Background Acute decompensated heart failure (ADHF) is associated with a high rate of readmissions and mortality. Remote dielectric sensing (ReDS) fluid monitoring provides an accurate tool for non-invasive measurement of absolute lung fluid content, providing actionable information and a new tool for managing HF. Methods The SMILE trial was a prospective, multicenter, randomized clinical trial testing the hypothesis that post-discharge HF management guided by frequent in-home ReDS assessment is superior to usual care. Patients with a current hospitalization for ADHF, regardless of the LVEF, were enrolled in 43 US centers. Subjects randomized to the treatment arm were discharged home with the ReDS fluid monitor system and managed using ReDS measurements, according to protocol-defined algorithms. Control patients received usual care, without ReDS. The primary endpoint was recurrent (cumulative) ADHF hospitalizations, analyzed using the Andersen-Gill model with treatment group as the only covariate. Patients were followed for up to 9 months, until the last patient enrolled reached 3 months of follow-up. Results Between October 2015 and October 2017, 268 patients were randomized - 135 to treatment and 133 to control - and followed for 6.1±3.4 months. Patients were aged 68±12 years; 30% were women and 29% had LVEF≥40%. Pre-specified analysis of the per-protocol cohort demonstrated 21 readmissions in 15 ReDS patients compared to 43 readmissions in 34 control patients (HR 0.52, 95% CI [0.31-0.87], P=0.01) or a 48% readmissions reduction (Figure). Subgroup analysis by LVEF < or ≥40% showed similar reductions in ADHF readmissions (RRR 50%, P=0.03 and 46%, P=NS, respectively), with ReDS-guided HF management. Number of days lost to ADHF hospitalization was lower (1.37 vs. 2.62 days, 48% reduction, P=0.006) and time from discharge to first ADHF readmission was longer (HR 0.45, 95% CI [0.25-0.83], P=0.01), for ReDS-guided management. There was no significant difference in mortality between groups. Conclusions The SMILE trial demonstrates a substantial reduction in recurrent ADHF hospitalizations and improvement in other outcome measures in recently discharged ADHF patients managed using daily ReDS assessment of absolute lung fluid content. Acute decompensated heart failure (ADHF) is associated with a high rate of readmissions and mortality. Remote dielectric sensing (ReDS) fluid monitoring provides an accurate tool for non-invasive measurement of absolute lung fluid content, providing actionable information and a new tool for managing HF. The SMILE trial was a prospective, multicenter, randomized clinical trial testing the hypothesis that post-discharge HF management guided by frequent in-home ReDS assessment is superior to usual care. Patients with a current hospitalization for ADHF, regardless of the LVEF, were enrolled in 43 US centers. Subjects randomized to the treatment arm were discharged home with the ReDS fluid monitor system and managed using ReDS measurements, according to protocol-defined algorithms. Control patients received usual care, without ReDS. The primary endpoint was recurrent (cumulative) ADHF hospitalizations, analyzed using the Andersen-Gill model with treatment group as the only covariate. Patients were followed for up to 9 months, until the last patient enrolled reached 3 months of follow-up. Between October 2015 and October 2017, 268 patients were randomized - 135 to treatment and 133 to control - and followed for 6.1±3.4 months. Patients were aged 68±12 years; 30% were women and 29% had LVEF≥40%. Pre-specified analysis of the per-protocol cohort demonstrated 21 readmissions in 15 ReDS patients compared to 43 readmissions in 34 control patients (HR 0.52, 95% CI [0.31-0.87], P=0.01) or a 48% readmissions reduction (Figure). Subgroup analysis by LVEF < or ≥40% showed similar reductions in ADHF readmissions (RRR 50%, P=0.03 and 46%, P=NS, respectively), with ReDS-guided HF management. Number of days lost to ADHF hospitalization was lower (1.37 vs. 2.62 days, 48% reduction, P=0.006) and time from discharge to first ADHF readmission was longer (HR 0.45, 95% CI [0.25-0.83], P=0.01), for ReDS-guided management. There was no significant difference in mortality between groups. The SMILE trial demonstrates a substantial reduction in recurrent ADHF hospitalizations and improvement in other outcome measures in recently discharged ADHF patients managed using daily ReDS assessment of absolute lung fluid content.

