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AIMS: Heart failure (HF) is a clinical syndrome with no definitive diagnostic tests. HF registries are often based on manual reviews of medical records of hospitalized HF patients identified using International Classification of Diseases (ICD) codes. However, most HF patients are not hospitalized, and manual review of big electronic health record (EHR) data is not practical. The US Department of Veterans Affairs (VA) has the largest integrated healthcare system in the nation, and an estimated 1.5 million patients have ICD codes for HF (HF ICD-code universe) in their VA EHR. The objective of our study was to develop artificial intelligence (AI) models to phenotype HF in these patients. METHODS AND RESULTS: The model development cohort (n = 20 000: training, 16 000; validation 2000; testing, 2000) included 10 000 patients with HF and 10 000 without HF who were matched by age, sex, race, inpatient/outpatient status, hospital, and encounter date (within 60 days). HF status was ascertained by manual chart reviews in VAs External Peer Review Program for HF (EPRP-HF) and non-HF status was ascertained by the absence of ICD codes for HF in VA EHR. Two clinicians annotated 1000 random snippets with HF-related keywords and labelled 436 as HF, which was then used to train and test a natural language processing (NLP) model to classify HF (positive predictive value or PPV, 0.81; sensitivity, 0.77). A machine learning (ML) model using linear support vector machine architecture was trained and tested to classify HF using EPRP-HF as cases (PPV, 0.86; sensitivity, 0.86). From the HF ICD-code universe, we randomly selected 200 patients (gold standard cohort) and two clinicians manually adjudicated HF (gold standard HF) in 145 of those patients by chart reviews. We calculated NLP, ML, and NLP + ML scores and used weighted F scores to derive their optimal threshold values for HF classification, which resulted in PPVs of 0.83, 0.77, and 0.85 and sensitivities of 0.86, 0.88, and 0.83, respectively. HF patients classified by the NLP + ML model were characteristically and prognostically similar to those with gold standard HF. All three models performed better than ICD code approaches: one principal hospital discharge diagnosis code for HF (PPV, 0.97; sensitivity, 0.21) or two primary outpatient encounter diagnosis codes for HF (PPV, 0.88; sensitivity, 0.54). CONCLUSIONS: These findings suggest that NLP and ML models are efficient AI tools to phenotype HF in big EHR data to create contemporary HF registries for clinical studies of effectiveness, quality improvement, and hypothesis generation.

This document describes performance measures for heart failure that are appropriate for public reporting or pay-for-performance programs and is meant to serve as a focused update of the "2020 ACC/AHA Clinical Performance and Quality Measures for Adults With Heart Failure: A Report of the American College of Cardiology/American Heart Association Task Force on Performance Measures." The new performance measures are taken from the "2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines" and are selected from the strongest recommendations (Class 1 or Class 3). In contrast, quality measures may not have as much evidence base and generally comprise metrics that might be useful for clinicians and health care organizations for quality improvement but are not yet appropriate for public reporting or pay-for-performance programs. New performance measures include optimal blood pressure control in patients with heart failure with preserved ejection fraction, the use of sodium-glucose cotransporter-2 inhibitors for patients with heart failure with reduced ejection fraction, and the use of guideline-directed medical therapy in hospitalized patients. New quality measures include the use of sodium-glucose cotransporter-2 inhibitors in patients with heart failure with mildly reduced and preserved ejection fraction, the optimization of guideline-directed medical therapy prior to intervention for chronic secondary severe mitral regurgitation, continuation of guideline-directed medical therapy for patients with heart failure with improved ejection fraction, identifying both known risks for cardiovascular disease and social determinants of health, patient-centered counseling regarding contraception and pregnancy risks for individuals with cardiomyopathy, and the need for a monoclonal protein screen to exclude light chain amyloidosis when interpreting a bone scintigraphy scan assessing for transthyretin cardiac amyloidosis.

ImportanceEarly detection of atrial fibrillation (AF) may help prevent adverse cardiovascular events such as stroke. Deep learning applied to electrocardiograms (ECGs) has been successfully used for early identification of several cardiovascular diseases.ObjectiveTo determine whether deep learning models applied to outpatient ECGs in sinus rhythm can predict AF in a large and diverse patient population.Design, setting, and participantsThis prognostic study was performed on ECGs acquired from January 1, 1987, to December 31, 2022, at 6 US Veterans Affairs (VA) hospital networks and 1 large non-VA academic medical center. Participants included all outpatients with 12-lead ECGs in sinus rhythm.Main outcomes and measuresA convolutional neural network using 12-lead ECGs from 2 US VA hospital networks was trained to predict the presence of AF within 31 days of sinus rhythm ECGs. The model was tested on ECGs held out from training at the 2 VA networks as well as 4 additional VA networks and 1 large non-VA academic medical center.ResultsA total of 907 858 ECGs from patients across 6 VA sites were included in the analysis. These patients had a mean (SD) age of 62.4 (13.5) years, 6.4% were female, and 93.6% were male, with a mean (SD) CHA2DS2-VASc (congestive heart failure, hypertension, age, diabetes mellitus, prior stroke or transient ischemic attack or thromboembolism, vascular disease, age, sex category) score of 1.9 (1.6). A total of 0.2% were American Indian or Alaska Native, 2.7% were Asian, 10.7% were Black, 4.6% were Latinx, 0.7% were Native Hawaiian or Other Pacific Islander, 62.4% were White, 0.4% were of other race or ethnicity (which is not broken down into subcategories in the VA data set), and 18.4% were of unknown race or ethnicity. At the non-VA academic medical center (72 483 ECGs), the mean (SD) age was 59.5 (15.4) years and 52.5% were female, with a mean (SD) CHA2DS2-VASc score of 1.6 (1.4). A total of 0.1% were American Indian or Alaska Native, 7.9% were Asian, 9.4% were Black, 2.9% were Latinx, 0.03% were Native Hawaiian or Other Pacific Islander, 74.8% were White, 0.1% were of other race or ethnicity, and 4.7% were of unknown race or ethnicity. A deep learning model predicted the presence of AF within 31 days of a sinus rhythm ECG on held-out test ECGs at VA sites with an area under the receiver operating characteristic curve (AUROC) of 0.86 (95% CI, 0.85-0.86), accuracy of 0.78 (95% CI, 0.77-0.78), and F1 score of 0.30 (95% CI, 0.30-0.31). At the non-VA site, AUROC was 0.93 (95% CI, 0.93-0.94); accuracy, 0.87 (95% CI, 0.86-0.88); and F1 score, 0.46 (95% CI, 0.44-0.48). The model was well calibrated, with a Brier score of 0.02 across all sites. Among individuals deemed high risk by deep learning, the number needed to screen to detect a positive case of AF was 2.47 individuals for a testing sensitivity of 25% and 11.48 for 75%. Model performance was similar in patients who were Black, female, or younger than 65 years or who had CHA2DS2-VASc scores of 2 or greater.Conclusions and relevanceDeep learning of outpatient sinus rhythm ECGs predicted AF within 31 days in populations with diverse demographics and comorbidities. Similar models could be used in future AF screening efforts to reduce adverse complications associated with this disease.

