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Background There are limited data on the use of angiotensin receptor neprilysin inhibitors (ARNIs) in minority populations with heart failure (HF) with reduced ejection fraction. We used data from the CHAMP-HF (Change the Management of Patients With Heart Failure) registry to evaluate ARNI initiation and associated changes in health status and clinical outcomes across different races and ethnicities. Methods and Results CHAMP-HF was a prospective, observational registry of US outpatients with chronic HF with reduced ejection fraction. We compared patients starting ARNI with patients not starting ARNI using a propensity-matched analysis. Patients were grouped as Hispanic, non-Hispanic Black, non-Hispanic White, or non-Hispanic other individuals, where "non-Hispanic other" consists of all patients who did not identify as Hispanic, Black, or White. Health status was assessed using the 12-item Kansas City Cardiomyopathy Questionnaire. Outcomes were analyzed with multivariable models that included race and ethnicity, ARNI initiation, and an interaction term between race and ethnicity and ARNI initiation. Cox proportional hazards models were used for death/HF hospitalization, and multiple regression was used for change in Kansas City Cardiomyopathy Questionnaire score. The analysis included 1516 patients, with 758 patients in each group (ARNI and no ARNI). Changes in Kansas City Cardiomyopathy Questionnaire score after ARNI initiation were similar among all race and ethnicity groups (mean [SD], non-Hispanic White individuals, 3.5 [19.0]; non-Hispanic Black individuals, 2.0 [17.0]; non-Hispanic other individuals, 5.5 [20.3]; and Hispanic individuals, 3.2 [20.1]), with no statistically significant interaction between race and ethnicity and ARNI initiation (P=0.21). There was similarly no statistically significant interaction between race and ethnicity and ARNI initiation for HF hospitalization (P=0.82) or all-cause mortality (P=0.92). Conclusions In a large registry of outpatients with HF with reduced ejection fraction, the association between ARNI initiation and outcomes did not differ by race and ethnicity. These data support the use of ARNI therapy for chronic HF with reduced ejection fraction irrespective of race and ethnicity.

AimsWe aimed to develop a risk prediction tool that incorporated both clinical events and worsening health status for patients with heart failure (HF) with reduced ejection fraction (HFrEF). Identifying patients with HFrEF at increased risk of a poor outcome may enable proactive interventions that improve outcomes.Methods and resultsWe used data from a longitudinal HF registry, CHAMP-HF, to develop a risk prediction tool for poor outcomes over the next 6 months. A poor outcome was defined as death, an HF hospitalization, or a ≥20-point decrease (or decrease below 25) in 12-item Kansas City Cardiomyopathy Questionnaire (KCCQ-12) overall summary score. Among 4546 patients in CHAMP-HF, 1066 (23%) experienced a poor outcome within 6 months (1.3% death, 11% HF hospitalization, and 11% change in KCCQ-12). The model demonstrated moderate discrimination (c-index = 0.65) and excellent calibration with observed data. The following variables were associated with a poor outcome: age, race, education, New York Heart Association class, baseline KCCQ-12, atrial fibrillation, coronary disease, diabetes, chronic kidney disease, smoking, prior HF hospitalization, and systolic blood pressure. We also created a simplified model with a 0-10 score using six variables (New York Heart Association class, KCCQ-12, coronary disease, chronic kidney disease, prior HF hospitalization, and systolic blood pressure) with similar discrimination (c-index = 0.63). Patients scoring 0-3 were considered low risk (event rate 40%).ConclusionsThe PROMPT-HF risk model can identify outpatients with HFrEF at increased risk of poor outcomes, including clinical events and health status deterioration. With further validation, this model may help inform therapeutic decision making.