Background Ambulatory pulmonary artery (PA) pressure-directed clinical management of Heart Failure (HF) patients has been shown to reduce HF hospitalizations; however the work flow associated with remote hemodynamic monitoring in such patients has not been studied. We performed a time and motion study in a group of patients with heart failure. Methods A non-interventional, single site “time and motion” study of usual care processes was conducted in the Heart Failure clinic of a 630-bed community hospital between July - October 2017. All enrolled patients were NYHA class III. Patients previously implanted with an ambulatory PA pressure sensor (CardioMEMSTM, Abbott; CMEM group), as well as sensor-eligible patients who had not previously received the implant (non-CMEM group), were recruited at a routine HF clinic visit. The usual care visit, for both CMEM and non-CMEM group, was observed from the time the patient arrived at the clinic to the time they left. The in-clinic observation was quantified based on the time spent in the prep area, exam room area, dictation, and scheduling desk. Primary reason for telephone calls made to CMEM group was captured. Results The HF clinic workflow was observed for 53 patients (n = 24 CMEM, n = 29 non-CMEM). The mean clinic visit time were 48:55 ± 15:34 minutes for CMEM and 55:57 ± 21:42 minutes non-CMEM (p = 0.07). 75% of the visit time was spent in the exam room with the provider. Telephone call duration was 5:47 ± 15:09 minutes (N = 92) with a median of 2:13 minutes of which, 52% were related to review of pulmonary artery pressures, 29% to HF monitoring, 12% to labs, and 3% to medication change. Conclusion This is the first characterization of the practical implications of utilizing remote hemodynamic monitoring. The additional time spent during follow-up calls was partially offset by shorter office visits. In addition, since most of the office time involved the provider (exam room) as opposed to nurse time (phone calls), the utilization of CardioMEMS™ may improve provider efficiency. The economic implications of remote hemodynamic management and office visits for HF patients can be studied based on these data.

Background Cardiology has advanced guideline development and quality measurement. Recognizing the substantial benefits of guideline‐directed medical therapy, this study aims to measure and explain apparent deviations in heart failure (HF) guideline adherence by clinicians at hospital discharge and describe any impact on readmission rates. Methods and Results The extent of decongestion and prescription of neurohormonal therapy were recorded prospectively for 226 HF discharges, including 132 (58%) from an academic hospital and 94 (42%) from a community hospital. Among all discharges, 25% were discharged with residual congestion (30% academic versus 18% community, P=0.070). Among discharges of patients with HF with reduced ejection fraction, 37% (45% academic versus 18% community, P<0.001) were discharged without β‐blocker therapy or with lower doses than at admission. Moreover, 46% of patients with HF with reduced ejection fraction (48% academic versus 39% community, P=0.390) were discharged without an angiotensin‐converting enzyme inhibitor or angiotensin II receptor blocker or with lower doses than at admission. Renal dysfunction was the most common reason for discharge with congestion, and hypotension the most common reason for discharge with no or decreased neurohormonal therapy. There was a trend toward higher 90‐day readmission rates after discharge with residual congestion. Conclusions Clinicians frequently deviate from guidelines in both academic and community hospitals; however, this deviation may not always indicate poor quality. Application of guidelines recommended for stable populations is increasingly limited for hospitalized patients by hypotension, renal dysfunction, and inotrope use. Patients with renal dysfunction, hypotension, and recent inotrope use merit further study to determine best practices and possibly to adjust quality metrics for HF severity.