AIMS: Sex differences in long-term outcomes following hospitalization for heart failure (HF) across ejection fraction (EF) subtypes are not well described. In this study, we evaluated the risk of mortality and rehospitalization among males and females across the spectrum of EF over 5 years of follow-up following an index HF hospitalization event. METHODS AND RESULTS: Patients hospitalized with HF between 1 January 2006 and 31 December 2014 from the American Heart Associations Get With The Guidelines-Heart Failure registry with available 5-year follow-up using Medicare Part A claims data were included. The association between sex and risk of mortality and readmission over a 5-year follow-up period for each HF subtype (HF with reduced EF [HFrEF, EF ≤40%], HF with mildly reduced EF [HFmrEF, EF 41-49%], and HF with preserved EF [HFpEF, EF >50%]) was assessed using adjusted Cox models. The effect modification by the HF subtype for the association between sex and outcomes was assessed by including multiplicative interaction terms in the models. A total of 155 670 patients (median age: 81 years, 53.4% female) were included. Over 5-year follow-up, males and females had comparably poor survival post-discharge; however, females (vs. males) had greater years of survival lost to HF compared with the median age- and sex-matched US population (HFpEF: 17.0 vs. 14.6 years; HFrEF: 17.3 vs. 15.1 years; HFmrEF: 17.7 vs. 14.6 years for age group 65-69 years). In adjusted analysis, females (vs. males) had a lower risk of 5-year mortality (adjusted hazard ratio [aHR] 0.89, 95% confidence interval [CI] 0.87-0.90, p

BackgroundThe burden of heart failure is growing. Guideline-directed medical therapies (GDMT) reduce adverse outcomes in heart failure with reduced ejection fraction (HFrEF). Whether there is geographic variation in HFrEF quality of care is not well described.ObjectivesThis study evaluated variation nationally for prescription of GDMT within the Veterans Health Administration.MethodsA cohort of Veterans with HFrEF had their address linked to hospital referral regions (HRRs). GDMT prescription was defined using pharmacy data between July 1, 2020, and July 1, 2021. Within HRRs, we calculated the percentage of Veterans prescribed GDMT and a composite GDMT z-score. National choropleth maps were created to evaluate prescription variation. Associations between GDMT performance and demographic characteristics were evaluated using linear regression.ResultsMaps demonstrated significant variation in the HRR composite score and GDMT prescriptions. Within HRRs, the prescription of beta-blockers to Veterans was highest with a median of 80% (IQR: 77.3%-82.2%) followed by angiotensin-converting enzyme inhibitor/angiotensin receptor blocker/angiotensin receptor-neprilysin inhibitors (69.3%; IQR: 66.4%-72.1%), sodium-glucose cotransporter 2 inhibitors (10.3%; IQR: 7.7%-12.8%), mineralocorticoid receptor antagonists (29.2%; IQR: 25.8%-33.9%), and angiotensin receptor-neprilysin inhibitors (12.2%; IQR: 8.6%-15.3%). HRR composite GDMT z-scores were inversely associated with the HRR median Gini coefficient (R = -0.13; P = 0.0218) and the percentage of low-income residents (R = -0.117; P = 0.0413).ConclusionsWide geographic differences exist for HFrEF care. Targeted strategies may be required to increase GDMT prescription for Veterans in lower-performing regions, including those affected by income inequality and poverty.

BACKGROUND: Patient-reported outcomes (PROs) may improve care for patients with heart failure. The Kansas City Cardiomyopathy Questionnaire-12 (KCCQ-12) is a patient survey that captures symptom frequency, symptom burden, physical limitations, social limitations, and quality of life. Despite the utility of PROs and the KCCQ-12, the implementation and routine use of these measures can be difficult. We conducted an evaluation of clinician perceptions of the KCCQ-12 to identify barriers and facilitators to implementation into clinical practice. METHODS: We conducted interviews with cardiologists from 4 institutions across the United States and Canada (n=16) and observed clinic visits at 1 institution in Northern California (n=5). Qualitative analysis was conducted in 2 rounds: (1) rapid analysis constructed around major themes related to the aims of the study and (2) content analysis with codes derived from the rapid analysis and implementation science. RESULTS: Most heart failure physicians and advanced practice clinicians reported that the KCCQ-12 was acceptable, appropriate, and useful in clinical care. Clinician engagement efforts, trialability, and the straightforward design of the KCCQ-12 facilitated its use in clinical care. Further opportunities identified to facilitate implementation include more streamlined integration into the electronic health record and comprehensive staff education on PROs. Participants highlighted that the KCCQ-12 was useful in clinic visits to improve the consistency of patient history taking, focus patient-clinician conversations, collect a more accurate account of patient quality of life, track trends in patient well-being over time, and refine clinical decision-making. CONCLUSIONS: In this qualitative study, clinicians reported that the KCCQ-12 enhanced several aspects of heart failure patient care. Use of the KCCQ-12 was facilitated by a robust clinician engagement campaign and the design of the KCCQ-12 itself. Future implementation of PROs in heart failure clinic should focus on streamlining electronic health record integration and providing additional staff education on the value of PROs. REGISTRATION: URL: https://clinicaltrials.gov; Unique identifier: NCT04164004.

