, 15% in 2 years, as compared to Q2-3 (1-2 hours/day, 8%-7% mortality), and Q4-5 (>2 hours/day, 2%-3% mortality) (P < .001). Patients with the lowest level of activity (Q1) had a 2.02 times higher risk of mortality (95% CI: 1.21-3.38, P = .007), and they had an 82% higher risk of heart failure hospitalization (95% CI: 1.28-2.57, P = .001).

CONCLUSIONS

High CIED-derived 30-day median patient activity predicted inappropriate therapy, while low patient activity predicted mortality and heart failure in ICD and cardiac resynchronization therapy with defibrillator patients enrolled in MADIT-RIT. Device-derived activity assessment could serve as a useful predictor of outcomes.

Clinical utility of CorVue intrathoracic impedance alert with device-measured physical activity in predicting heart failure events

Cardiac implantable electronic devices (CIEDs) offer heart failure (HF) diagnostic information, including intrathoracic impedance (ITI) or physical activity (PA). However, few studies have evaluated the utility of these parameters measured by CIEDs with CorVue algorithm. The purpose of this study was to investigate the relationship between ITI alerts triggered by the CorVue algorithm and HF development. We also examined the association between device-measured PA and ITI alerts associated with HF development. We retrospectively studied consecutive patients with CIEDs equipped with CorVue algorithm, which were implanted between June 1, 2011 and August 31, 2019. These patients were divided into two groups: patients with decreased ITI followed by the ITI alerts (ITI alert group) and those without the alerts (non-ITI alert group). There were 35 and 14 patients in the ITI and non-ITI alert groups, respectively. A total of 96 ITI alerts were observed. ITI alerts associated with HF development were observed in 21% (20/96); whereas, ITI alerts not associated with HF development were observed in 79% (76/96). Accurate device-measured PA was confirmed in 76 ITI alerts, which consisted of 30 alerts with lower PA and 46 alerts without lower PA. ITI alerts associated with HF development were observed in 30% (9/30) of the alerts with lower PA, whereas observed only in 6.5% (3/46) of the alerts without lower PA. In conclusion, the CorVue ITI alerts indicated a high false-positive rate. However, device-measured PA may be useful to determine whether ITI alerts are associated with HF development or not, which was attributed to the high negative predictive value.

The AWAKE-HF Study: Sacubitril/Valsartan Impact on Daily Physical Activity and Sleep in Heart Failure

BACKGROUND

AWAKE-HF evaluated the effect of the initiation of sacubitril/valsartan versus enalapril on activity and sleep using actigraphy in patients who have heart failure with reduced ejection fraction (HFrEF).

METHODS

In this randomized, double-blind study, patients with HFrEF (n = 140) were randomly assigned to sacubitril/valsartan or enalapril for 8 weeks, followed by an 8-week open-label phase with sacubitril/valsartan. Primary endpoint was change from baseline in mean activity counts during the most active 30 min/day at week 8. The key secondary endpoint was change in mean nightly activity counts/minute from baseline to week 8. Kansas City Cardiomyopathy Questionnaire-23 (KCCQ-23) was an exploratory endpoint.

RESULTS

There were no detectable differences between groups in geometric mean ratio of activity counts during the most active 30 min/day at week 8 compared with baseline (0.9456 [sacubitril/valsartan:enalapril]; 95% confidence interval [CI] 0.8863-1.0088; P = 0.0895) or in mean change from baseline in activity during sleep (difference: 2.038 counts/min; 95% CI - 0.062 to 4.138; P = 0.0570). Change from baseline to week 8 in KCCQ-23 was 2.89 for sacubitril/valsartan and 4.19 for enalapril, both nonsignificant.

CONCLUSIONS

In AWAKE-HF, no detectable differences in activity and sleep were observed when comparing sacubitril/valsartan with enalapril in patients with HFrEF using a wearable biosensor.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, NCT02970669.

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.

Impact of a poor functional capacity on the clinical outcomes in patients with a pacemaker implantation -Results from the Japanese Heart Rhythm Society Registry

BACKGROUND

Functional capacity (FC) correlates with mortality in various cardiovascular diseases. The aim of this study was to examine whether cardiac pacemaker implantations improve the FC and affect the prognosis.