BackgroundWe evaluated factors associated with interventions and events in patients (pts) with heart failure (HF) while enrolled in a HF service (BEACON, Medtronic, plc).MethodsCertified HF nurses (CHFNs) interpret monthly transmissions from devices with the Medtronic OptiVol™ fluid status monitoring feature. This data, combined with weight, blood pressure and symptoms, are used to stratify a pts risk for a HF event (very high, high, moderate, low) and provide a follow-up recommendation (24 hours, 72 hours, 7 days, routine). The CHFN contacted the pt to assess for intervention (provider outreach, medication change, office visit). A generalized estimating equation model tested whether the probability of intervention varied by age, gender, device type or risk. A recurrent events model assessed the impact of age, gender, occurrence of transmissions in each risk category and occurrence of interventions on the hazard of a HF event.ResultsThis real-world evidence evaluation included 2,931 transmissions from 485 pts (73 ± 10 years age, 67% male) enrolled in the HF service for an average of 177 ± 121 days. Compared to moderate risk, higher risk transmissions resulted in a higher probability of outreach and medication changes (figure). There was no difference in the probability of intervention by age or gender. A total of 24 pts (4.9%) reported 31 HF hospitalizations and 2 ER visits (0.14 HF events/patient-year) while on the HF service. There was no significant association between age, gender and risk of HF events. Each additional higher risk transmission, which may have been followed by an intervention, was associated with a decreasing hazard of HF events (any higher risk: HR = 0.85, p = 0.002; moderate risk: HR = 0.73, p = 0.01; high risk: HR = 0.56, p = 0.001; very high risk: HR = 1.00, p = 0.97). There was a trend towards decreasing risk of HF events with an increasing number of interventions, but the trend was not statistically significant (any intervention: HR = 0.93, p = 0.3; outreach: HR = 0.86, p = 0.25; medication change: HR = 0.71, p = 0.14; office visit: HR = 0.93, p = 0.68).ConclusionHigher risk transmissions have a significantly increased probability for intervention, validating the clinical appropriateness of the HF service risk stratification scheme. An increased number of higher risk transmissions, which leads to increased intervention, may also reduce the hazard of future HF events. Future controlled studies should prospectively evaluate this approach. We evaluated factors associated with interventions and events in patients (pts) with heart failure (HF) while enrolled in a HF service (BEACON, Medtronic, plc). Certified HF nurses (CHFNs) interpret monthly transmissions from devices with the Medtronic OptiVol™ fluid status monitoring feature. This data, combined with weight, blood pressure and symptoms, are used to stratify a pts risk for a HF event (very high, high, moderate, low) and provide a follow-up recommendation (24 hours, 72 hours, 7 days, routine). The CHFN contacted the pt to assess for intervention (provider outreach, medication change, office visit). A generalized estimating equation model tested whether the probability of intervention varied by age, gender, device type or risk. A recurrent events model assessed the impact of age, gender, occurrence of transmissions in each risk category and occurrence of interventions on the hazard of a HF event. This real-world evidence evaluation included 2,931 transmissions from 485 pts (73 ± 10 years age, 67% male) enrolled in the HF service for an average of 177 ± 121 days. Compared to moderate risk, higher risk transmissions resulted in a higher probability of outreach and medication changes (figure). There was no difference in the probability of intervention by age or gender. A total of 24 pts (4.9%) reported 31 HF hospitalizations and 2 ER visits (0.14 HF events/patient-year) while on the HF service. There was no significant association between age, gender and risk of HF events. Each additional higher risk transmission, which may have been followed by an intervention, was associated with a decreasing hazard of HF events (any higher risk: HR = 0.85, p = 0.002; moderate risk: HR = 0.73, p = 0.01; high risk: HR = 0.56, p = 0.001; very high risk: HR = 1.00, p = 0.97). There was a trend towards decreasing risk of HF events with an increasing number of interventions, but the trend was not statistically significant (any intervention: HR = 0.93, p = 0.3; outreach: HR = 0.86, p = 0.25; medication change: HR = 0.71, p = 0.14; office visit: HR = 0.93, p = 0.68). Higher risk transmissions have a significantly increased probability for intervention, validating the clinical appropriateness of the HF service risk stratification scheme. An increased number of higher risk transmissions, which leads to increased intervention, may also reduce the hazard of future HF events. Future controlled studies should prospectively evaluate this approach.