Introduction: In patients with heart failure with reduced ejection fraction (HFrEF), use of guideline directed medical therapies (GDMT) reduces mortality. Whether there is geographic variation in GDMT prescribing is not well-characterized. Hypothesis: We assessed the hypothesis that there is wide geographic variation nationally within the Veterans Affairs (VA) healthcare system for the receipt of GDMT. Methods: We linked the primary residence address of a cohort of Veterans with HFrEF receiving care at VA facilities (n=178,856) to hospital referral regions (HRRs). Using VA and non-VA pharmacy data between July 1, 2020 and July 1, 2021, we defined receipt of GDMT. For each HRR, we calculated the percentage of eligible Veterans that were prescribed each class of GDMT and a composite GDMT z-score. Lastly, we constructed national choropleth maps to depict HRR geographic variation in composite z-scores and prescription of each class of GDMT. Results: There was significant variation in individual GDMT class prescription and composite score across HRRs as shown in choropleth maps ( Figure) . Within HRRs, beta-blocker prescription was highest, with a median 80% of Veterans (interquartile range [IQR] 77.3% to 82.2%), afterload-reducing agents including angiotensin converting enzyme inhibitor / angiotensin receptor blocker / angiotensin receptor-neprilysin inhibitors (ARNI) 69.3% (IQR 66.4% to 72.1%), mineralocorticoid receptor antagonists (MRA) 29.2% (IQR 25.8% to 33.9%), sodium-glucose cotransporter 2 inhibitors (SGLT2I) 10.3% (IQR 7.7% to 12.8%), and ARNI 12.2% (IQR 8.6% to 15.3%). HRRs with the highest and lowest composite scores were often found in the same U.S. Census Regions. Conclusions: In conclusion, wide geographic disparities are present for GDMT prescribing to Veterans across HRRs. Veteran receipt of ARNI, SGLT2I, and MRA is low nationwide. Targeted approaches may be necessary to improve GDMT prescription for Veterans in lower performing HRRs.

BackgroundWith rising United States health care expenditure, estimating current spending for patients with heart failure (HF) informs the value of preventative health interventions.ObjectivesThe purpose of this study was to estimate current health care expenditure growth for patients with HF in the United States.MethodsThe authors pooled MEPS (Medical Expenditure Panel Survey) data from 2009-2018 to calculate total HF-related expenditure across clinical settings in the United States. A 2-part model adjusted for demographics, comorbidities, and year was used to estimate annual mean and incremental expenditures associated with HF.ResultsIn the United States, an average of $28,950 (2018 inflation-adjusted dollars) is spent per year for health care-related expenditure for individuals with HF compared with $5,727 for individuals without HF. After adjusting for demographics and comorbidities, a diagnosis of HF was associated with $3,594 in annual incremental expenditure compared with those without HF. HF-related expenditure increased from $26,864 annual per person in 2009-2010 to $32,955 in 2017-2018, representing a 23% rise over 10 years. In comparison, expenditure on myocardial infarction, type 2 diabetes mellitus, and cancer grew by 16%, 28%, and 16%, respectively. Most of the cost was related to hospitalization: $12,569 per year. Outpatient office-based care and prescription medications saw the greatest growth in cost over the period, 41% and 24%, respectively. Estimated incremental national expenditure for HF per year was $22.3 billion; total annual expenditure for adults with HF was $179.5 billion.ConclusionsHF is a costly condition for which expenditure is growing faster than that of other chronic conditions.

BACKGROUND: The Get With The Guidelines - Atrial Fibrillation (GWTG-AFIB) Registry uses achievement and quality measures to improve the care of patients with atrial fibrillation (AF). We sought to evaluate overall and site-level variation in attainment of these measures among sites participating in the GWTG-AFIB Registry. METHODS: From the GWTG-AFIB registry, we included patients with AF admitted between 1/3/2013 and 6/30/2019. We described patient-level attainment and variation in attainment across sites of 6 achievement measures with 1) defect-free scores (percent of patients with all eligible measures attained), and 2) composite opportunity scores (percent of all eligible patient measures attained). We also described attainment of 11 quality measures at the patient-level. RESULTS: Among 80,951 patients hospitalized for AF (age 70±13 years, 47.0% female; CHA2DS2-VASc 3.6±1.8) at 132 sites. Site-level defect-free scores ranged from 4.7% to 85.8% (25th, 50th, 75th percentile: 32.7%, 52.1%, 64.4%). Composite opportunity scores ranged from 39.4% to 97.5% (25th, 50th, 75th: 68.1%, 80.3%, 87.1%). Attainment was notably low for the following quality measures: 1) aldosterone antagonist prescription when ejection fraction ≤35% (29% of those eligible); and 2) avoidance of antiplatelet therapy with OAC in patients without coronary/peripheral artery disease (81% of those eligible). CONCLUSIONS: Despite high overall attainment of care measures across GWTG-AFIB registry sites, large site variation was present with meaningful opportunities to improve AF care beyond OAC prescription, including but not limited to prescription of aldosterone antagonists in those with AF and systolic dysfunction and avoidance of non-indicated adjunctive antiplatelet therapy.

