Roy S. Small

Right Ventricular Outflow Versus Apical Pacing in Pacemaker Patients with Congestive Heart Failure and Atrial Fibrillation

Introduction: Prior studies suggest that right ventricular apical (RVA) pacing has deleterious effects. Whether the right ventricular outflow tract (RVOT) is a more optimal site for permanent pacing in patients with congestive heart failure (CHF) has not been established.

Sleep-Disordered Breathing in Heart Failure: Identifying and Treating an Important but Often Unrecognized Comorbidity in Heart Failure Patients

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.

Threshold crossing of device-based intrathoracic impedance trends identifies relatively increased mortality risk

Aims Threshold crossings of impedance trends detected by implanted devices have been associated with clinically relevant heart failure events, but long-term prognosis of such events has not been demonstrated. The aim of this study is to examine the relationship between alterations in intrathoracic impedance and mortality risk in patients with implantable devices. Methods and results We reviewed remote monitoring data in the de-identified Medtronic CareLink® Discovery Link that captured intrathoracic impedance trends for >6 months. The initial 6 months of the cardiac and impedance trends were used as the observation period to create the patient groups and cross-referenced with the Social Security Death Index for mortality data. In our study cohort of 21 217 patients, 36% experienced impedance threshold crossing within the initial 6 months of monitoring (defined as the ‘early threshold crossing’ group). Patients with early threshold crossings demonstrated an increased risk of age- and gender-adjusted all-cause mortality [hazard ratio (HR) 2.15, 95% confidence interval (CI) 1.95–2.38, P< 0.0001]. Increased mortality risk remained significant when analysed in subgroups of patients without defibrillator shock (HR 2.10, 95% CI 1.90–2.34, P< 0.0001, n= 1621) or within those patients without device-detectable atrial fibrillation (AF) during the initial 6 months of monitoring (HR 2.09, 95% CI 1.86–2.34, P< 0.0001, n= 17 235). Both the number and the duration of early threshold crossings of impedance trends detectable by implanted devices were associated with increased mortality risk. Furthermore, the improvement of altered impedance trends portends more favourable prognosis. Conclusions Threshold crossing of impedance trends detectable by implanted devices is associated with relatively increased mortality risk even after adjusted for demographic, device-detected AF, or defibrillator shocks.

Implantable device diagnostics on day of discharge identify heart failure patients at increased risk for early readmission for heart failure

We 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.

A critical link between heart failure self-care and intrathoracic impedance.

Background:Effective self-care is regarded as essential to the management of heart failure (HF). The influence of self-care on HF decompensation, however, is not well understood. Accordingly, we examined the relationship between self-care and fluid accumulation accompanying worsening HF as indexed by decreasing intrathoracic impedance (Z). Methods:Z data were collected from 58 HF patients with OptiVol enabled devices (Medtronic Inc, Minneapolis, Minnesota). Heart failure self-care was measured with the European Heart Failure Self-care Behaviour Scale. Regression modeling was used to describe the influence of HF self-care on the likelihood of a fluid index (FI) threshold crossing, the number of threshold crossings, and number of days spent above threshold. Results:Patients were elderly (74.98 [SD, 8.12] years), with a mean left ventricular ejection fraction of 26.21% (SD, 9.77%), and 63.7% had class New York Heart Association III HF. Patients were followed up for 317 (SD, 96) days; 65.5% had FI threshold crossings (mean 1.45 [SD, 1.56] crossings), spending an average of 33.8 (SD, 42.4) days above FI threshold. Controlling for age, sex, left ventricular ejection fraction, functional class, and duration of follow-up, each additional point on the European Heart Failure Self-care Behaviour Scale was associated with an increase in the odds of having had an FI threshold crossing (adjusted odds ratio, 1.201; 95% confidence interval, 1.013-1.424; P < .05) and more days spent above FI threshold (incidence rate ratio, 1.051; 95% confidence interval, 1.002-1.102; P < .05). Conclusion:Intrathoracic impedance measurements obtained from implantable devices provide important information regarding the influence of self-care on fluid accumulation in patients with HF.

Stratifying patients at the risk of heart failure hospitalization using existing device diagnostic thresholds.

Background Heart failure hospitalizations (HFHs) cost the US health care system ~

Remote Monitoring in Heart Failure: the Current State

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.

Improving the Efficiency of Heart Failure Care

Opinion statementThe 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.

Assessing Impedance in Heart Failure From Device Diagnostics to Population Health Opportunities

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.

Integrating device-based monitoring into clinical practice: insights from a large heart failure clinic.

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 …