METHODS AND RESULTS

We prospectively enrolled 621 de novo pacemaker recipients (age 76 ± 9 years, 50.7% male). The FC was assessed by metabolic equivalents (METs) during the implantation and periodically thereafter. The patients were a priori classified into poor FC (<2 METs, n = 40), moderate FC (2 ≤ METs < 4, n = 239), and good FC (≥4 METs, n = 342). Three months after the pacemaker implantation, poor FC or moderate FC patients improved to a good FC by 43%. The distribution of the three FCs remained at those levels until after 1 year of follow-up (P = .18). During a median follow-up of 2.4 years, 71 patients (11%) had cardiovascular hospitalizations and 35 (5.6%) all-cause death. A multivariate Cox analysis revealed that a poor FC at baseline was an independent predictor of both cardiovascular hospitalization (hazard ratio [HR] 2.494, P = .012) and all-cause death (HR 3.338, P = .016). One year after the pacemaker implantation, the eight who remained with a poor FC had a high mortality rate of 37.5% (P < .01).

CONCLUSION

Approximately half of the poor or moderate FC patients improved to good FC 3 months after the pacemaker implantation. The baseline FC predicted the prognosis, and patients with an improved FC after the pacemaker implantation had a better prognosis.

Sex Differences in Physical Activity and Its Association With Cardiac Death and All-Cause Mortality in Patients With Implantable Cardioverter-Defibrillators

Objective: To clarify the impact of sex on physical activity (PA) levels among patients with implantable cardioverter-defibrillators/cardiac resynchronization therapy defibrillators (ICD/CRT-D) and its association with cardiac death and all-cause mortality.

Methods: Overall, data of 820 patients with ICD/CRT-D from the SUMMIT registry were retrospectively analyzed. Baseline PA from 30 to 60 days after device implantation was measured using Biotronik accelerometer sensors. The primary and secondary endpoints were cardiac death and all-cause mortality, respectively.

Results: Baseline PA levels were significantly higher in male patients than in female patients (11.40 ± 5.83% vs. 9.93 ± 5.49%, P = 0.001). Males had higher predictive PA cut-off values for cardiac death (11.16 vs. 7.15%) and all-cause mortality (11.33 vs. 7.17%). During the median follow-up time of 75.7 ± 29.1 months, patients with baseline PA<cut-off values had higher cumulative incidence of cardiac death and all-cause mortality in both males and females. At a PA level between the cut-off values of males and females, males had a higher risk of cardiac death (hazard ratio = 4.952; 95%CI = 1.055-23.245, P = 0.043) and all-cause mortality (hazard ratio = 2.432; 95%CI = 1.095-5.402, P = 0.029).

Conclusions: Males had higher predictive PA cut-off values for cardiac death and all-cause mortality in patients with ICD/CRT-D. Sex should be considered as an important contributing factor when deciding for PA targets.

OUTSTEP-HF: randomised controlled trial comparing short-term effects of sacubitril/valsartan versus enalapril on daily physical activity in patients with chronic heart failure with reduced ejection fraction

AIMS

OUTSTEP-HF compared the effect of sacubitril/valsartan vs. enalapril on 6-min walk test (6MWT) distance, non-sedentary daytime physical activity and heart failure (HF) symptoms in patients with HF with reduced ejection fraction (HFrEF).

METHODS AND RESULTS

Ambulatory patients (n = 621) with stable symptomatic HFrEF were randomised 1:1 to sacubitril/valsartan (n = 310) or enalapril (n = 311). Changes in physical activity and mean daily non-sedentary daytime activity from baseline to Week 12 were measured using 6MWT and a wrist-worn accelerometer device, respectively. After 12 weeks, 6MWT improved by 35.09 m with sacubitril/valsartan [97.5% confidence interval (CI) 27.85, 42.32] and by 26.11 m with enalapril (97.5% CI 18.78, 33.43); however, there was no significant difference between groups [least squares means treatment difference: 8.98 m (97.5% CI -1.31, 19.27); P = 0.0503]. Mean daily non-sedentary daytime activity decreased by 27 min with sacubitril/valsartan and by 21 min with enalapril [least squares means treatment difference: -6 min (97.5% CI -25.7, 13.4), P = 0.4769] after 12 weeks. 6MWT improved by ≥30 m in 51% of patients in the sacubitril/valsartan group vs. 44% of patients treated with enalapril (odds ratio 1.251, 95% CI 0.895, 1.748). At Week 4, non-sedentary daytime activity increased by ≥10% in 58% of patients treated with sacubitril/valsartan vs. 64% with enalapril; 58% of patients treated with sacubitril/valsartan reported improved HF symptoms as assessed by patient global assessment vs. 43% with enalapril. However, these differences did not persist at Week 12.