The cost of heart failure care is high owing to the cost of hospitalization and chronic treatments. Heart failure treatments vary in their benefit and cost. The cost effectiveness of therapies can be determined by comparing the cost of treatment required to obtain a certain benefit, often defined as an increase in 1 year of life. This review was sponsored by the Heart Failure Society of America and describes the growing economic burden of heart failure for patients and the health care system in the United States. It also provides a summary of the cost effectiveness of drugs, devices, diagnostic tests, hospital care, and transitions of care for patients with heart failure. Many medications that are no longer under patent are inexpensive and highly cost-effective. These include angiotensin-converting enzyme inhibitors, beta-blockers and mineralocorticoid receptor antagonists. In contrast, more recently developed medications and devices, vary in cost effectiveness, and often have high out-of-pocket costs for patients.

Background Sacubitril/Valsartan has been highly efficacious in randomized trials of heart failure with reduced ejection fraction (HFrEF). However, the effectiveness of sacubitril/valsartan in older patients hospitalized for HFrEF in real-world US practice is unclear. Methods and Results This study included Medicare beneficiaries age ≥65 years who were hospitalized for HFrEF ≤40% in the Get With The Guidelines-Heart Failure registry between October 2015 and December 2018, and eligible for sacubitril/valsartan. Associations between discharge prescription of sacubitril/valsartan and clinical outcomes were assessed after inverse probability of treatment weighting and adjustment for other HFrEF medications. Overall, 1551 (10.9%) patients were discharged on sacubitril/valsartan. Of those not prescribed sacubitril/valsartan, 7857 (62.0%) were prescribed an angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker. Over 12-month follow-up, compared with a discharge prescription of angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker, sacubitril/valsartan was independently associated with lower all-cause mortality (adjusted hazard ratio [HR], 0.82; 95% CI, 0.72-0.94; P=0.004) but not all-cause hospitalization (adjusted HR, 0.97; 95% CI, 0.89-1.07; P=0.55) or heart failure hospitalization (adjusted HR, 1.04; 95% CI, 0.91-1.18; P=0.59). Patients prescribed sacubitril/valsartan versus those without a prescription had lower risk of all-cause mortality (adjusted HR, 0.69; 95% CI, 0.60-0.79; P

BackgroundFew contemporary data exist evaluating care patterns and outcomes in heart failure (HF) across the spectrum of kidney function.ObjectivesThis study sought to characterize differences in quality of care and outcomes in patients hospitalized for HF by degree of kidney dysfunction.MethodsGuideline-directed medical therapies were evaluated among patients hospitalized with HF at 418 sites in the GWTG-HF (Get With The Guidelines-Heart Failure) registry from 2014 to 2019 by discharge CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration)-derived estimated glomerular filtration rate (eGFR). We additionally evaluated the risk-adjusted association of admission eGFR with in-hospital mortality.ResultsAmong 365,494 hospitalizations (age 72 ± 15 years, left ventricular ejection fraction [EF]: 43 ± 17%), median discharge eGFR was 51 ml/min/1.73 m2 (interquartile range: 34 to 72 ml/min/1.73 m2), 234,332 (64%) had eGFR

ImportanceThe Centers for Medicare & Medicaid Services uses a new peer group-based payment system to compare hospital performance as part of its Hospital Readmissions Reduction Program, which classifies hospitals into quintiles based on their share of dual-eligible beneficiaries for Medicare and Medicaid. However, little is known about the association of a hospital's share of dual-eligible beneficiaries with the quality of care and outcomes for patients with heart failure (HF).ObjectiveTo evaluate the association between a hospital's proportion of patients with dual eligibility for Medicare and Medicaid and HF quality of care and outcomes.Design, setting, and participantsThis retrospective cohort study evaluated 436 196 patients hospitalized for HF using the Get With The Guidelines-Heart Failure registry from January 1, 2010, to December 31, 2017. The analysis included patients 65 years or older with available data on dual-eligibility status. Hospitals were divided into quintiles based on their share of dual-eligible patients. Quality and outcomes were analyzed using unadjusted and adjusted multivariable logistic regression models. Data analysis was performed from April 1, 2020, to January 1, 2021.Main outcomes and measuresThe primary outcome was 30-day all-cause readmission. The secondary outcomes included in-hospital mortality, 30-day HF readmissions, 30-day all-cause mortality, and HF process of care measures.ResultsA total of 436 196 hospitalized HF patients 65 years or older from 535 hospital sites were identified, with 258 995 hospitalized patients (median age, 81 years; interquartile range, 74-87 years) at 455 sites meeting the study criteria and included in the primary analysis. A total of 258 995 HF hospitalizations from 455 sites were included in the primary analysis of the study. Hospitals in the highest dual-eligibility quintile (quintile 5) tended to care for patients who were younger, were more likely to be female, belonged to racial minority groups, or were located in rural areas compared with quintile 1 sites. After multivariable adjustment, hospitals with the highest quintile of dual eligibility were associated with lower rates of key process measures, including evidence-based β-blocker prescription, measure of left ventricular function, and anticoagulation for atrial fibrillation or atrial flutter. Differences in clinical outcomes were seen with higher 30-day all-cause (adjusted odds ratio, 1.24; 95% CI, 1.14-1.35) and HF (adjusted odds ratio, 1.14; 95% CI, 1.03-1.27) readmissions in higher dual-eligible quintile 5 sites compared with quintile 1 sites. Risk-adjusted in-hospital and 30-day mortality did not significantly differ in quintile 1 vs quintile 5 hospitals.Conclusions and relevanceIn this cohort study, hospitals with a higher share of dual-eligible patients provided care with lower rates of some of the key HF quality of care process measures and with higher 30-day all-cause or HF readmissions compared with lower dual-eligibility quintile hospitals.

