Search

Supplemental Digital Content is available in the text.

Supplemental Digital Content is available in the text.

Supplemental Digital Content is available in the text.

Supplemental Digital Content is available in the text.

Supplemental Digital Content is available in the text.

Supplemental Digital Content is available in the text.

Supplemental Digital Content is available in the text.

Supplemental Digital Content is available in the text.

Supplemental Digital Content is available in the text.

Introduction:Prior studies demonstrate that poor CRF in early adulthood is associated with adverse cardiac structure and function in midlife. The purpose of this study is to examine if higher early adulthood CRF and retention of CRF through midlife are associated with lower subsequent risk of subclinical or clinical HF.Methods:CARDIA participants with available data on CRF at baseline (Year [Y] 0: 1985-86), follow-up (Y7 or Y20), and HF staging data by Y30 were included. CRF was estimated using treadmill duration from a maximal, symptom-limited graded exercise test via modified Balke protocol. An adjusted linear mixed model was used to estimate treadmill duration when CRF assessment was missing at Y7 or 20. HF stages were defined using AHA HF staging criteria, including Stage 0 (no HF risk factors). Clinical HF was adjudicated by committee. Adjusted multinomial models tested associations between Y0 CRF and percent CRF retained through Y20 with HF stages at Y30, with Stage 0 as the reference. Interactions by the four race-sex groups were examined.Results:Of 2,565 individuals (25.1±3.5 y, 43% Black, 55% female), 30% (n=778), 37% (n=952), 32% (n=813), and 1% (n=32) were classified as Stages 0, A, B, or C/D by Y30 exam, respectively. Compared with Stage 0, every 1-minute increment higher CRF in early-adulthood was associated with a lower adjusted odds ratio of HF [Stage A: 0.72 (95% CI 0.68, 0.76), Stage B: 0.80 (95% CI 0.75, 0.84), Stage C/D 0.86 (95% CI 0.71, 1.04)]. Compared with Stage 0, every 1-standard deviation of % CRF retained at Y20 (midlife) was also associated with a lower odds of Stage A, B, and C/D HF at Y30 (Figure). A race-sex interaction was not observed (p-interaction 0.42).Conclusion:Higher early adulthood CRF, and greater retention of CRF through midlife, were associated with lower risk of developing subclinical or clinical HF. Strategies to maintain optimal CRF across the young adulthood to midlife transition may be important in prevention of HF.

Objective:To evaluate the association between non-alcoholic fatty liver disease (NAFLD), heart failure (HF), and all-cause mortality.Background:Both NAFLD and HF are increasing in prevalence due to shared risk factors.Methods:We used data from the National Health and Nutrition Examination Survey (NHANES) 2005-2018 to identify non-pregnant individuals aged ≥20 years with HF and NAFLD and linked with the cause of death data from the National Center for Health Statistics. The associations between NAFLD, HF, and all-cause mortality were assessed using logistic regression and Cox proportional hazard modeling as appropriate.Results:There were 82,358,893 weighted eligible participants of whom 3,833,667 (4.7%) had NAFLD. The mean (SE) age was 51.5 (0.35) years, 45.1% women, 63.0% Non-Hispanic White and 11.8% Non-Hispanic Black. Cardiovascular comorbidities were more common in participants with NAFLD; they were more likely to have hypertension (81.7% vs 53.5%), diabetes (65.1% vs 17.1%), stroke (7.3% vs 4.1%), coronary artery disease (14.9% vs 8.4%), or HF (10.5% v s 3.5%) compared with participants without NAFLD. In multivariate logistic regression models adjusting for age, race/ethnicity and sex, participants with NAFLD were 3.5 times more likely to have HF [aOR, 95% CI: 3.47 (1.98-6.06)]. Older age, male sex, presence of diabetes and coronary artery disease were associated with higher odds of HF in participants with established NAFLD. At the end of the follow-up period, participants with NAFLD had higher all-cause mortality compared with participants without NAFLD [HR(95% CI): 1.93 (1.24-2.99), p<0.001].Conclusion:In this analysis of US adults, ambulatory participants with NAFLD were ~3.5 times more likely to have HF, and twice as likely to experience mortality compared with participants without NAFLD. Further studies are needed to identify the possible linkage between NAFLD and HF beyond the shared risk factor pathogenesis.