CONCLUSION

After 12 weeks of treatment, there was no significant benefit of sacubitril/valsartan on either 6MWT or daytime physical activity measured by actigraphy compared with enalapril.

Measuring physical activity with activity monitors in patients with heart failure: from literature to practice. A position paper from the Committee on Exercise Physiology and Training of the Heart Failure Association of the European Society of Cardiology

The aims of this paper were to provide an overview of available activity monitors used in research in patients with heart failure and to identify the key criteria in the selection of the most appropriate activity monitor for collecting, reporting, and analysing physical activity in heart failure research. This study was conducted in three parts. First, the literature was systematically reviewed to identify physical activity concepts and activity monitors used in heart failure research. Second, an additional scoping literature search for validation of these activity monitors was conducted. Third, the most appropriate criteria in the selection of activity monitors were identified. Nine activity monitors were evaluated in terms of size, weight, placement, costs, data storage, water resistance, outcomes and validation, and cut‐off points for physical activity intensity levels were discussed. The choice of a monitor should depend on the research aims, study population and design regarding physical activity. If the aim is to motivate patients to be active or set goals, a less rigorously tested tool can be considered. On the other hand, if the aim is to measure physical activity and its changes over time or following treatment adjustment, it is important to choose a valid activity monitor with a storage and battery longevity of at least one week. The device should provide raw data and valid cut‐off points should be chosen for analysing physical activity intensity levels. Other considerations in choosing an activity monitor should include data storage location and ownership and the upfront costs of the device.

Baseline and decline in device-derived activity level predict risk of death and heart failure in patients with an ICD for primary prevention

BACKGROUND

Implanted defibrillators are capable of recording activity data based on company-specific proprietary algorithms. This study aimed to determine the prognostic significance of baseline and decline in device-derived activity level across different device companies in the real world.

METHODS

We performed a retrospective cohort study of patients (n = 280) who underwent a defibrillator implantation (Boston, Medtronic, St. Jude, and Biotronik) for primary prevention at the University of Michigan from 2014 to 2016. Graphical data obtained from device interrogations were retrospectively converted to numerical data. The activity level averaged over a month from a week postimplantation was used as baseline. Subsequent weekly average activity levels (SALs) were standardized to this baseline. SAL below 59.4% was used as a threshold to group patients. All-cause mortality and death/heart failure were the primary end-points of this study.

RESULTS

Fifty-six patients died in this study. On average, they experienced a 50% decline in SAL prior to death. Patients (n = 129) who dropped their SAL below threshold were more likely to be older, male, diabetic, and have more symptomatic heart failure. They also had a significantly increased risk of heart failure/death (hazard ratio [HR] 3.6, 95% confidence interval [95% CI] 2.3-5.8, P < .0001) or death (HR 4.2, 95% CI 2.2-7.7, P < .0001) compared to those who had sustained activity levels. Lower baseline activity level was also associated with significantly increased risk of heart failure/death and death.

CONCLUSION

Significant decline in device-derived activity level and low baseline activity level are associated with increased mortality and heart failure in patients with an ICD for primary prevention.

Artificial Intelligence, Data Sensors and Interconnectivity: Future Opportunities for Heart Failure

A higher proportion of patients with heart failure have benefitted from a wide and expanding variety of sensor-enabled implantable devices than any other patient group. These patients can now also take advantage of the ever-increasing availability and affordability of consumer electronics. Wearable, on- and near-body sensor technologies, much like implantable devices, generate massive amounts of data. The connectivity of all these devices has created opportunities for pooling data from multiple sensors – so-called interconnectivity – and for artificial intelligence to provide new diagnostic, triage, risk-stratification and disease management insights for the delivery of better, more personalised and cost-effective healthcare. Artificial intelligence is also bringing important and previously inaccessible insights from our conventional cardiac investigations. The aim of this article is to review the convergence of artificial intelligence, sensor technologies and interconnectivity and the way in which this combination is set to change the care of patients with heart failure.