BackgroundPostdischarge mortality following hospitalization for heart failure with reduced ejection fraction (HFrEF) has remained high and unchanged over the past 2 decades, despite effective therapies for HFrEF. We aimed to explore whether these patterns could in part be explained by changes in longitudinal risk profile and HF severity over time.MethodsAmong patients hospitalized for HF in the GWTG-HF registry from January 2005 to December 2018 with available data, we evaluated GWTG-HF and ADHERE risk scores, observing in-hospital mortality per-year. The risk profiles and outcomes were described overall and by subgroups based on ejection fraction (EF), diabetes mellitus (DM), sex, and age.ResultsOverall, 335,735 patients were included (50% HFrEF, 46% DM, 48% female, mean age 74 years). In-hospital mortality increased by 2.0% per year from 2005 to 2018. There was no significant change in mean GWTG-HF risk score overall or when stratified by EF groups (P = 0.46 HFrEF, p = 0.26 HF mid-range EF [HFmrEF], and P = 0.72 HF preserved EF [HFpEF]), age, sex, or presence of DM. The observed/expected ratio based on the GWTG-HF risk score was 0.93 (0.91-0.96), 0.83 (0.77-0.90), 0.92 (0.89-95) for HFrEF, HFmrEF, and HFpEF, respectively. Similar findings were seen when risk was assessed using ADHERE risk score.ConclusionsThere were no significant changes in average risk profiles among hospitalized HF patients over the study duration. These data do not support the notion that worsening risk profile explains the lack of improved outcomes despite therapeutic advances, underscoring the importance of aggressive implementation of guideline-recommended therapies and investigation of novel treatments.

Background There are conflicting data regarding the benefit of primary prevention implantable cardioverter-defibrillators (ICDs) in patients with diabetes mellitus and heart failure (HF) with reduced ejection fraction. We aimed to assess the comparative effectiveness of ICD placement in patients with diabetes mellitus and HF with reduced ejection fraction. Methods and Results Data were obtained from the Get With the Guidelines-Health Failure registry, linked with claims from the Centers for Medicare & Medicaid Services. We used a Cox proportional hazards model censored at 5 years with propensity score matching. Of the 17 186 patients with HF with reduced ejection fraction from the Centers for Medicare & Medicaid Services claims database (6540 with diabetes mellitus; 38%), 1677 (646 with diabetes mellitus; 39%) received an ICD during their index HF hospitalization or were prescribed an ICD at discharge. Patients with diabetes mellitus and an ICD (n=646), as compared with those without an ICD (n=1031), were more likely to be younger (74 versus 78 years of age) and have coronary artery disease (68% versus 60%). After propensity matching, ICD use among patients with diabetes mellitus, as compared with those without an ICD, was associated with a reduced risk of all-cause mortality at 5 years after HF discharge (54% versus 59%; multivariable hazard ratio, 0.73; 95% CI, 0.64-0.82; P

BACKGROUND: Current guidelines recommend evaluation for underlying heart disease and reversible conditions for patients with new-onset heart failure (HF). There are limited data on contemporary testing for coronary artery disease (CAD) in patients with new-onset HF. METHODS: We performed an observational cohort study using the Get With The Guidelines-Heart Failure registry linked to Medicare claims. All patients were aged ≥65 and hospitalized for new-onset HF from 2009 to 2015. We collected left ventricular ejection fraction (LVEF), prior HF history, and in-hospital CAD testing from the registry, as well as testing for CAD using claims from 90 days before to 90 days after index HF hospitalization. RESULTS: Among 17 185 patients with new-onset HF, 6672 (39%) received testing for CAD, including 3997 (23%) during the index hospitalization. Testing for CAD differed by LVEF: 53% in HF with reduced EF (LVEF ≤40%), 42% in HF with borderline EF (LVEF, 41%-49%), and 31% in HF with preserved EF (LVEF ≥50%). After multivariable adjustment, patients who received testing for CAD, compared with those who did not, were younger and more likely to be male, have a smoking history, have hyperlipidemia, and have HF with reduced ejection fraction or HF with borderline ejection fraction (all P

BackgroundIn PIONEER-HF (Comparison of Sacubitril/Valsartan Versus Enalapril on Effect on NT-pro BNP in Patients Stabilized From an Acute Heart Failure Episode), the in-hospital initiation of sacubitril/valsartan in patients hospitalized for acute decompensated heart failure (ADHF) was well-tolerated and led to improved outcomes. We aim to determine the representativeness of the PIONEER-HF trial among patients hospitalized for ADHF using real-world data.MethodsThe study population was derived from all patients discharged alive for ADHF in the Get With The Guidelines-HF registry from 2006 to 2018 with HF with reduced ejection fraction (HFrEF; all HFrEF with ADHF). We then determined the proportion of patients meeting PIONEER-HF eligibility criteria (PIONEER-HF eligible) and those meeting a set of limited eligibility criteria (actionable cohort). Rates of HF readmissions and all-cause mortality were then compared between the all HFrEF with ADHF, PIONEER-HF eligible, and actionable cohorts using linked Medicare claims data.ResultsA total of 99 767 patients with HFrEF in Get With The Guidelines-HF were hospitalized for ADHF. PIONEER-HF inclusion criteria were met by 71 633 (71.8%) patients, and both inclusion and exclusion criteria were met by 20 704 (20.8%) patients. Further, 68 739 (68.9%) patients met the criteria for the actionable cohort. Among the Centers for Medicare and Medicaid-linked patients, the HF rehospitalization rate at 1 year was 35.1% (95% CI, 34.5-35.8) for all HFrEF with ADHF patients, 32.6% (95% CI, 31.3-33.9) for the PIONEER-HF eligible cohort, and 33.1% (95% CI, 32.3-33.9) for the actionable cohort. The 1-year all-cause mortality was 36.7% (95% CI, 36.1-7.4) for all HFrEF with ADHF patients, 31.6% (95% CI, 30.3-32.9) for the PIONEER-HF eligible cohort, and 32.2% (95% CI, 31.4-33.0) for the actionable cohort.ConclusionsPatient characteristics and clinical outcomes for patients eligible for PIONEER-HF only modestly differ when compared with those encountered in routine practice, suggesting that the in-hospital initiation of sacubitril/valsartan should be routinely considered for patients with HFrEF hospitalized for ADHF.