Introduction:Canagliflozin (CAN) vs. placebo (PBO) reduced the risk of hospitalization for heart failure (HHF) in type 2 diabetes. Whether this benefit is uniform across diabetes-specific HF risk scores (WATCH-DM and TRS-HFDM) is not known.Methods:Using data from the pooled CANVAS and CANVAS-R trials, we stratified participants without prevalent HF by the integer WATCH-DM score derived quintiles (low [≤14] = quintiles 1-2, intermediate [15-19] = quintiles 3-4, high [≥20] = quintile 5) and by the TRS-HFDMscore (low [0-1], intermediate [2], high [3-6]). Discrimination and calibration were assessed by Harrell’s C-index and Hosmer-Lemeshow test, respectively. Cox regression models evaluated the effect of CAN on risk of HHF across risk score categories.Results:Among participants without prevalent HF (n = 8,691), CAN vs. PBO reduced the risk of HHF (HR 0.80, 95% CI 0.62-1.03). The WATCH-DM score demonstrated a C-index of 0.70 (95% CI, 0.66-0.73) and no evidence of miscalibration (χ2< 20). CAN consistently reduced risk of HHF across WATCH-DM strata (P-intxn = 0.55) with the greatest absolute risk reduction and lowest NNT observed in the highest vs. lowest risk cohort (ARR 4.6% vs. 0.3% and NNT 22 vs. 333) (Fig. A). Comparatively, the TRS-HFDMdemonstrated a C-index of 0.67 (95% CI, 0.63-0.71) and no evidence of miscalibration (χ2< 20). Similar to WATCH-DM, patients in the highest TRS-HFDMrisk group derived the greatest absolute risk reduction and lowest NNT (ARR 3.1% vs. -0.3%% and NNT 32 vs. -333) with no differences across strata (P-intxn = 0.17) (Fig. B).Conclusions:Both the WATCH-DM and TRS-HFDMcan accurately stratify HHF risk in patients with type 2 diabetes and free of HF. Greater absolute risk reductions with CAN vs PBO were observed with higher risk scores.

Introduction:Frailty is common in patients with heart failure with reduced ejection fraction (HFrEF) and is independently associated with mortality. Implantable cardiac defibrillator (ICD) therapy is recommended to reduce mortality risk in patients with HFrEF. Whether baseline frailty modifies the efficacy of ICD therapy in HFrEF is not known.Methods:Stable outpatients with HFrEF randomized to ICD vs. placebo in the SCD-HeFT trial were included. Baseline frailty was estimated using Rockwood’s Frailty Index (FI) by dividing the number of deficits present by the number of variables considered (n=37). Participants were categorized into tertiles of FI. Multivariable adjusted Cox proportional hazard models with multiplicative interaction terms (frailty*treatment arm) were constructed to evaluate whether frailty modified the treatment effect of ICD therapy on the primary outcome all-cause mortality and secondary outcomes of cardiovascular (CV) mortality and sudden cardiac death (SCD).Results:Among 1,673 participants (age: 59±12 y, 23% women), the median [IQR] FI ranged from 0.19 [0.14-0.23] in tertile 1 (lower frailty burden) to 0.51 [0.47-0.56] in tertile 3 (higher frailty burden). Baseline frailty significantly modified the treatment effect of ICD therapy (P-interaction: 0.03) (Fig. A). Specifically, ICD therapy was associated with a lower risk of all-cause mortality in tertile 1 [HR (95% CI) = 0.55 (0.37-0.80)] but not in tertile 3 participants [HR (95% CI) = 0.90 (0.67-1.22)] (Fig. B). Among secondary outcomes, frailty status modified the association of both CV mortality and SCD (P-interaction = 0.007 and 0.04, respectively). Similar results were observed in landmark analyses at 12 months.Conclusions:Among patients with chronic stable HFrEF, baseline frailty modified the treatment effect of ICD therapy with a greater reduction in the risk of CV mortality and SCD in patients with a lower burden of frailty.

Background:Intentional weight loss with bariatric surgery is associated with better outcomes in younger patients with prevalent HF. However, temporal trends in use of bariatric surgery and anti-obesity medications (AOM) among older patients with new onset HF and obesity, and their effect on CV outcomes are not well studied.Methods:Medicare patients with obesity and new onset HF from 2013 to 2019 were identified using the 100% inpatient files. Patients who underwent bariatric surgery were matched to controls in a 1:2 ratio (matched on age, sex, race, BMI, and HF diagnosis year, and comorbidities). In a random 5% sample with available Part D data, HF patients with obesity who were prescribed AOM (Semaglutide, liraglutide, naltrexone or orlistat) were identified and matched to HF controls as above. Cox models were used to evaluate the association of weight loss therapies (modeled as a time-varying dependent variable) and risk of mortality, atrial fibrillation (AF), and HF readmission rate.Results:Overall, 1.5% (2684 of 174,196) patients with new onset HF and BMI ≥35 underwent bariatric surgery (46% men, age 55 y and BMI 52 Kg/m2). Bariatric surgery use increased from 0.3% in 2013 to 1.4% in 2019 (P <0.01). In propensity-matched analyses (surgery N=2144 vs. control N=3920, f/u of 4.2 y), bariatric surgery following incident HF was associated with a significantly lower risk of mortality and new-onset AF (Figure), and a lower rate of HF readmissions (pre- vs. post-surgery rate: 0.9 vs. 0.3/100 person-days). In the subset with Part D data (N=36603), use of AOM was low (3.7%). In propensity-matched analysis, (AOM N=611 vs. controls N=891, f/u of 1.8 y), use of AOM were associated with 30% lower risk of mortality and 35% lower risk of AF compared with controls.Conclusions:Bariatric surgery and AOM are associated with favorable CV outcomes among HF patients with obesity. However, their utilization remains extremely low highlighting an important gap in care of HF patients with obesity.