Utility of single-item questions to assess physical inactivity in patients with chronic heart failure

Aim

The purpose of this study was to explore the utility of two single‐item self‐report (SR) questions to assess physical inactivity in patients with heart failure (HF).

Methods and results

This is a cross‐sectional study using data from 106 patients with HF equipped with accelerometers for 1 week each. Two SR items relating to physical activity were also collected. Correlations between accelerometer activity counts and the SR items were analysed. Patients were classified as physically active or inactive on the basis of accelerometer counts, and the SR items were used to try to predict that classification. Finally, patients were classified as having high self‐reported physical activity or low self‐reported physical activity, on the basis of the SR items, and the resulting groups were analysed for differences in actual physical activity. There were significant but weak correlations between the SR items and accelerometer counts: ρ = 0.24, P = 0.016 for SR1 and ρ = 0.21, P = 0.033 for SR2. Using SR items to predict whether a patient was physically active or inactive produced an area under the curve of 0.62 for SR1, with a specificity of 92% and a sensitivity of 30%. When dividing patients into groups on the basis of SR1, there was a significant difference of 1583 steps per day, or 49% more steps in the high self‐reported physical activity group (P < 0.001).

Conclusions

There might be utility in the single SR question for high‐specificity screening of large populations to identify physically inactive patients in order to assign therapeutic interventions efficiently where resources are limited.

Association of Implantable Device Measured Physical Activity With Hospitalization for Heart Failure

OBJECTIVES

The purpose of this study was to evaluate the association of physical activity (PA) level and longitudinal PA trajectory with a composite heart failure hospitalization and mortality endpoint over a 5-year follow-up period following implantation.

BACKGROUND

Low device measured PA early after implantation of an implantable cardioverter-defibrillator (ICD) or cardiac resynchronization therapy defibrillator (CRT-D) is associated with poor outcomes.

METHODS

We linked daily PA data from the Boston Scientific ALTITUDE dataset of patients with ICD or CRT-D implantation to Medicare claims data. We used a joint model to investigate the association of the composite endpoint with 1) the time-varying point estimate of PA and 2) the time-varying trajectory/slope of PA during follow-up.

RESULTS

Among 20,927 patients with median activity level 85 min/day, 14.1% and 49.6% experienced the composite endpoint at 1 and 5 years. Adjusted joint model results showed that there was a 1.13 (95% confidence interval: 1.12 to 1.13)-fold increase in the hazard of the composite endpoint for 75 min of daily PA relative to 85 min of PA; and a within-patient 10-min decrease in average daily PA over an 8-week period from 85 to 75 min was associated with a hazard ratio of 4.02 (95% confidence interval: 3.82 to 4.22) for the composite endpoint.

CONCLUSIONS

Patients with large decreases in PA have significantly higher risk of experiencing heart failure hospitalization or death. PA data from implantable devices may identify patients before clinical decompensation.

Physical activity is reduced prior to ventricular arrhythmias in patients with a wearable cardioverter defibrillator

INTRODUCTION

The utility of accelerometer-based activity data to identify patients at risk of sustained ventricular tachycardia (VT) or ventricular fibrillation (VF) has not previously been investigated. The aim of the current study was to determine whether physical activity is associated with manifesting spontaneous sustained VT/VF requiring emergent defibrillation in patients with an ejection fraction of ≤35%.

METHODS

Patients consecutively prescribed a wearable cardioverter defibrillator (WCD) from April 2015 to May 2018 were included. Shock data and 4 weeks of physical activity data, beginning with the first week of WCD wear, were analyzed.

RESULTS

Based on the ROC curve outcome generated from 4057 patients, average daily step count during the first week accurately predicted those patients with sustained VT/VF compared to those without (shocked (n = 81) vs nonshocked (n = 3976) area under the curve, c-index = 0.71, 95% CI = 0.65-0.77, P < .001). An average cutoff of 3637 daily steps during week 1 separated the groups. Patients who averaged fewer than 3637 steps per day during the first week of WCD use were 4.3 times more likely to experience a shock than those who walked more than 3637 steps per day (OR = 4.29, 95% CI = 2.58-7.15, P < .001).