The BEACON heart failure (HF) management system triages high risk HF patients to ensure more focused care. We designed a risk stratification algorithm that combines diagnostics in Medtronic implantable cardiac devices with biometrics and symptoms with oversight by certified HF nurses (HFN). We

Opinion statement The treatment of congestive heart failure is an expensive undertaking with much of this cost occurring as a result of hospitalization. It is not surprising that many remote monitoring strategies have been developed to help patients maintain clinical stability by avoiding congestion. Most of these have failed. It seems very unlikely that these failures were the result of any one underlying false assumption but rather from the fact that heart failure is a progressive, deadly disease and that human behavior is hard to modify. One lesson that does stand out from the myriad of methods to detect congestion is that surrogates of congestion, such as weight and impedance, are not reliable or actionable enough to influence outcomes. Too many factors influence these surrogates to successfully and confidently use them to affect HF hospitalization. Surrogates are often attractive because they can be inexpensively measured and followed. They are, however, indirect estimations of congestion, and due to the lack specificity, the time and expense expended affecting the surrogate do not provide enough benefit to warrant its use. We know that high filling pressures cause transudation of fluid into tissues and that pulmonary edema and peripheral edema drive patients to seek medical assistance. Direct measurement of these filling pressures appears to be the sole remote monitoring modality that shows a benefit in altering the course of the disease in these patients. Congestive heart failure is such a serious problem and the consequences of hospitalization so onerous in terms of patient well-being and costs to society that actual hemodynamic monitoring, despite its costs, is beneficial in carefully selected high-risk patients. Those patients who benefit are ones with a prior hospitalization and ongoing New York Heart Association (NYHA) class III symptoms. Patients with NYHA class I and II symptoms do not require hemodynamic monitoring because they largely have normal hemodynamics. Those with NYHA class IV symptoms do not benefit because their hemodynamics are so deranged that they cannot be substantially altered except by mechanical circulatory support or heart transplantation. Finally, hemodynamic monitoring offers substantial hope to those patients with normal ejection fraction (EF) heart failure, a large group for whom medical therapy has largely been a failure. These patients have not benefited from the neurohormonal revolution that improved the lives of their brothers and sisters with reduced ejection fractions. Hemodynamic stabilization improves the condition of both but more so of the normal EF cohort. This is an important observation that will help us design future trials for the 50% of heart failure patients with normal systolic function.

Background: The management of HF patients is resource intense and requires dedicated personnel and infrastructure to provide care for this population. The high 30-day re-admission rate for HF patients attests to the challenges facing clinicians. Risk stratification of this group might allow resources to be allocated in a more cost and time effective manner. We designed an algorithm which combines implantable cardiac device derived diagnostics and externally acquired information to risk stratify HF patients known to be at elevated risk for a HF exacerbation in the outpatient setting. The goal of this project was to triage HF patients so that healthcare resources could focus on those requiring more urgent care. Methods: The BEACON HF management service combines monthly monitoring of physiologic parameters derived from Medtronic implanted devices (CTR-D, ICD and CRT-P) with daily automatic heart rate (HR), blood pressure (BP), weights and symptoms (shortness of breath or swelling) to manage patients at increased risk of a HF exacerbation. Monitored device diagnostics included intra-thoracic impedance, night HR, HR variability, daily activity, atrial and ventricular arrhythmias, % atrial and ventricular pacing and device therapy. HF trained nurses called patients when defined thresholds were crossed and reviewed all transmissions. The risk stratification algorithm was designed with the goal of categorizing patients into very high (24-hour follow-up), high (72-hour follow-up), moderate (1 week follow-up) and low (routine follow-up) risk groups. Results: 262 high risk HF patients (71 ± 10 years, 66% male) were enrolled into the BEACON telehealth service. A total of 1041 device transmissions from 210 patients were available for review during an average period of 132 ± 86 days. The risk categorization of transmissions, along with contributing factors, are included in the table below.Tabled 1RiskVery HighHighMediumLowRecommended follow upWithin 24 hoursWithin 72 hoursWithin 1 weekroutineTransmissions (% of 1041 Transmissions)116 (11%)129 (12%)338 (32%)458 (44%)Patients (% of 210 Pts with at least 1 Transmissions in risk category)58 (28%)70 (33%)139 (66%)151 (72%)Contributing factors (% of Transmissions in each risk category)Worsening HF symptoms74%22%16%0%Weight gain from baseline60%14%12%5%OptiVol fluid Index crossing59%71%14%0%Reducing or low patient activity53%34%55%0%Arrhythmias or reduced CRT therapy37%28%33%11%Increasing or high night heart rate30%34%8%0%Reducing or low heart rate variability30%28%16%15% Open table in a new tab Conclusion: Very high risk transmissions accounted for 11.1% of all transmissions, whereas 44.0% were identified as low risk, requiring no unscheduled follow-up. The capability of the BEACON HF service to risk stratify allows for the healthcare system to focus on those patients requiring care.