Introduction:With increasing disease recognition and widespread availability of genetic testing, it is important to characterize the clinical outcomes and prognosis among familial dilated cardiomyopathy (DCM) patients with stage D heart failure requiring a mechanical circulatory support device (MCSD). INTERMACS (INTEragency Registry for Mechanical Assisted Circulatory Devices) was examined to assess the clinical characteristics and outcomes of familial DCM patients who received an MCSD.Methods:DCM patients who received an MCSD between June 2005-December 2017 were classified according to their etiology. The primary outcome was death (with heart transplant as a competing risk) and the secondary outcome was heart transplant (with death as a competing risk). Multivariable-adjusted Cox regression analyses were used to assess the risk of study outcomes across DCM etiologies.Results:Among 19,928 DCM patients, 8,622 (43.3%), 7,091 (35.6%), 568 (2.9%), and 3,647 (18.3%) had ischemic DCM, idiopathic DCM, familial DCM, and DCM due to other causes respectively. Familial DCM patients had the lowest median age at implantation [46 (34, 56) years] compared with other DCM etiologies. Bridge to transplant was the most common device strategy (78.4%) in the familial DCM group (45.6% were listed and an additional 32.8% were eligible for a heart transplant). Familial DCM patients had the lowest adverse events of bleeding, device thrombosis, infection, and respiratory failure post-MCSD implantation. Over a median follow-up of 1.0 (0.4, 2.0) years, familial DCM patients had the lowest risk of death [HRadj: 0.68 (95% CI: 0.55-0.83)] and the highest likelihood of heart transplantation [HRadj: 1.47 (95% CI: 1.28-1.69)] compared with the other DCM groups.Conclusions:Among DCM patients receiving MCSDs, familial DCM patients had the lowest adverse events, the lowest risk of death, and the highest likelihood of heart transplantation, compared with other DCM etiologies.

Introduction:Although heart failure (HF) guidelines emphasized dietary sodium restriction, the recommendation was based on limited evidence. We analyzed the impact of dietary sodium restriction on HF outcomes and quality of life (QoL) by systematically reviewing the available literature to-date.Methods:MEDLINE and SCOPUS were queried from inception till April 2022 for randomized controlled trials (RCTs) and observational studies with sodium restriction (≤1500-3000mg) as an intervention/comparator and assessing its impact (or association) on HF outcomes. Data about HF-related hospitalizations, all-cause mortality and QoL (via the Kansas City Cardiomyopathy Questionnaire) was extracted, pooled and analyzed. Forest plots were created based on random effects model.Results:Twelve studies (n= 4637 patients) were included in our analysis with a median follow-up time of 6 months. The pooled analysis demonstrated no difference in HF hospitalizations between the sodium-restricted and unrestricted groups (OR = 1.30 [0.81-2.10] P<0.28) (Figure 1a). However, a significantly higher risk of all-cause mortality was observed associated with sodium-restriction (OR = 1.68, 95% CI: 1.26-2.24, P< 0.0004) (Figure 1b). Dietary sodium restriction was not associated with QoL (mean difference = 0.14, 95% CI: -0.07-0.35, P< 0.18). (Figure 1c).Conclusions:Our observations suggest that sodium restriction in patients with HF may not improve QoL or reduce hospitalizations, but is associated with increased risk of mortality.

Introduction:Optimal guideline-directed medical therapies (GDMT) improves clinical outcomes among patients with new-onset HFrEF. Limited data exist on achievement of optimal GDMT in the first 12 months among newly diagnosed patients with HFrEF.Methods:2016-2020 OPTUM Claims Database, which includes privately insured and Medicare patients covered through the United Healthcare insurance, was used. Patients with new-onset HF were identified using validated ICD-10 codes and a 12-month look back to exclude prevalent HF. HFrEF patients were identified based on claims with ICD-10 codes of I50.2 and I50.4 within 6 months of HF diagnosis. Rates of optimal GDMT (≥50% target dose of ACEI or ARB or any dose of ARNI, ≥50% dose of beta-blocker, and any MRA) within 12 months of the incident HF diagnosis were compared overall and across race- and sex- groups. Adjusted Cox-proportional hazards models were used to evaluate the association of different patient-level factors with time to optimal GDMT during 12-month follow-up.Results:The study included 118963 patients with new-onset HFrEF (Age: 72 years, 15.8% Black, 57.4% Men). Only 8.3% achieved optimal GDMT during the 12 months after incident HF diagnosis. The optimal GDMT use within 12-months of HF diagnosis was low across the race-ethnic and gender groups (Figure 1A/1B). In adjusted Cox models, younger age, Black race, male sex, prevalent HF risk factors including hypertension, private (vs. Medicare insurance), and interval hospitalizations during the follow-up period were each associated with increased probability of achieving optimal GDMT (Figure 1C). In contrast, prevalent COPD, stroke/TIA, and polypharmacy were associated with a lower probability of achieving optimal GDMT.Conclusions:Utilization of optimal GDMT among patients with HFrEF is very low in the first 12 months after diagnosis. These findings highlight the need for aggressive implementation strategies to optimize GDMT utilization after new HF diagnosis.