DISCUSSION

Average daily step counts are lower in WCD patients who manifest spontaneous VT/VF. Whether these findings represent a causal or correlational relationship, future studies to encourage a minimum daily step count in high-risk patients may impact the incidence of sustained VT/VF.

Effects of Physical Activity, Exercise, and Fitness on Obesity-Related Morbidity and Mortality

Obesity is associated with increased prevalence of cardiovascular (CV) disease (CVD) risk factors, which may adversely impact CV structure and function and may increase the prevalence of most CVD, particularly heart failure (HF) and coronary heart disease (CHD). Physical activity (PA), exercise training (ET) and cardiorespiratory fitness (CRF) are all associated with marked reductions in most CVD, including HF and CHD. Additionally, PA/ET and, especially CRF, markedly alter the relationship between adiposity and subsequent major CVD outcomes and dramatically impact the "obesity paradox," which are all reviewed, including attention to the debate regarding "fitness versus fatness" for long-term prognosis, including in patients with established CVD.

Circulatory factors associated with function and prognosis in patients with severe heart failure

Background

Multiple circulatory factors are increased in heart failure (HF). Many have been linked to cardiac and/or skeletal muscle tissue processes, which in turn might influence physical activity and/or capacity during HF. This study aimed to provide a better understanding of the mechanisms linking HF with the loss of peripheral function.

Methods and results

Physical capacity measured by maximum oxygen uptake, myocardial function (measured by echocardiography), physical activity (measured by accelerometry), and mortality data was collected for patients with severe symptomatic heart failure an ejection fraction < 35% (n = 66) and controls (n = 28). Plasma circulatory factors were quantified using a multiplex immunoassay. Multivariate (orthogonal projections to latent structures discriminant analysis) and univariate analyses identified many factors that differed significantly between HF and control subjects, mainly involving biological functions related to cell growth and cell adhesion, extracellular matrix organization, angiogenesis, and inflammation. Then, using principal component analysis, links between circulatory factors and physical capacity, daily physical activity, and myocardial function were identified. A subset of ten biomarkers differentially expressed in patients with HF vs controls covaried with physical capacity, daily physical activity, and myocardial function; eight of these also carried prognostic value. These included established plasma biomarkers of HF, such as NT-proBNP and ST2 along with recently identified factors such as GDF15, IGFBP7, and TfR, as well as a new factor, galectin-4.

Conclusions

These findings reinforce the importance of systemic circulatory factors linked to hemodynamic stress responses and inflammation in the pathogenesis and progress of HF disease. They also support established biomarkers for HF and suggest new plausible markers.

Graphic abstract

Electronic supplementary material

The online version of this article (10.1007/s00392-019-01554-3) contains supplementary material, which is available to authorized users.

Can activity monitors predict outcomes in patients with heart failure? A systematic review

Actigraphy is increasingly incorporated into clinical practice to monitor intervention effectiveness and patient health in congestive heart failure (CHF). We explored the prognostic impact of actigraphy-quantified physical activity (AQPA) on CHF outcomes. PubMed and Medline databases were systematically searched for cross-sectional studies, cohort studies or randomised controlled trials from January 2007 to December 2017. We included studies that used validated actigraphs to predict outcomes in adult HF patients. Study selection and data extraction were performed by two independent reviewers. A total of 17 studies (15 cohort, 1 cross-sectional, 1 randomised controlled trial) were included, reporting on 2,759 CHF patients (22-89 years, 27.7% female). Overall, AQPA showed a strong inverse relationship with mortality and predictive utility when combined with established risk scores, and prognostic roles in morbidity, predicting cognitive function, New York Heart Association functional class and intercurrent events (e.g. hospitalisation), but weak relationships with health-related quality of life scores. Studies lacked consensus regarding device choice, time points and thresholds of PA measurement, which rendered quantitative comparisons between studies difficult. AQPA has a strong prognostic role in CHF. Multiple sampling time points would allow calculation of AQPA changes for incorporation into risk models. Consensus is needed regarding device choice and AQPA thresholds, while data management strategies are required to fully utilise generated data. Big data and machine learning strategies will potentially yield better predictive value of AQPA in CHF patients.