Heart failure care is expensive and resource intensive. In the era of population medicine, accountable care organizations, and bundled care, an inexpensive noninvasive technique to facilitate the management of this population would be a valuable asset. Although continuous remote monitoring of pulmonary artery pressure (PAP) is available and proven to improve outcomes in the clinical trial setting,1 it is invasive and expensive to implant and requires dedicated personnel to routinely monitor the patient, interpret the data, and consistently use the information. Indeed, few practices are prepared for the type of infrastructure investment required to effectively monitor PAP at the present time under the current payment model. Hence, the adoption of PAP monitoring has been slow and likely limited to patients with advanced heart failure within health systems with sophisticated heart failure programs. Unlike cardiac implantable electronic devices, current trends indicate that PAP monitoring will be used more commonly in patients with heart failure and a preserved ejection fraction because this is a group that is most difficult to manage and accounts for the majority of readmissions. See Article by Zile et al Impedance measurements from cardiac implantable electronic devices have been clinically available for over a decade. The scientific principle underlying the measurement of impedance, which is the biological equivalent of resistance, is Ohm’s law: R = V / I . Resistance ( R ) is a function of the relationship between the applied voltage ( V ) and the current ( I ) measured across an electric field.2 In patients with cardiac implantable electronic devices that can measure impedance, the electric field includes the lung and thoracic tissue that lie between the device and the tip of the pacing electrode. Presumably, a congested chest has higher fluid content and …

Background: Treating patients using ambulatory pulmonary artery pressure (PAP) monitoring has been shown to reduce heart failure (HF) hospitalizations. In order for this technology to be effective, patients must take an active role in their care by transmitting PAP data on a daily basis. Adherence to daily monitoring programs can present challenges for many patients. We investigated whether or not a PAP monitoring program could be established and maintained in a community hospital setting. Hypothesis: Adequate patient compliance can be achieved in a community hospital setting to allow meaningful utilization of PAP monitoring. Methods: We retrospectively reviewed 32 patients implanted with a CardioMEMs device from Feb 2015 to Feb 2016. It is our practice to require patients undergoing implantation of a PAP monitor to sign an agreement, which documents their understanding and intent to comply with regular transmissions. We analyzed 19 patients (age 67.6 ± 11.4 years, 47% male) that were monitored for at least 6 months and the data collection was closed on 3/14/2016. Baseline demographics, number of transmissions and hemodynamic data were analyzed. All patients' transmissions were reviewed twice weekly and a clinic nurse called to encourage compliance in patients who had not transmitted regularly. Mean, systolic and diastolic PAP was reviewed at baseline, 3 months, and 6 months. Three compliance endpoints were analyzed: average number of transmissions per patient over the follow-up period, the number of days between transmissions, and the frequency of transmission over time. Results: 19 patients with at least 6 months of data following implant had 4,475 transmissions with a follow-up of 283.4 ± 51.0 days. The number of transmissions per month was 25.1 ± 5.7. There was no difference in the number or frequency of transmission for patients <65 years or >65 years old. Patient compliance with transmissions remained stable over the follow-up period at 3 and 6 months. One patient died of non HF related causes in follow-up. Conclusions: Patient compliance with device transmissions was high and remained stable over time. This is likely the result of patient selection criteria, a pre-procedure monitoring agreement and the utilization of a nurse telephone intervention system. Hemodynamic measurements were stable at baseline and remained so over time. Implementing a HF monitoring program which utilizes PAP measurements is feasible in a community hospital setting and can be maintained over time.