Introduction:Prediabetes (preDM) is a risk factor for diabetes mellitus (DM) and both are associated with elevated risk of cardiovascular disease (CVD). However, the association of transitions in glycemic status with cardiovascular disease (CVD) is not well established.Methods:The present study included participants with hypertension enrolled in the Systolic Blood Pressure Intervention Trial (SPRINT) without DM at baseline. Study participants had available fasting plasma glucose (FPG) at baseline and 2-year follow-up and no primary outcome CVD event (myocardial infarction, other acute coronary syndrome, stroke, heart failure, or cardiovascular death) prior to 2 years. Euglycemia, preDM, and DM status were defined based on FPG, self-reported history, or use of glucose-lowering medication. Participants were stratified by glycemic status at baseline and 2-year follow up. The association of changes in glycemic status with CVD risk were assessed using adjusted Cox models.Results:The present study included 4,708 participants (33.6% women, 35.1% Black, 41.4% preDM). Among 2,760 participants with euglycemia at baseline, 716 (25.9%) developed preDM or DM over 2-year follow-up. Most participants with baseline preDM continued to have preDM or progressed to DM (71.3%). After the 2-year visit, 151 participants (3.2%) had a CVD event. Participants with persistent euglycemia had fewer CVD events (2.6%) compared with those with incident preDM or DM on follow-up (4.5%) (Figure 1A). In adjusted analysis, among participants with baseline euglycemia, those who developed prediabetes or diabetes had 70% higher risk of a CVD event during follow-up compared with those with persistent euglycemia (HR [95% CI], 1.70 [1.09-2.64]) (Figure 1B).Conclusions:In adults with hypertension, worsening glycemic status from euglycemia to preDM or DM was associated with higher risk for CVD. Prevention of dysglycemia may be an important target to prevent CVD in hypertension.

Introduction:High-sensitivity cardiac troponin (hs-cTn) assays were first approved for use in the U.S. in 2017. They are the guideline preferred biomarker to evaluate patients with acute chest pain. Few data exist regarding implementation of hs-cTn assays in the U.S.Hypothesis:We hypothesize that use of hs-cTn assays has increased over time and that patients assessed with hs-cTn have a shorter length of stay (LOS) and similar use of cardiac testing.Methods:We examined trends in implementation of hs-cTn assays among participating hospitals in the NCDR Chest Pain MI Registry from 1/1/2019 through 9/30/2021. Excluding STEMI patients, associations between hs-cTn use, in-hospital diagnostic imaging, and patient outcomes were assessed using logistic or negative binomial regression models.Results:Among 550 participating hospitals with 251,000 patients in the registry, implementation of hs-cTn assays increased from 3.3% in Q1, 2019 to 32.6% in Q3, 2021 (Ptrend<0.0001; Figure). Implementation was similar by hospital size, type, and geographic location. hs-cTn use was associated with more echocardiography among patients with NSTE-ACS (82% vs. 75%; aOR: 1.43, 95% CI, 1.19-1.73) but not in low-risk chest pain. hs-cTn use was associated with decreased odds of invasive coronary angiography in low-risk patients (3.7% vs. 4.5%; aOR: 0.73, 95% CI, 0.58-0.92) but similar use in NSTE-ACS. There was no association between hs-cTn use and non-invasive stress/CTCA testing. Among NSTE-ACS patients, hs-cTn use was not associated with PCI, CABG, or in-hospital mortality. Use of hs-cTn was associated with shorter LOS (47.6 hours vs. 48 hours; IRR: 0.96, 95% CI, 0.93-0.98).Conclusions:Although implementation of hs-cTn among U.S. hospitals is increasing, most U.S hospitals continue to use less-sensitive troponin assays. hs-cTn use was associated with shorter LOS overall, greater use of echocardiography in NSTE-ACS, and lower use of invasive angiograms in low-risk patients.