JA, Jortberg E, Bhatkar V, Ceruolo M, Ghaffari R, Clason DL, Maynard JP, Combs AH. A Pivotal Study to Validate the Performance of a Novel Wearable Sensor and System for Biometric Monitoring in Clinical and Remote Environments

BACKGROUND

Increasingly, drug and device clinical trials are tracking activity levels and other quality of life indices as endpoints for therapeutic efficacy. Trials have traditionally required intermittent subject visits to the clinic that are artificial, activity-intensive, and infrequent, making trend and event detection between visits difficult. Thus, there is an unmet need for wearable sensors that produce clinical quality and medical grade physiological data from subjects in the home. The current study was designed to validate the BioStamp nPoint® system (MC10 Inc., Lexington, MA, USA), a new technology designed to meet this need.

OBJECTIVE

To evaluate the accuracy, performance, and ease of use of an end-to-end system called the BioStamp nPoint. The system consists of an investigator portal for design of trials and data review, conformal, low-profile, wearable biosensors that adhere to the skin, a companion technology for wireless data transfer to a proprietary cloud, and algorithms for analyzing physiological, biometric, and contextual data for clinical research.

METHODS

A prospective, nonrandomized clinical trial was conducted on 30 healthy adult volunteers over the course of two continuous days and nights. Supervised and unsupervised study activities enabled performance validation in clinical and remote (simulated "at home") environments. System outputs for heart rate (HR), heart rate variability (HRV) (including root mean square of successive differences [RMSSD] and low frequency/high frequency ratio), activity classification during prescribed activities (lying, sitting, standing, walking, stationary biking, and sleep), step count during walking, posture characterization, and sleep metrics including onset/wake times, sleep duration, and respiration rate (RR) during sleep were evaluated. Outputs were compared to FDA-cleared comparator devices for HR, HRV, and RR and to ground truth investigator observations for activity and posture classifications, step count, and sleep events.

RESULTS

Thirty participants (77% male, 23% female; mean age 35.9 ± 10.1 years; mean BMI 28.1 ± 3.6) were enrolled in the study. The BioStamp nPoint system accurately measured HR and HRV (correlations: HR = 0.957, HRV RMSSD = 0.965, HRV ratio = 0.861) when compared to ActiheartTM. The system accurately monitored RR (mean absolute error [MAE] = 1.3 breaths/min) during sleep when compared to a Capnostream35TM end-tidal CO2 monitor. When compared with investigator observations, the system correctly classified activities and posture (agreement = 98.7 and 92.9%, respectively), step count (MAE = 14.7, < 3% of actual steps during a 6-min walk), and sleep events (MAE: sleep onset = 6.8 min, wake = 11.5 min, sleep duration = 13.7 min) with high accuracy. Participants indicated "good" to "excellent" usability (average System Usability Scale score of 81.3) and preferred the BioStamp nPoint system over both the Actiheart (86%) and Capnostream (97%) devices.

CONCLUSIONS

The present study validated the BioStamp nPoint system's performance and ease of use compared to FDA-cleared comparator devices in both the clinic and remote (home) environments.

Rationale and design of the randomized multicentre His Optimized Pacing Evaluated for Heart Failure (HOPE-HF) trial

Aims

In patients with heart failure and a pathologically prolonged PR interval, left ventricular (LV) filling can be improved by shortening atrioventricular delay using His‐bundle pacing. His‐bundle pacing delivers physiological ventricular activation and has been shown to improve acute haemodynamic function in this group of patients.

In the HOPE‐HF (His Optimized Pacing Evaluated for Heart Failure) trial, we are investigating whether these acute haemodynamic improvements translate into improvements in exercise capacity and heart failure symptoms.

Methods and results

This multicentre, double‐blind, randomized, crossover study aims to randomize 160 patients with PR prolongation (≥200 ms), LV impairment (EF ≤ 40%), and either narrow QRS (≤140 ms) or right bundle branch block. All patients receive a cardiac device with leads positioned in the right atrium and the His bundle. Eligible patients also receive a defibrillator lead. Those not eligible for implantable cardioverter defibrillator have a backup pacing lead positioned in an LV branch of the coronary sinus. Patients are allocated in random order to 6 months of (i) haemodynamically optimized dual chamber His‐bundle pacing and (ii) backup pacing only, using the non‐His ventricular lead.