AimsSodium-glucose co-transporter (SGLT)-2 inhibitors have been shown to reduce the risk of cardiovascular death and heart failure (HF) hospitalization in patients with type 2 diabetes mellitus (DM) and high cardiovascular risk in two large clinical outcome trials: empagliflozin in EMPA-REG OUTCOME and canagliflozin in CANVAS. The scope of eligibility for SGLT-2 inhibitors (empagliflozin and canagliflozin) among patients with type 2 DM and HF, based on clinical trial criteria and current US Food and Drug Administration (FDA) labelling criteria, remains unknown.Methods and resultsUsing data from the US Get With The Guidelines (GWTG)-Heart Failure registry, we evaluated the proportion of patients with DM and HF eligible for SGLT-2 inhibitor therapy based on the clinical trial criteria and the US FDA labelling criteria. The GWTG-HF registry is a quality improvement registry of patients admitted in hospital with HF in the USA. We included GWTG-HF registry participants meeting eligibility criteria hospitalized between August 2014 and 30 June 2017 from sites fully participating in the registry. The initial inclusion time point reflects when both drugs had FDA approval. Among the 139 317 patients (out of 407 317) with DM hospitalized with HF (in 460 hospitals; 2014 to 2017), the median age was 71 years, 47% (n = 65 685) were female, and 43% (n = 59 973) had HF with reduced ejection fraction. Overall, 43% (n = 59 943) were eligible for the EMPA-REG OUTCOME trial, 45% (n = 62 818) were eligible for the CANVAS trial, and 34% (n = 47 747) of patients were eligible for either SGLT-2 inhibitors based on the FDA labelling criteria. Among the FDA-eligible patients, 91.5% (n = 43 708) were eligible for either the EMPA-REG OUTCOME trial or the CANVAS trial. Patients who were FDA eligible, compared with those who were not, were younger (70.0 vs. 72.0 years of age), more likely to be male (57.7 vs. 50.3%), and had less burden of co-morbidities.ConclusionsThe majority of patients with DM who are hospitalized with HF are not eligible for SGLT-2 inhibitor therapies. Ongoing studies evaluating the safety and efficacy of SGLT-2 inhibitors among patients with HF may potentially broaden the population that may benefit from these therapies.

Background Limited data exist to guide treatment for patients with heart failure with preserved ejection fraction and atrial fibrillation, including the important decision regarding rate versus rhythm control. Methods and Results We analyzed the Get With The Guidelines-Heart Failure (GWTG-HF) registry linked to Medicare claims data from 2008 to 2014 to describe current treatments for rate versus rhythm control and subsequent outcomes in patients with heart failure with preserved ejection fraction and atrial fibrillation using inverse probability weighted analysis. Rhythm control was defined as use of an antiarrhythmic medication, cardioversion, or AF ablation or surgery. Rate control was defined as use of any combination of β-blocker, calcium channel blocker, and digoxin without evidence of rhythm control. Among 15 682 fee-for-service Medicare patients, at the time of discharge, 1857 were treated with rhythm control and 13 825 with rate control, with minimal differences in baseline characteristics between groups. There was higher all-cause death at 1 year in the rate control compared with the rhythm control group (37.5% and 30.8%, respectively, P

Objectives:The relationship between prior glycemic status and outcomes in intracerebral hemorrhage (ICH) is not established. We hypothesized that higher hemoglobin (Hb) A1c is associated with worse outcomes in ICH. Patients and methods:Using the GWTG-Stroke registry, data on patients with ICH between April 1, 2003 and September 30, 2015 were harvested. Patients were divided into four ordinal groups based on HbA1c values of 8.0%. Outcomes (mortality, modified Rankin Scale (mRS), home discharge and independent ambulatory status) were analyzed for patients overall and separately for patients with or without history of diabetes using multivariable regression models. Results:Among 75,455 patients with ICH (with available HbA1c data), patients with lower HbA1c (8.0%), (15.0%; 205/1364) were associated with higher in-hospital mortality. Lower HbA1c was also associated with higher mRS, less chance of going home, and lower likelihood of having independent ambulatory status in patients with prior history of diabetes. Conclusions:Among patients with no reported history of diabetes, both very low and very high HbA1c were directly associated with higher in-hospital mortality. Only very low HbA1c was associated with higher mortality in known diabetic patients. Further studies are needed to better define the relationship between HbA1c and outcomes, for it may have important implications for care of ICH patients.

BackgroundDiabetes mellitus is an increasingly prevalent condition among heart failure (HF) patients. The long-term morbidity and mortality among patients with and without diabetes with HF with reduced (HFrEF), borderline (HFbEF), and preserved ejection fraction (HFpEF) are not well described.MethodsUsing the Get With The Guidelines (GWTG)-HF Registry linked to Centers for Medicare & Medicaid Services claims data, we evaluated differences between HF patients with and without diabetes. Adjusted Cox proportional-hazard models controlling for patient and hospital characteristics were used to evaluate mortality and readmission outcomes.ResultsA cohort of 86,659 HF patients aged ≥65 years was followed for 3 years from discharge. Unadjusted all-cause mortality was between 4.4% and 5.5% and all-cause hospitalization was between 19.4% and 22.6% for all groups at 30 days. For all-cause mortality at 3 years from hospital discharge, diabetes was associated with an adjusted hazard ratio of 1.27 (95% CI 1.07-1.49, P = .0051) for HFrEF, 0.95 (95% CI 0.55-1.65, P = .8536) for HFbEF, 1.02 (95% CI 0.87-1.19, P = .8551) for HFpEF. For all-cause readmission, diabetes was associated with an adjusted hazard ratio of 1.06 (95% CI 0.87-1.29, P = .5585) for HFrEF, 1.48 (95% CI 1.15-1.90, P = .0023) for HFbEF, and 1.06 (95% CI 0.91-1.22, P = .4747) for HFpEF.ConclusionsHFrEF and HFbEF patients with diabetes are at increased risk for mortality and rehospitalization after hospitalization for HF, independent of other patient and hospital characteristics. Among HFpEF patients, diabetes does not appear to be independently associated with significant additional risks.