Introduction:Diabetic cardiomyopathy (DbCM) is characterized by abnormal cardiac structure or function in the absence of cardiovascular disease (CVD). We assessed whether WATCH-DM, a validated risk score to predict incident heart failure (HF) in patients with DM, can identify DbCM.Methods:We prospectively enrolled 150 individuals with DM free of known CVD or overt HF in a single-center institution. The presence of DbCM was calculated using different definitions: 1) least restrictive: ≥1 echocardiographic abnormality (left atrial enlargement, left ventricular hypertrophy, diastolic dysfunction); 2) intermediate restrictive: ≥2 echocardiographic abnormalities; and 3) most restrictive: elevated N-terminal pro-B-type natriuretic peptide levels (>125 in normal/overweight or >100 pg/mL in obese) plus ≥2 echocardiographic abnormalities. DbCM prevalence was compared across high (scores ≥ 11) and low (scores < 11) WATCH-DM using chi-squared test. Adjusted logistic regression models were used to evaluate the association between WATCH-DM and components of DbCM.Results:The prevalence of DbCM ranged from 60.7% to 7.3% in the least and most restrictive definitions, respectively. Subjects with high (vs. low) WATCH-DM score were more often males (58% vs 32%), older (71 vs 68 years) and had a longer duration of DM (13 vs 10 years). Moreover, the concentration of NT pro-BNP was observed to be significantly higher in the high WATCH-DM cohort. Across definitions, individuals with high WATCH-DM had a numerically higher prevalence of DbCM (Fig. A). Among individual components, high WATCH-DM was associated with a higher risk of diastolic dysfunction (OR [95% CI] = 2.53 [1.20-5.54]) (Fig. B). We observed no significant differences in LV hypertrophy or LA enlargement across WATCH-DM scores.Conclusion:High WATCH-DM risk score is associated with a higher prevalence of DbCM and echocardiographic abnormalities and may be an effective tool for identifying patients with DbCM.

Introduction:Heart failure with preserved ejection fraction (HFpEF) is a common condition with one of its characteristics being exercise intolerance, which contributes to poor quality of life and clinical outcomes. High-intensity interval training (HIIT) is an innovative training approach, but its impact on patients with HFpEF is uncertain. We pooled data from all relevant studies reporting results of HIIT versus moderate continuous training (MCT) on cardiopulmonary exercise outcomes in patients with HFpEF.Methods:PubMed and SCOPUS were queried until February, 2022 for all randomized controlled trials (RCT) comparing the effects of HIIT versus MCT on outcomes such as peak oxygen consumption (peak VO2), respiratory exchange ratio (RER), and minute ventilation / carbon dioxide production (VE/CO2)slope. A random-effects model was used and weighted mean differences (WMDs) were reported with 95% confidence intervals (CI). Heterogeneity across studies was evaluated using the Higgins I2statistic.Results:Three RCTs (n = 150) were included in our analysis. The mean training duration was 23 weeks (range: 4 - 52 weeks). Pooled analysis demonstrated that HIIT significantly improved peak VO2(WMD = 1.46 mL.kg -1.min-1(0.88, 2.05); p<0.00001; I2=0%; Figure 1a), as compared to MCT in patients with HFpEF. However, no significant differences were demonstrated between HIIT and MCT, for RER (WMD = -0.10 (-0.32, 0.12); p=0.38; I2=0%; Figure 1b), and VE/CO2slope (WMD = 0.62 (-1.99, 3.24); p=0.64; I2=67%; Figure 1c).Conclusions:Our study demonstrates that HIIT, compared to MCT, had a significant impact on improving peak VO2, without evidence of significant benefits on VE/CO2slope. Larger trials of exercise training in HFpEF may consider peak VO2as a key outcome measure in addition to clinical events. Nevertheless, these improvements in peak VO2with HIIT could translate into improvements in quality of life and clinical outcomes in patients with HFpEF.

Introduction:The Centers for Medicare and Medicaid Services(CMS) expanded coverage for cardiac rehabilitation(CR) in 2014 for patients with clinically stable heart failure(HF) with reduced ejection fraction. Contemporary CR referral and participation rates among eligible patients with HFrEF are not known.Methods:Patients hospitalized for HF with ejection fraction ≤35% in the American Heart Association Get With The Guidelines®-HF(GWTG-HF) registry from 2010-2020 were included. Trends in rate of referrals and predictors of referral were determined. Among subset of participants with available Medicare-linked data, rate of CR participation was assessed, and 1-year outcomes were compared among patients referred vs. not referred to CR.Results:Of 69,441 HF patients eligible for CR, 17,076(24.6%) were referred to CR. There was substantial variability in referral across GWTG-HF participating centers (range 0-100%, IQR 4%-50%). Of patients with fee-for-service Medicare referred to CR, only 4.2% participated in CR in the year following HF hospitalization (median sessions: 3, range 1-76). Referral rate increased from 2010-2020, with significant increase since 2014 CMS coverage expansion (ptrend<0.001). Patients not referred were more likely to be older, of minority race, and with greater burden of comorbidities. Patients admitted to rural hospitals and those in the Northeast were less likely to be referred to CR. Among patients free of HF events within 30 days post-discharge, CR referral was independently associated with lower risk of 1-year all-cause mortality vs. those not referred (HR 0.84, 95% CI (0.73 - 0.98, p = 0.0267), without significant difference in 1-year HF-related or all-cause readmission.Conclusions:Although CR referrals have increased among eligible HF patients since CMS expanded coverage in 2014, absolute referral and participation rates remain low. Age, race, and burden of comorbidities were independently associated with CR referral.