The primary endpoint is change in exercise capacity assessed by peak oxygen uptake. Secondary endpoints include change in ejection fraction, quality of life scores, B‐type natriuretic peptide, daily patient activity levels, and safety and feasibility assessments of His‐bundle pacing.

Conclusions

Hope‐HF aims to determine whether correcting PR prolongation in patients with heart failure and narrow QRS or right bundle branch block using haemodynamically optimized dual chamber His‐bundle pacing improves exercise capacity and symptoms. We aim to complete recruitment by the end of 2018 and report in 2020.

Patterns of physical activity and survival following cardiac resynchronization therapy implantation: the ALTITUDE activity study

Aims

Cardiac resynchronization therapy with implantable defibrillator backup (CRT-D) improves outcomes, but predictors and markers of response remain limited. Physical activity information collected by CRT devices may provide insights to CRT response and the relationship between activity changes and survival.

Methods and results

Patients entered into the LATITUDE remote monitoring system from 2008 to 2012 after receipt of a new CRT-D were eligible. Mean daily activity was calculated from LATITUDE uploads at baseline (first 3-10 days following implant) and 6 months (180-210 days). Pairwise differences for baseline-6-month activity were calculated, and survival according to quintiles of 6-month activity change was assessed. Cox regression was used to examine the adjusted association between survival and baseline-6-month activity change. A total of 26 509 patients were followed for a median of 2.3 years (mean age 70.2 ± 11.0 years, 70.7% male). Mean baseline activity was 66.2 ± 47.7 min/day, with mean paired increase at 6 months of 37.1 ± 48.2 min/day [95% CI (confidence interval), 36.5-37.6, P < 0.0001], though 15.5% of patients did not improve or worsened at 6 months. Survival at 3 years was significantly higher in the largest baseline-6-month activity change quintile vs. the lowest quintile (88.9% vs. 62.1%, log-rank P-value < 0.001). Adjusted for age and gender, higher 6-month activity change was associated with a lower risk of death (adjusted hazard ratios 0.65 per 30 min increase in activity, 95% CI, 0.63-0.67).

Conclusions

Change in physical activity between baseline and 6 months following CRT implantation is strongly associated with survival.

Measuring Physical Activity With Implanted Cardiac Devices: A Systematic Review

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 methodological issues that may affect interpretation of study results.

Methods and Results

We conducted a systematic review of D‐PA studies published from January 1 1995 to December 30 2017, identifying 29 studies meeting inclusion criteria, 5 of which were validation reports. Few technical details about D‐PA sensors are reported, and procedures for analyzing and interpreting D‐PA data are heterogeneous. Trends in D‐PA over time and associations with clinical outcomes were reported by 22 studies, and in 7 studies, D‐PA was combined with other device parameters in risk stratification models, demonstrating modest‐to‐good sensitivity in predicting acute heart failure decompensation, hospitalization, and mortality.

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. Future work must address challenges related to D‐PA data measurement, interpretation, and generalizability to support expanded clinical applications of this technology.

Physical Activity Measured by Implanted Devices Predicts Atrial Arrhythmias and Patient Outcome: Results of IMPLANTED (Italian Multicentre Observational Registry on Patients With Implantable Devices Remotely Monitored)

Background

To determine whether daily physical activity (PA), as measured by implanted devices (through accelerometer sensor), was related to the risk of developing atrial arrhythmias during long‐term follow‐up in a population of heart failure (HF) patients with an implantable cardioverter defibrillator (ICD).

Methods and Results

The study population was divided into 2 equally sized groups (PA cutoff point: 3.5 h/d) according to their mean daily PA recorded by the device during the 30‐ to 60‐day period post‐ICD implantation. Propensity score matching was used to compare 2 equally sized cohorts with similar characteristics between lower and higher activity patients. The primary end point was time free from the first atrial high‐rate episode (AHRE) of duration ≥6 minutes. Secondary end points were: first AHRE ≥6 hours, first AHRE ≥48 hours, and a combined end point of death or HF hospitalization. Data from 770 patients (65±15 years; 66% men; left ventricular ejection fraction 35±12%) remotely monitored for a median of 25 months were analyzed. A PA ≥3.5 h/d was associated with a 38% relative reduction in the risk of AHRE ≥6 minutes (72‐month cumulative survival: 75.0% versus 68.1%; log rank P=0.025), and with a reduction in the risk of AHRE ≥6 hours, AHRE ≥48 hours, and the combined end point of death or HF hospitalization (all P<0.05).