Background: Heart failure (HF) is one of the most common reasons for hospital admission in the United States. Typically, congestion is the primary reason for HF decompensation. Ambulatory pulmonary artery pressure (PAP) monitoring has been shown to reduce HF hospitalizations in clinical trials. Hypothesis: Real world application of CardioMEMS technology in a community hospital setting will result in reduction in HF hospitalizations. Methods: 26 patients (age 66.7 ± 9.84; 15 male; 85% HF Preserved EF) who underwent CardioMEMS device implantation between February, 2015 and February, 2016 were retrospectively reviewed. Patients enrolled were at least 60 days post implant. Baseline demographics, hospitalizations, and office based interventions were recorded. Implanted patients had an average of 6.7 ± 1.5 major comorbid conditions. One patient died following 197 days of monitoring from a non-cardiac cause. Patients were compared to their own 1 year historic control and evaluated in patient years for statistical analysis. Results: Patients who underwent CardioMEMS implantation had a reduction in all cause admissions from 3 to 2.5 per patient year (P = .5). Heart failure admissions were also reduced from 1.9 to 0.5 per patient year (P < .001). Total all cause hospitalized days decreased from 17.3 ± 14.3 to 8.5 ± 12.3 (P = .02) and heart failure days decreased from 12 ± 10.5 to 2.4 ± 7.7 (P < .001). This reduction was associated with an increased intensity of office interventions. Phone calls per week increased from 1.4 ± 1.7 to 2.7 ± 1.3 (P < .001), medication changes per week increased from 0.6 ± 0.6 to 1 ± 0.8 (P = .03), and office visits per month rose minimally 0.9 ± 0.5 to 1.1 ± 0.6 (P = .13). Conclusions: Ambulatory hemodynamic monitoring of PAP for a high-risk patient population, in the community hospital setting, has demonstrated a reduction of heart failure admissions. Managing an increased volume of phone calls and medication changes both significantly reduced the number of hospitalizations for HF, and time spent in the hospital for those admissions. In the current era of healthcare reform, process improvement and integration of technology into clinical practice are critical to delivering the best patient outcomes. Studies addressing efficiencies in heart failure program monitoring are needed to further propel current practice toward improved outcomes for heart failure populations.

Introduction: Standardized Clinical Assessment and Management Plans (SCAMPs) are a novel tool forthe prospective auditing of clinical outcomes and quality improvement in areas of practice variation. Using the SCAMP methodology to address heart failure (HF) discharges, two sites collaborated to investigate adherence to guideline-recommended achievement of optimal volume status and reasons for deviation in clinical practice. Methods: Consecutive patients hospitalized for chronic HF at a tertiary referral center (Brigham and Women’s Hospital, Boston MA, n=108, 55.3%) and community hospital with a dedicated heart failure program (Lancaster General Hospital, Lancaster PA, n=87, 44.6%) were enrolled in a HF SCAMP which recommended discharge only after complete decongestion (defined by jugular venous pressure <8cmH20 and absence of lower extremity edema, orthopnea and rales). Reasons for deviation from were documented by the attending physician. 90 day readmission rates were recorded. Results: There were 195 patients enrolled. The average age at BWH was 64 years compared to 79 year at LGH. Overall, 57 (29%) patients had residual congestion at discharge, 37% of patients at BWH and 20% at LGH (p=0.01). However, the average weight change was -4.3kg at BWH and -3.8Kg at LGH. At BWH, the most common reason for inadequate decongestion was renal dysfunction (34% BWH vs. 6% LGH, p=0.04). At LGH, non-cardiac/chronic edema (“edema resistant”) was the most common reason (44% LGH vs. 17% BWH (p=0.08). Plan for continued diuresis at home was more common at LGH (LGH 19% vs. BWH 0%, p=0.03). At 90 days, 37% of congested patients and 23% of completely decongested patients had been readmitted (p=0.08). Conclusions: Nearly 1 in 3 patients admitted for worsening HF were discharged with residual congestion, which was more common at the tertiary care center and trended with higher readmission rates. The reasons for inadequate decongestion were different between sites.