Background:Frailty is associated with adverse post-hospitalization outcomes among patients admitted with heart failure. Whether frailty associated risk of adverse events among HF patients differs by HF subtype (HFpEF vs. HFrEF) is not well-established.Methods:Using Medicare claims data, we identified patients newly hospitalized for HF in 2016 within a cohort of 5% fee-for-service Medicare beneficiaries and used ICD-10 codes to specify HF subtype. Frailty was quantified using the Hospital Frailty Risk Score (HFRS), which computes frailty using 109 ICD-10 codes within 3 months of the index HF hospitalization. The association of HFRS with risk of outcomes were assessed using adjusted Cox proportional hazard models and multiplicative interaction testing was performed for HF subtype and HFRS. Improvement in model discrimination with addition of HFRS was assessed using change in the C-statistic and the integrated discrimination improvement test (IDI).Results:The study cohort included 14,276 Medicare beneficiaries hospitalized for HF [mean age (SD), 79 (8.4); 53 % women; 88 % white], among them 6836 (48%) with HFpEF and 3586 (25%) with HFrEF. In adjusted Cox models, higher frailty burden was associated with greater risk of 30- and 90- day mortality among beneficiaries hospitalized for HFrEF and HFpEF (Table 1). For readmission outcomes, higher frailty burden was associated with a significantly higher risk of 30-day and 90-day readmission among patients with HFpEF but not HFrEF (p-interaction HFRS * HF subtypes = 0.03 for both, Table 1). Addition of HFRS significantly improve discrimination to predict readmission. [30-day readmission, IDI (95%CI) = 0.011 (0.006-0.016)].Conclusion:Higher frailty burden is significantly associated with increased risk of mortality in patients with HFpEF and HFrEF. In contrast, frailty is more strongly associated with risk of readmission (30-day and 90-day) among patients with HFpEF only but not among HFrEF.

Introduction:While the utilization of mitral valve transcatheter edge-to-edge repair (TEER) procedures continues to increase over time, a validated, patient-centered, hospital-level performance metric for TEER is lackingHypothesis:We examined the utility of 30-risk adjusted home time (HT) as a hospital-level performance metric for TEER procedure and compared it with the established volume, 30-day readmission, and 30-day mortality-based measures.Methods:Medicare patients who received TEER from 2013 to 2019 were identified. HT is defined as time spent alive and out of a hospital, skilled nursing facility, or long-term facility 30 days after TEER. Hospital-level risk-standardized measures of 30-day HT, readmission (RSRR), and mortality (RSMR) were developed using standard risk-adjustment models and correlation between these performance metrics was estimated by Pearson correlation. Longer-term patient-level outcomes of 1-year mortality and readmission were also compared across quartiles of hospitals on 30-day HT.Results:Overall, 24,420 patients who underwent TEER in 344 hospitals were included (mean age 80 y, 54% men, 7% Black race). At the hospital level, the median risk-adjusted 30-day HT was 24 days. There was significant inverse correlation between risk adjusted 30-day HT and 30-day RSRR (r=-0.43), 30-day RSMR (r=-0.5), and modest correlation with hospital’s annual TEER volume (r=0.11, P=0.05). The 1-year readmission and mortality among patients undergoing TEER decreased across increasing 30-day HT categories (Figure). 30-day HT (vs. annual TEER volume) meaningfully reclassified hospital performance in 34% of the hospitals with lower 1-year mortality and readmission among hospitals that were up classified (vs. no change) in performance ranking.Conclusions:Risk-adjusted 30-day HT is a patient-centered, comprehensive quality metric to assess hospital performance in TEER that correlates with important short- and long-term outcomes.

Introduction:Individuals presenting with acute decompensated heart failure (ADHF) have varying response to diuretic therapy and short- and long-term prognosis.Hypothesis:If machine learning can risk stratify patients with ADHF and identify subgroups at risk for diuretic resistance.Methods:Participants with ADHF from the ROSE-AHF and CARRESS-HF clinical trials were included (n=451) and clustered using multivariable finite-mixture models based on diuretic efficiency (fluid output over first 72 hours per total intravenous loop diuretic dose). Differences in diuretic efficiency, in-hospital length of stay, and in-hospital mortality were assessed using linear and logistic regression models. Phenogroups were externally validated in trial (DOSE/ESCAPE, ATHENA-HF) and real-world (GWTG-HF) cohorts.Results:Clustering identified 3 phenogroups. Participants in phenogroup 1 (n=271, 60%) had worse diuretic efficiency [median(IQR) = 11.6(6.6-17.9) mL/mg) compared with phenogroups 2 (n=145, 32%) and 3 (n=35, 8%) [median(IQR) = 16.3(11.2-23.9) and 20.2(12.3-49.9) mL/mg, respectively; p<0.001]. An integer-based risk score to predict phenogroup 1 (lowest diuretic efficiency) was created: BAN-ADHF (Fig.). Net urine output was 2600 vs. 1090mL per 24 hours in patients with scores of 5 and 15, respectively (Fig). In the external validation cohorts, participants with scores ≥11 vs. <11 had significantly lower global well-being, higher natriuretic peptide levels on discharge, longer length of stay, and higher risk of in-hospital mortality.Conclusions:We developed and validated a phenomapping strategy and risk score for individuals with ADHF and differential response to diuretic therapy, which was associated with length of stay and mortality.