Conclusions

In HF patients with ICD, a low level of daily PA was associated with a higher risk of atrial arrhythmias, regardless of the patients' baseline characteristics. In addition, a lower daily PA predicted death or HF hospitalization.

Defibrillator shocks and their effect on objective and subjective patient outcomes: Results of the PainFree SST clinical trial

BACKGROUND

The effect of implantable cardioverter-defibrillator (ICD) shock on device-measured activity and patient-reported outcomes is unknown.

OBJECTIVE

The purpose of this study was to analyze the acute and long-term effects of ICD shock on objective behavioral data (ie, device-based physical activity) and subjective patient-reported outcomes (eg, quality of life and shock anxiety).

METHODS

The PainFree Smart Shock Technology (SST) clinical trial included 2770 patients with a single- or dual-chamber ICD or cardiac resynchronization therapy - defibrillator device who were followed for 22 ± 9 months. Participants completed measures of quality of life (EuroQol-5D [EQ-5D] questionnaire) and shock anxiety (Florida Shock Anxiety Scale) at baseline, biannual visits, and monthly for 6 months after an ICD shock. Daily physical activity data were obtained from a built-in device accelerometer.

RESULTS

The average daily activity was 185.3 ± 119.4 min/d. Activity was significantly reduced after an ICD shock (P < .0001) and recovered to a normal level after ∼90 days. An ICD shock was also associated with decreased quality of life (EQ5-D health score) and increased EQ-5D anxiety scores, but it did not affect mobility, self-care, activity, or pain. Similarly, shock anxiety (Florida Shock Anxiety Scale) increased in shocked patients and remained significantly elevated at 24 months, regardless of appropriate or inappropriate shock delivery.

CONCLUSION

ICD shocks have a long-lasting adverse effect on both objective, device-measured physical activity and subjective patient-reported outcomes of quality of life and shock anxiety. Successful management of patients with an ICD requires attention to clinically relevant behavioral and psychological outcomes to expedite recovery and return to activities of daily living.

Accelerometer-Measured Daily Activity in Heart Failure With Preserved Ejection Fraction: Clinical Correlates and Association With Standard Heart Failure Severity Indices

BACKGROUND

Daily physical activity assessed by accelerometers represents a novel method to assess the impact of interventions on heart failure (HF) patients' functional status. We hypothesized that daily activity varies by patient characteristics and correlates with established measures of HF severity in HF with preserved ejection fraction.

METHODS AND RESULTS

In this ancillary study of the NEAT-HFpEF trial (Nitrate's Effects on Activity Tolerance in HF With Preserved Ejection Fraction), average daily accelerometer units (ADAU) and hours active per day were assessed during a 14-day period before starting isosorbide mononitrate or placebo (n=110). Baseline ADAU was negatively associated with age, female sex, height, and body mass index, and these variables accounted for 28% of the variability in ADAU (P<0.007 for all). Adjusting for these factors, patients with lower ADAU were more likely to have had an HF hospitalization, orthopnea, diabetes mellitus and anemia, be treated with β-blockers, have higher ejection fraction, relative wall thickness and left atrial volume, and worse New York Heart Association class, HF-specific quality of life scores, 6-minute walk distance, and NT-proBNP (N-terminal pro-B-type natriuretic peptide; P<0.05 for all). Associations between hours active per day and clinical characteristics were similar. Relative to baseline, there were no significant associations between changes in ADAU or hours active per day and changes in standard functional assessments (New York Heart Association, quality of life, 6-minute walk distance, and NT-proBNP) with isosorbide mononitrate.

CONCLUSIONS

Daily activity is a measure of HF-related and global functional status in HF with preserved ejection fraction. As compared with intermittently assessed standard HF assessments, change in daily activity may provide unique information about the impact of HF interventions on functional status.

CLINICAL TRIAL REGISTRATION

URL: https://www.clinicaltrials.gov/. Unique identifier: NCT02053493.