BackgroundHealth status outcomes are increasingly being promoted as measures of health care quality, given their importance to patients. In heart failure (HF), an American College of Cardiology/American Heart Association Task Force proposed using the proportion of patients with preserved health status as a quality measure but not as a performance measure because risk adjustment methods were not available.MethodsWe built risk adjustment models for alive with preserved health status and for preserved health status alone in a prospective registry of outpatients with HF with reduced ejection fraction across 146 US centers between December 2015 and October 2017. Preserved health status was defined as not having a ≥5-point decrease in the Kansas City Cardiomyopathy Questionnaire Overall Summary score at 1 year. Using only patient-level characteristics, hierarchical multivariable logistic regression models were developed for 1-year outcomes and validated using data from 1 to 2 years. We examined model calibration, discrimination, and variability in sites' unadjusted and adjusted rates.ResultsAmong 3932 participants (median age [interquartile range] 68 years [59-75], 29.7% female, 75.4% White), 2703 (68.7%) were alive with preserved health status, 902 (22.9%) were alive without preserved health status, and 327 (8.3%) had died by 1 year. The final risk adjustment model for alive with preserved health status included baseline Kansas City Cardiomyopathy Questionnaire Overall Summary, age, race, employment status, annual income, body mass index, depression, atrial fibrillation, renal function, number of hospitalizations in the past 1 year, and duration of HF (optimism-corrected C statistic=0.62 with excellent calibration). Similar results were observed when deaths were ignored. The risk standardized proportion of patients alive with preserved health status across the 146 sites ranged from 62% at the 10th percentile to 75% at the 90th percentile. Variability across sites was modest and changed minimally with risk adjustment.ConclusionsThrough leveraging data from a large, outpatient, observational registry, we identified key factors to risk adjust sites' proportions of patients with preserved health status. These data lay the foundation for building quality measures that quantify treatment outcomes from patients' perspectives.

BackgroundComorbidities are common in patients with atrial fibrillation (AF) and affect prognosis, yet are often undertreated. However, contemporary rates of use of guideline-directed therapies (GDT) for non-AF comorbidities and their association with outcomes are not well described.MethodsWe used the Outcomes Registry for Better Informed Treatment of AF (ORBIT-AF) to test the association between GDT for non-AF comorbidities and major adverse cardiac or neurovascular events (MACNE; cardiovascular death, myocardial infarction, stroke/thromboembolism, or new-onset heart failure), all-cause mortality, new-onset heart failure, and AF progression. Adjustment was performed using Cox proportional hazards models and logistic regression.ResultsOnly 6,782 (33%) of the 20,434 patients eligible for 1 or more GDT for non-AF comorbidities received all indicated therapies. Use of all comorbidity-specific GDT was highest for patients with hyperlipidemia (75.6%) and lowest for those with diabetes mellitus (43.1%). Use of "all eligible" GDT was associated with a nonsignificant trend toward lower rates of MACNE (HR 0.90 [0.79-1.02]) and all-cause mortality (HR 0.90 [0.80-1.01]). Use of GDT for heart failure was associated with a lower risk of all-cause mortality (HR 0.77 [0.67-0.89]), and treatment of obstructive sleep apnea was associated with a lower risk of AF progression (OR 0.75 [0.62-0.90]).ConclusionsIn AF patients, there is underuse of GDT for non-AF comorbidities. The association between GDT use and outcomes was strongest in heart failure and obstructive sleep apnea patients where use of GDT was associated with lower mortality and less AF progression.

Background Chronic kidney disease ( CKD ) is a common comorbidity in patients with atrial fibrillation. The presence of CKD complicates drug selection for stroke prevention and rhythm control. Methods and Results Patients enrolled in ORBIT AF (Outcomes Registry for Better Informed Treatment of Atrial Fibrillation) with baseline renal function and follow-up data were included (N=9019). CKD was defined as an estimated creatinine clearance

BackgroundTherapeutic decisions in atrial fibrillation (AF) are often influenced by assessment of bleeding risk. However, existing bleeding risk scores have limitations.ObjectivesWe sought to develop and validate a novel bleeding risk score using routinely available clinical information to predict major bleeding in a large, community-based AF population.MethodsWe analysed data from Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT-AF), a prospective registry that enrolled incident and prevalent AF patients at 176 US sites. Using Cox proportional hazards regression, we identified factors independently associated with major bleeding among patients taking oral anticoagulation (OAC) over a median follow-up of 2 years (interquartile range = 1.6-2.5). We also created a numerical bedside risk score that included the five most predictive risk factors weighted according to their strength of association with major bleeding. The predictive performance of the full model, the simple five-item score, and two existing risk scores (hypertension, abnormal renal/liver function, stroke, bleeding history or predisposition, labile INR, elderly, drugs/alcohol concomitantly, HAS-BLED, and anticoagulation and risk factors in atrial fibrillation, ATRIA) were then assessed in both the ORBIT-AF cohort and a separate clinical trial population, Rivaroxaban Once-daily oral direct factor Xa inhibition compared with vitamin K antagonism for prevention of stroke and embolism trial in atrial fibrillation (ROCKET-AF).ResultsAmong 7411 ORBIT-AF patients taking OAC, the rate of major bleeding was 4.0/100 person-years. The full continuous model (12 variables) and five-factor ORBIT risk score (older age [75+ years], reduced haemoglobin/haematocrit/history of anaemia, bleeding history, insufficient kidney function, and treatment with antiplatelet) both had good ability to identify those who bled vs. not (C-index 0.69 and 0.67, respectively). These scores both had similar discrimination, but markedly better calibration when compared with the HAS-BLED and ATRIA scores in an external validation population from the ROCKET-AF trial.ConclusionsThe five-element ORBIT bleeding risk score had better ability to predict major bleeding in AF patients when compared with HAS-BLED and ATRIA risk scores. The ORBIT risk score can provide a simple, easily remembered tool to support clinical decision making.