Introduction:The burden of ASCVD is higher among non-Hispanic Black (NHB) and Hispanic vs. non-Hispanic White (NHW) US adults, potentially due to differences in use of preventive medications such as statins. We evaluated patterns in statin use for primary prevention by self-identified race/ethnicity (NHB, NHW, and Hispanic) according to 10-year ASCVD risk using the Pooled Cohort Equations.Methods:This serial, cross-sectional analysis included NHANES participants from 2013-2020 age 40-75 years without ASCVD, diabetes, LDL ≥190 mg/dL, or missing data for estimation of 10-year ASCVD risk. Statin use was determined by interviewer pill bottle review. Poisson regression estimated adjusted prevalence ratios for statin use associated with race/ethnicity and ASCVD risk categories (5-<7.5%, 7.5-<20%, and ≥20%); all analyses incorporated NHANES survey weights.Results:A total of 3,088 participants representing 37.8 million US adults (mean age 62 y, 38% women, 13% NHB, 11% Hispanic, 76% NHW) were included. Overall, statin use was lower in NHB (20.0%) and Hispanic (15.4%) than NHW adults (27.9%). Within all ASCVD risk categories, the odds of statin use were significantly lower among NHB and Hispanic vs. NHW adults (Figure). Within each race/ethnicity group, the use of statins increased across increasing ASCVD risk strata, with a significantly greater utilization among those with ASCVD risk ≥20% (vs. ASCVD risk 5-<7.5%) (Figure). Statin use was stable over time and within race/ethnicity and risk strata (p>0.05 for all NHANES cycles).Conclusions:Overall statin use for primary prevention based on 10-year ASCVD risk was low in all race/ethnicity groups regardless of predicted ASCVD risk, though undertreatment was most severe in NHB and Hispanic adults. Improvements in equitable utilization of statins for primary prevention in Black and Hispanic adults are needed to address disparities in ASCVD.

Introduction:Machine learning methodology can provide means for the identification of diabetic cardiomyopathy (DbCM), a severe and evolving complication of diabetes that leads to high morbidity and mortality. Phenotypic characterization of patient subgroups may support clinically relevant risk stratification in the population with DbCM.Methods:Among individuals with diabetes from the ARIC study cohort (training, n=953), unsupervised hierarchical clustering was performed with 24 candidate variables incorporating echocardiographic parameters, NT-proBNP, and hs-cTnT. The cluster with highest risk of HF was identified as DbCM. A deep learning (DL) classifier was developed to predict DbCM in the ARIC training cohort and validated in a pooled community-based cohort (ARIC testing plus CHS; n=1,050) and an electronic health record (EHR) cohort (n=3,139).Results:Clustering identified 3 phenogroups. Participants in group 3 (vs. 1 and 2) were more commonly men, had higher levels of creatinine, hs-cTnT, and NT-proBNP, higher LA size and LVMi, and increased prevalence of diastolic dysfunction and hypertension. The 5-year risk of HF was significantly higher in phenogroup 3 and thus identified DbCM (17.8% vs. 2.0% [phenogroup 2] vs. 3.5% [phenogroup 1]) (Figure 1A). The key predictors of DbCM were NTproBNP, LVMi, LA size, and diastolic dysfunction parameters (Figure 1B). The DL classifier demonstrated high model performance in identifying DbCM (AUROC = 0.96, accuracy = 0.93, and precision = 0.75). In the validation cohort (community-based), the DL classifier identified 16% of participants with DbCM with a two-fold higher risk of HF (HR [95% CI], 1.99 [1.47-2.67]; ref = no DbCM). A similar pattern of findings was observed in the EHR cohort (37% with DbCM; DbCM vs. no DbCM: HR [95% CI], 1.58 [1.17-2.12]).Conclusion:Machine learning-based techniques can be used to define and identify DbCM which is associated with higher risk of overt HF.