Morbidity and mortality are high in all heart failure patients (heart failure with reduced (HFrEF) or preserved ejection fraction (HFpEF) following heart failure hospitalization. Disposition plans at the time of discharge impact readmission and adherence to outpatient service and resource utilization. A retrospective review of all heart failure admissions to a community hospital was performed. Admissions from a 6 month period from January 1 2013 through June 30 2013 were examined using the Crimson database and manual chart review. The discharge disposition of 537 admissions was grouped according to their discharge coding diagnosis: HFrEF and HFpEF. Discharge disposition, Table 1. Of the patients admitted, the mean age was 74.3±11.8, with 51% males. Discharge disposition was similar between the 2 groups, with the exception of utilization of hospice services. HFpEF carries an equally poor prognosis yet hospice services were engaged in only 3% (n=8) of the patients discharged during that time period as opposed to 9% (n=27) of patients with HFrEF (p=0.004). In the 6 month interval follow up, the mortality in those patients readmitted with HFrEF was 46.2%% and HFpEF was 35.6%%. Patients with heart failure hospitalizations have a high short-term mortality. Close integration with hospice or palliative medicine is important to better clarify patients' goals of care. Patients with HFpEF have a similarly poor prognosis but end of life care discussions may be underutilized in this group. Further prospective studies are needed with heart failure and end of life care to better formulate a disposition plan given the changing landscape in health care delivery.Table 1Discharge DispositionDispositionHFpEFHFrEFn=248 (%)n=289(%)Home83 (33)87 (30)Home with Home Health Services101 (41)110 (38)Skilled Nursing Facility52 (21)60 (21)Hospice Services8 (3)27 (9)Expired4 (2)5 (2) Open table in a new tab

BACKGROUND:Heart failure hospitalizations (HFHs) cost the US health care system ∼$20 billion annually. Identifying patients at risk of HFH to enable timely intervention and prevent expensive hospitalization remains a challenge. Implantable cardioverter defibrillators (ICDs) and cardiac resynchronization devices with defibrillation capability (CRT-Ds) collect a host of diagnostic parameters that change with HF status and collectively have the potential to signal an increasing risk of HFH. These device-collected diagnostic parameters include activity, day and night heart rate, atrial tachycardia/atrial fibrillation (AT/AF) burden, mean rate during AT/AF, percent CRT pacing, number of shocks, and intrathoracic impedance. There are thresholds for these parameters that when crossed trigger a notification, referred to as device observation, which gets noted on the device report. We investigated if these existing device observations can stratify patients at varying risk of HFH.METHODS:We analyzed data from 775 patients (age: 69 ± 11 year, 68% male) with CRT-D devices followed for 13 ± 5 months with adjudicated HFHs. HFH rate was computed for increasing number of device observations. Data were analyzed by both excluding and including intrathoracic impedance. HFH risk was assessed at the time of a device interrogation session, and all the data between previous and current follow-up sessions were used to determine the HFH risk for the next 30 days.RESULTS:2276 follow-up sessions in 775 patients were evaluated with 42 HFHs in 37 patients. Percentage of evaluations that were followed by an HFH within the next 30 days increased with increasing number of device observations. Patients with 3 or more device observations were at 42× HFH risk compared to patients with no device observation. Even after excluding intrathoracic impedance, the remaining device parameters effectively stratified patients at HFH risk.CONCLUSION:Available device observations could provide an effective method to stratify patients at varying risk of heart failure hospitalization.

