Publications

BACKGROUND: Use of an antibiotic-eluting envelope (AEE) during cardiac implantable electronic device procedures reduces infection risk but increases procedural costs. We aim to estimate the cost-effectiveness of AEE use during cardiac implantable electronic device procedures among patients with heart failure.

METHODS: A state-transition cohort model of heart failure patients undergoing cardiac implantable electronic device implantation or generator replacement was developed with input parameters estimated from randomized trials, registries, surveys, and claims data. Effectiveness was estimated from the World-Wide Randomized Antibiotic Envelope Infection Prevention Trial. AEE was assumed to cost $953 per unit. The model projected mortality, quality-adjusted life-years, costs, and the incremental cost-effectiveness ratio of AEE use compared with usual care from a US healthcare sector perspective over a lifetime horizon. We assumed a cost-effectiveness threshold of $100 000 per quality-adjusted life-year gained.

RESULTS: Compared with usual care, AEE use in initial implantations produced an incremental cost-effectiveness ratio of $112 000 per quality-adjusted life-year gained (39% probability of being cost-effective). In generator replacement procedures, AEE use produced an incremental cost-effectiveness ratio of $54 000 per quality-adjusted life-year gained (84% probability of being cost-effective). Results were sensitive to the underlying rate of infection, cost of the AEE, and durability of AEE effectiveness.

CONCLUSIONS: Universal AEE use for cardiac implantable electronic device procedures in patients with heart failure with reduced ejection fraction is unlikely to be cost-effective, reinforcing the need for individualized risk assessment to guide uptake of the AEE in clinical practice. Selective use in patients at increased risk of infection, such as those undergoing generator replacement procedures, is more likely to meet health system value benchmarks.

BACKGROUND: Frailty is associated with significant morbidity and mortality in older adults. Whether frailty predicts adverse outcomes after percutaneous left atrial appendage closure (LAAC) remains uncertain.

OBJECTIVE: The purpose of this study was to examine the association between frailty and clinical outcomes after percutaneous LAAC.

METHODS: We identified patients 65 years and older in Medicare fee-for-service claims who underwent LAAC between October 1, 2016, and December 31, 2019. Patients were identified as frail on the basis of the Hospital Frailty Risk Score (HFRS), a validated frailty measure centered on health resource utilization, with the cohort stratified into low (<5), intermediate (5-15), and high (>15) risk groups.

RESULTS: Of the 21,787 patients who underwent LAAC, 10,740 (49.3%) were considered frail (HFRS >5), including 3441 (15.8%) in the high-risk group. The mortality rate (up to 1095 days) were 16.1% in the low-risk group, 26.7% in the intermediate-risk group, and 41.1% in the high-risk group (P < .001). After adjusting for age, sex, and comorbidities, HFRS >15 (compared with HFRS <5) was associated with a higher risk of long hospital stay (odds ratio [OR] 8.29; 95% confidence interval [CI] 5.94-11.57), 30-day readmission (OR 1.80, 95% CI 1.58-2.05), 30-day mortality (OR 5.68, 95% CI 3.40-9.40), and 1-year mortality (OR 2.83, 95% CI 2.39-3.35). In restricted cubic spline models, the adjusted OR for all outcomes monotonically increased with increasing HFRS.

CONCLUSION: Frailty is common in patients undergoing LAAC and is associated with increased risks of long hospital stay, readmissions, and short-term mortality.

Cardiac implantable electronic device (CIED) procedures require informed consent and, ideally, shared decision making to guide patients through their experiences as CIED recipients. The information that different patients need or want about cybersecurity risk varies. This article considers device cybersecurity risks in light of federal guidelines and suggests strategies for communicating these risks clearly during informed consent conversations and follow-up.

Shared decision making (SDM) has been advocated to improve patient care, patient decision acceptance, patient-provider communication, patient motivation, adherence, and patient reported outcomes. Documentation of SDM is endorsed in several society guidelines and is a condition of reimbursement for selected cardiovascular and cardiac arrhythmia procedures. However, many clinicians argue that SDM already occurs with clinical encounter discussions or the process of obtaining informed consent and note the additional imposed workload of using and documenting decision aids without validated tools or evidence that they improve clinical outcomes. In reality, SDM is a process and can be done without decision tools, although the process may be variable. Also, SDM advocates counter that the low-risk process of SDM need not be held to the high bar of demonstrating clinical benefit and that increasing the quality of decision making should be sufficient. Our review leverages a multidisciplinary group of experts in cardiology, cardiac electrophysiology, epidemiology, and SDM, as well as a patient advocate. Our goal is to examine and assess SDM methodology, tools, and available evidence on outcomes in patients with heart rhythm disorders to help determine the value of SDM, assess its possible impact on electrophysiological procedures and cardiac arrhythmia management, better inform regulatory requirements, and identify gaps in knowledge and future needs.

OBJECTIVE: The authors sought to describe state-to-state variations in the scope of statutory authority granted to default surrogates who decide on mental health treatment for incapacitated patients.

METHODS: The authors investigated state statutes delineating the powers of default surrogates to make decisions about mental health treatment. Statutes in all 50 U.S. states and the District of Columbia were identified and analyzed independently by three reviewers. Research was conducted from August 2017 to November 2018 and updated in January 2020.

RESULTS: State statutes varied in approaches to default surrogate decision making for mental health treatment. Eight states' statutes delegate broad authority to surrogates, whereas 25 states prohibit surrogates from giving consent for specific therapies. Thirteen states are silent on whether surrogates may make decisions.

CONCLUSIONS: Heterogeneity among state statutory laws contributes to complexity of treating patients without decisional capacity. This variability encumbers efforts to support surrogates and clinicians and may contribute to health disparities.

California has focused on health equity in the state's COVID-19 reopening plan. The Blueprint for a Safer Economy assigns each of California's 58 counties into 1 of 4 tiers based on 2 metrics: test positivity rate and adjusted case rate. To advance to the next less-restrictive tier, counties must meet that tier's test positivity and adjusted case rate thresholds. In addition, counties must have a plan for targeted investments within disadvantaged communities, and counties with more than 106 000 residents must meet an equity metric. California's explicit incorporation of health equity into its reopening plan underscores the interrelated fate of its residents during the COVID-19 pandemic and creates incentives for action. This article evaluates the benefits and challenges of this novel health equity focus, and outlines recommendations for other US states to address disparities in their reopening plans.

While cardiorespiratory fitness is strongly associated with mortality and diverse outcomes, routine measurement is limited. We used smartphone-derived physical activity data to estimate fitness among 50 older adults. We recruited iPhone owners undergoing cardiac stress testing and collected recent iPhone physical activity data. Cardiorespiratory fitness was measured as peak metabolic equivalents of task (METs) achieved on cardiac stress test. We then estimated peak METs using multivariable regression models incorporating iPhone physical activity data, and validated with bootstrapping. Individual smartphone variables most significantly correlated with peak METs (p-values both < 0.001) included daily peak gait speed averaged over the preceding 30 days (r = 0.63) and root mean square of the successive differences of daily distance averaged over 365 days (r = 0.57). The best-performing multivariable regression model included the latter variable, as well as age and body mass index. This model explained 68% of variability in observed METs (95% CI 46%, 81%), and estimated peak METs with a bootstrapped mean absolute error of 1.28 METs (95% CI 0.98, 1.60). Our model using smartphone physical activity estimated cardiorespiratory fitness with high performance. Our results suggest larger, independent samples might yield estimates accurate and precise for risk stratification and disease prognostication.