BackgroundAlthough digoxin has long been used to treat atrial fibrillation (AF) and heart failure (HF), its safety remains controversial.ObjectivesThis study sought to describe digoxin use over time in patients with AF who were stratified by the presence or absence of HF, to characterize the predictors of digoxin use and initiation, and to correlate digoxin use with outcomes.MethodsLongitudinal patterns of digoxin use and its association with a variety of outcomes were assessed in a prospective outpatient registry conducted at 174 U.S. sites with enrollment from June 2010 to August 2011.ResultsAmong 9,619 patients with AF and serial follow-up every 6 months for up to 3 years, 2,267 (23.6%) received digoxin at study enrollment, 681 (7.1%) were initiated on digoxin during follow-up, and 6,671 (69.4%) were never prescribed digoxin. After adjusting for other medications, heart rate was 72.9 beats/min among digoxin users and 71.5 beats/min among nonusers (p < 0.0001). Prevalent digoxin use at registry enrollment was not associated with subsequent onset of symptoms, hospitalization, or mortality (in patients with HF, adjusted hazard ratio [HR] for death: 1.04; without HF, HR: 1.22). Incident digoxin use during follow-up was not associated with subsequent death in patients with HF (propensity adjusted HR: 1.05), but was associated with subsequent death in those without HF (propensity adjusted HR: 1.99).ConclusionsAfter adjustment for detailed clinical factors, digoxin use in registry patients with AF had a neutral association with outcomes under most circumstances. Because of the multiple conflicting observational reports about digoxin's safety and possible concerns in specific clinical situations, a large pragmatic trial of digoxin therapy in AF is needed.

Purpose: To understand nursing home workers' experience during the coronavirus disease 2019 (COVID-19) pandemic and investigate the prevalence of health-related quality of life, emotional distress, job satisfaction, and the impact of the pandemic. Method: The Healthcare Worker Exposure Response and Outcomes (HERO) Registry served as the data source for this descriptive cross-sectional analysis. Recruitment was conducted nationally. Eligible nursing home workers (N = 1,409) enrolled in the study online, self-reported demographic and employment characteristics, and completed electronic surveys. Results: Nursing home workers reported overall good physical health, frequent depressive symptoms, burnout, and a high prevalence of feeling tired, stressed, having trouble sleeping, and feeling worried. Age and race were found to be positively associated with the impact of the pandemic. Conclusion: Findings demonstrate the difficulties and challenges nursing home workers faced during the COVID-19 pandemic. Future research needs to evaluate the relationships among nursing home workers' roles, mental health, depressive symptoms, and prevalence of burnout with a larger, more diverse sample. [Research in Gerontological Nursing, 17(3), 131–140.] [ABSTRACT FROM AUTHOR]

Propensity score weighting is an important tool for comparative effectiveness research. Besides the inverse probability of treatment weights (IPW), recent development has introduced a general class of balancing weights, corresponding to alternative target populations and estimands. In particular, the overlap weights (OW) lead to optimal covariate balance and estimation efficiency, and a target population of scientific and policy interest. We develop the R package PSweight to provide a comprehensive design and analysis platform for causal inference based on propensity score weighting. PSweight supports (i) a variety of balancing weights, (ii) binary and multiple treatments, (iii) simple and augmented weighting estimators, (iv) nuisance-adjusted sandwich variances, and (v) ratio estimands. PSweight also provides diagnostic tables and graphs for covariate balance assessment. We demonstrate the functionality of the package using a data example from the National Child Development Survey (NCDS), where we evaluate the causal effect of educational attainment on income. [ABSTRACT FROM AUTHOR]