Sleep-disordered breathing (SDB) is the most common comorbidity in patients with heart failure (HF) and has a significant impact on quality of life, morbidity, and mortality. A number of therapeutic options have become available in recent years that can improve quality of life and potentially the outcomes of HF patients with SDB. Unfortunately, SDB is not part of the routine evaluation and management of HF, so it remains untreated in most HF patients. Although recognition of the role of SDB in HF is increasing, clinical guidelines for the management of SDB in HF patients continue to be absent. This article provides an overview of SDB in HF and proposes a clinical care pathway to help clinicians to better recognize and treat SDB in their HF patients.

AimsWe hypothesized that diagnostic data in implantable devices evaluated on the day of discharge from a heart failure hospitalization (HFH) can identify patients at risk for HF readmission (HFR) within 30 days.Methods and resultsIn this retrospective analysis of four studies enrolling patients with CRT devices, we identified patients with a HFH, device data on the day of discharge, and 30‐day post‐discharge clinical follow‐up. Four diagnostic criteria were evaluated on the discharge day: (i) intrathoracic impedance >8 Ω below reference impedance; (ii) AF burden >6 h; (iii) CRT pacing <90%; and (iv) night heart rate >80 b.p.m. Patients were considered to have higher risk for HFR if ≥2 criteria were met, average risk if 1 criterion was met, and lower risk if no criteria were met. A Cox proportional hazards model was used to compare the groups. The data cohort consisted of a total of 265 HFHs in 175 patients, of which 36 (14%) were followed by HFR. On the discharge day, ≥2 criteria were met in 43 (16% of 265 HFHs), only 1 criterion was met in 92 (35%), and none of the four criteria were met in 130 HFHs (49%); HFR rates were 28, 16, and 7%, respectively. HFH with ≥2 criteria met was five times more likely to have HFR compared with HFH with no criteria met (adjusted hazard ratio 5.0; 95% confidence interval 1.9–13.5, P = 0.001).ConclusionDevice‐derived diagnostic criteria evaluated on the day of discharge identified patients at significantly higher risk of HFR.

The aim of the present study was to evaluate whether diagnostic data collected after a heart failure (HF) hospitalization can identify patients with HF at risk of early readmission. The diagnostic data from cardiac resynchronization therapy defibrillator (CRT-D) devices can identify outpatient HF patients at risk of future HF events. In the present retrospective analysis of 4 studies, we identified patients with CRT-D devices, with a HF admission, and 30-day postdischarge follow-up data. The evaluation of the diagnostic data for impedance, atrial fibrillation, ventricular heart rate during atrial fibrillation, loss of CRT-D pacing, night heart rate, and heart rate variability was modeled to simulate a review of the first 7 days after discharge on the seventh day. Using a combined score created from the device parameters that were significant univariate predictors of 30-day HF readmission, 3 risk groups were created. A Cox proportional hazards model adjusting for age, gender, New York Heart Association class, and length of stay during the index hospitalization was used to compare the groups. The study cohort of 166 patients experienced a total of 254 HF hospitalizations, with 34 readmissions within 30 days. Daily impedance, high atrial fibrillation burden with poor rate control (>90 beat/min) or reduced CRT-D pacing (<90% pacing), and night heart rate >80 beats/min were significant univariate predictors of 30-day HF readmission. Patients in the "high"-risk group for the combined diagnostic had a significantly greater risk (hazard ratio 25.4, 95% confidence interval 3.6 to 179.0, p = 0.001) compared to the "low"-risk group for 30-day readmission for HF. In conclusion, device-derived HF diagnostic criteria evaluated 7 days after discharge identified patients at significantly greater risk of a HF event within 30 days after discharge.