Background The angiotensin-receptor/neprilysin inhibitor ( ARNI ) sacubitril/valsartan reduces hospitalization and mortality for patients with heart failure with reduced ejection fraction. However, adoption of ARNI into clinical practice has been slow. Factors influencing use of ARNI have not been fully elucidated. Using data from the Get With The Guidelines-Heart Failure registry, Hospital Compare, Dartmouth Atlas, and the American Hospital Association Survey, we sought to identify hospital characteristics associated with patient-level receipt of an ARNI prescription. Methods and Results We analyzed patients with heart failure with reduced ejection fraction who were eligible for ARNI prescription (ejection fraction≤40%, no contraindications) and hospitalized from October 1, 2015 through December 31, 2016. We used logistic regression to estimate the associations between hospital characteristics and patient ARNI prescription at hospital discharge, accounting for clustering of patients within hospitals using generalized estimating equation methods and adjusting for patient-level covariates. Of 16 674 eligible hospitalizations from 210 hospitals, 1020 patients (6.1%) were prescribed ARNI at discharge. The median hospital-level proportion of patients prescribed ARNI was 3.3% (Q1, Q3: 0%, 12.6%). After adjustment for patient-level covariates, for-profit hospitals had significantly higher odds of ARNI prescription compared with not-for-profit hospitals (odds ratio, 2.53; 95% CI , 1.05-6.10; P=0.04), and hospitals located in the Western United States had lower odds of ARNI prescription compared with those in the Northeast (odds ratio, 0.33; 95% CI , 0.13-0.84; P=0.02). Conclusions Relatively few hospital characteristics were associated with ARNI prescription at hospital discharge, in contrast to what has been observed in early adoption in other disease areas. Additional evaluation of barriers to implementing new evidence into heart failure practice is needed.

AimsReadmission rates for patients with heart failure have consistently remained high over the past two decades. As more electronic data, computing power, and newer statistical techniques become available, data-driven care could be achieved by creating predictive models for adverse outcomes such as readmissions. We therefore aimed to review models for predicting risk of readmission for patients admitted for heart failure. We also aimed to analyze and possibly group the predictors used across the models.MethodsMajor electronic databases were searched to identify studies that examined correlation between readmission for heart failure and risk factors using multivariate models. We rigorously followed the review process using PRISMA methodology and other established criteria for quality assessment of the studies.ResultsWe did a detailed review of 334 papers and found 25 multivariate predictive models built using data from either health system or trials. A majority of models was built using multiple logistic regression followed by Cox proportional hazards regression. Some newer studies ventured into non-parametric and machine learning methods. Overall predictive accuracy with C-statistics ranged from 0.59 to 0.84. We examined significant predictors across the studies using clinical, administrative, and psychosocial groups.ConclusionsComplex disease management and correspondingly increasing costs for heart failure are driving innovations in building risk prediction models for readmission. Large volumes of diverse electronic data and new statistical methods have improved the predictive power of the models over the past two decades. More work is needed for calibration, external validation, and deployment of such models for clinical use.

IntroductionHeart failure (HF) is the leading cause of hospital readmission. Medicare home health services provide intermittent skilled nursing care to homebound Medicare beneficiaries. We examined whether discharge home health referral is associated with a lower risk of 30-day all-cause readmission in HF.Material and methodsOf the 8049 Medicare beneficiaries hospitalized for acute HF and discharged alive from 106 Alabama hospitals, 6406 (76%) patients were not admitted from nursing homes and were discharged home without discharge hospice referrals. Of these, 1369 (21%) received a discharge home health referral. Using propensity scores for home health referral, we assembled a matched cohort of 1253 pairs of patients receiving and not receiving home health referrals, balanced on 33 baseline characteristics.ResultsThe 2506 matched patients had a mean age of 78 years, 61% were women, and 27% were African American. Thirty-day all-cause readmission occurred in 28% and 19% of matched patients receiving and not receiving home health referrals, respectively (hazard ratio (HR) = 1.52; 95% confidence interval (CI): 1.29-1.80; p < 0.001). Home health referral was also associated with a higher risk of 30-day all-cause mortality (HR = 2.32; 95% CI: 1.58-3.41; p < 0.001) but not with 30-day HF readmission (HR = 1.28; 95% CI: 0.99-1.64; p = 0.056). HRs (95% CIs) for 1-year all-cause readmission, all-cause mortality, and HF readmission are 1.24 (1.13-1.36; p < 0.001), 1.37 (1.20-1.57; p < 0.001) and 1.09 (0.95-1.24; p = 0.216), respectively.ConclusionsHospitalized HF patients who received discharge home health services referral had a higher risk of 30-day and 1-year all-cause readmission and all-cause mortality, but not of HF readmission.

Aims:There is a paucity of data on the influence of diabetes on long-term outcomes after ischaemic stroke (IS). We assessed whether outcomes after IS differ between patients with and without diabetes. Methods and results:Patients aged ≥65 years (n = 409 060) in Get With The Guidelines-Stroke (nationwide registry of stroke patients from 1690 sites in the USA) were followed for 3 years post-discharge. The outcomes of interest were mortality, cardiovascular and non-cardiovascular hospitalizations, heart failure (HF), and recurrence of IS/transient ischaemic attack (TIA). Patients with diabetes (29.6%) were younger and had more comorbidities. At 3 years post-discharge after IS, diabetes was associated with higher risks of adverse outcomes: all-cause mortality [cumulative incidence 46.0% vs. 44.2%, absolute difference (AD) 1.8%; adjusted hazard ratio (aHR) 1.24, 95% confidence interval 1.23-1.25], all-cause readmission (71.3% vs. 63.7%, AD 7.6%; aHR 1.22, 1.21-1.23), composite of mortality and all-cause readmission (84.1% vs. 79.3%, AD 4.8%; aHR 1.21, 1.20-1.22), composite of mortality and cardiovascular readmission (69.5% vs. 64.3%, AD 5.2%; aHR 1.19, 1.18-1.20), IS/TIA readmission (15.9% vs. 13.3%, AD 2.6%; aHR 1.18, 1.16-1.20), HF readmission (10.3% vs. 6.4%, AD 3.9%; aHR 1.60, 1.56-1.64), non-cardiovascular readmission (58.3% vs. 50.3%, AD 8.0%; aHR 1.28, 1.26-1.29), and non-IS/TIA readmission (67.6% vs. 59.7%, AD 7.9%; aHR 1.23, 1.22-1.25). Accounting for the initial severity of stroke using the National Institute of Health Stroke Scale as well as using propensity score matching method as a sensitivity analysis, did not modify the results. Conclusion:Among older IS patients diabetes was associated with increased risks of death, cardiovascular and non-cardiovascular hospitalizations, HF, and IS/TIA recurrence.

BackgroundHeart failure (HF) is the leading cause of morbidity and mortality in the United States. Despite advancement in the management of HF, outcomes remain suboptimal, particularly among the uninsured. In 2014, the Affordable Care Act expanded Medicaid eligibility, and millions of low-income adults gained insurance. Little is known about Medicaid expansion's effect on inpatient HF care.Methods and resultsWe used the American Heart Association's Get With The Guidelines-Heart Failure registry to assess changes in inpatient care quality and outcomes among low-income patients (

BackgroundSurveys of patients with cardiovascular disease have suggested that "home-time"-being alive and out of any health care institution-is a prioritized outcome. This novel measure has not been studied among patients with heart failure (HF).ObjectivesThis study sought to characterize home-time following hospitalization for HF and assess its relationship with patient characteristics and traditionally reported clinical outcomes.MethodsUsing GWTG-HF (Get With The Guidelines-Heart Failure) registry data, patients discharged alive from an HF hospitalization between 2011 and 2014 and ≥65 years of age were identified. Using Medicare claims, post-discharge home-time over 30-day and 1-year follow-up was calculated for each patient as the number of days alive and spent outside of a hospital, skilled nursing facility (SNF), or rehabilitation facility.ResultsAmong 59,736 patients, 57,992 (97.1%) and 42,153 (70.6%) had complete follow-up for home-time calculation through 30 days and 1 year, respectively. The mean home-time was 21.6 ± 11.7 days at 30 days and 243.9 ± 137.6 days at 1 year. Contributions to reduced home-time varied by follow-up period, with days spent in SNF being the largest contributor though 30 days and death being the largest contributor through 1 year. Over 1 year, 2,044 (4.8%) patients had no home-time following index hospitalization discharge, whereas 8,194 (19.4%) had 365 days of home-time. In regression models, several conditions were associated with substantially reduced home-time, including chronic obstructive pulmonary disease, renal insufficiency, and dementia. Through 1 year, home-time was highly correlated with time-to-event endpoints of death (tau = 0.72) and the composite of death or HF readmission (tau = 0.59).ConclusionsHome-time, which can be readily calculated from administrative claims data, is substantially reduced for many patients following hospitalization for HF and is highly correlated with traditional time-to-event mortality and hospitalization outcomes. Home-time represents a novel, easily measured, patient-centered endpoint that may reflect effectiveness of interventions in future HF studies.

ObjectivesThe purpose of this study was to analyze cumulative Medicare expenditures at index admission and after discharge by race or ethnicity.BackgroundHeart failure with preserved ejection fraction (HFpEF) is a growing proportion of heart failure (HF) admissions. Research on health care expenditures for patients with HFpEF is limited.MethodsRecords of patients discharged from the Get With The Guidelines-Heart Failure registry between 2006 and 2014 were linked to Medicare data. The primary outcome was unadjusted payments for acute care services. Comparisons between race/ethnic groups were made using generalized linear mixed models. Cost ratios were reported by race/ethnicity, and adjustments were made sequentially for patient characteristics, hospital factors, and regional socioeconomic status.ResultsMedian Medicare costs for index hospitalizations were $7,241 for the entire cohort, $7,049 for whites, $8,269 for blacks, $8,808 for Hispanics, $8,477 for Asians, and $8,963 for other races. Median costs at 30 days for readmitted patients were $9,803 and $17,456 for the entire cohort at 1-year. No significant differences were seen in index admission cost ratios by race/ethnicity. At 30 days among readmitted patients, costs were 9% higher (95% confidence interval [CI]: 1% to 17%; p = 0.020) for blacks in the fully adjusted model than whites. At 1 year, costs were 14% higher (95% CI: 9% to 18%; p < 0.001) for blacks, 7% higher (95% CI: 0% to 14%; p = 0.041) for Hispanics, and 24% higher (95% CI: 8% to 42%; p = 0.003) for patients of other races. No significant differences between white and Asian expenditures were noted.ConclusionsMinority patients with HFpEF have greater acute care service costs. Further research of improving care delivery is needed to reduce acute care use for vulnerable populations.