Introduction:Current guidelines recommend N-terminal pro-brain natriuretic peptide (NT-proBNP) screening to identify subclinical structural cardiac abnormalities in patients at risk for developing clinical heart failure (HF) such as those with diabetes (DM). High-sensitivity cardiac troponin (hs-cTn) is another cardiac biomarker that can predict incident HF in patients with DM. It is unclear how the addition of hs-cTn to NT-proBNP screening impacts the detection of subclinical abnormalities of cardiac structure in patients with DM.Methods:Participants with DM but without known CVD at visit 5 (2011-2013) of the Atherosclerosis Risk in Communities (ARIC) study who had available cardiac biomarker data and detailed echocardiographic assessment were included. The associations of abnormal hs-cTn and/or NT-proBNP (defined as hs-cTn ≥ 6 ng/L and NT-proBNP ≥ 125 pg/mL) with abnormal echocardiographic measures of cardiac structure were assessed using multivariable adjusted linear regression analysis.Results:Participants (N=797, mean age 75±5y, 43% male, 77% White) had mean BMI 31±6 kg/m2, systolic blood pressure 129±17 mmHg, and serum creatinine 1.0±0.3 mg/dL. As shown in the table, abnormal NT-proBNP was associated with higher left ventricular (LV) mass, LV end-diastolic volume (EDV), left atrial (LA) volume, and E/A ratio. Abnormal hs-cTn was associated with lower global longitudinal strain (GLS), but no other measures of cardiac structure. The combination of abnormal hs-cTn and NT-proBNP was associated with higher LV EDV and LA volume and lower GLS.Conclusion:Among participants with DM free of CVD, abnormal NT-proBNP was associated with several echocardiographic parameters of abnormal cardiac structure. The addition of hs-cTn to NT-proBNP did not significantly improve detection of structural cardiac abnormalities other than low GLS.

Supplemental Digital Content is available in the text.

Introduction:Family history (FH) of premature CAD is a risk enhancer for adverse cardiovascular events. The preferred testing strategy to diagnose CAD in this high-risk population presenting with stable chest pain is unknown.Methods:This was a secondary analysis of the PROMISE trial, which randomized participants with stable chest pain to coronary computed tomographic angiography (CCTA) versus functional stress testing for the diagnosis of CAD and followed them for incident CV death or MI. Statistical analyses included logistic regression and Cox proportional hazard modeling. The effect of FH of premature CAD on the relationship between non-invasive testing modality and incident CV death or MI was assessed using interaction testing.Results:Patients with FH of premature CAD (n=3,098) were younger (58y vs 60y, p<0.001) and more likely to be women (57% vs 51%, p<0.001) than those without (n=6,584). They also had higher LDL-c levels (115 vs 112 mg/dL, p=0.01) and were more likely to be on aspirin (46% vs 44%, p=0.05) and a statin (48% vs 44%, p<0.001) at baseline. Over a median follow-up of 2.1 years, 60 (1.9%) participants with and 148 (2.3%) participants without FH of premature CAD had a primary outcome event. FH of premature CAD was not associated with an increased risk of the primary composite outcome (HR 1.01; 95% CI 0.66, 1.57). There was no significant difference in CV death or MI whether patients underwent CCTA or functional stress testing, irrespective of FH of premature CAD (FIGURE; FH: 1.9% vs 2.0%, No FH: 2.2% vs 2.3%; interaction p-value=0.8).Conclusions:In patients with FH of premature CAD presenting with stable chest pain, an initial strategy of using CCTA to diagnose CAD is similar to functional testing for adverse cardiovascular outcomes.

Background:Socioeconomic (SE) disadvantage is a strong determinant of adverse outcomes in patients with HF. The contribution of SE disparities to adverse outcomes in HF may differ among Black vs. White patients and has not been well studied.Methods:Using the 100% CMS MedPAR data, Black and White patients hospitalized with HF between 2014 and 2017 were identified and stratified based on the distressed community index (DCI)—a measure of the SE disadvantage of residential ZIP codes on a continuous scale (range 0-100, see Fig. legend)—into two groups: SE distressed (Q5) vs. non-distressed (Q1-4). The rates of 30-day and 1-year mortality and readmission were compared across the distressed vs. non-distressed race groups. The adjusted association between DCI and risk of adverse outcomes was assessed separately across the race groups using adjusted hierarchical logistic regression models with restricted cubic splines.Results:The study included 1,238,537 White (14.8% distressed) and 190,721 Black (44.4% distressed) patients. White patients living in SE distressed communities had a significantly higher risk of adverse outcomes at 30-days and 1-year f/u (Fig. A). In contrast, among Black patients, the risk of adverse outcomes among those living in distressed vs. non-distressed communities were not meaningfully different at 30-days and became more prominent by 1-year f/u. Similar results were noted in the restricted cubic spline analysis with stronger and more graded association between DCI score and risk of adverse outcomes in White (vs. Black) patients (Fig. B).Conclusion:SE distress is strongly associated with risk of adverse outcomes in White patients with HF. Among Black patients, SE distress is more common, but its adverse effects are less evident during short-term f/u and are better highlighted in the long-term. Other societal factors such as structural racism and poor access to care may be important prognostic determinants in Black patients with HF.

Background:Coronary artery disease (CAD) is a common cause of heart failure (HF). Whether the extent of coronary artery stenosis differs by HF type or prognosis for patients admitted with acute decompensated heart failure (ADHF) is uncertain.Methods:The Atherosclerosis Risk in Communities (ARIC) study conducted hospital surveillance of adjudicated HF in 4 US areas from 2005-2014. Medical histories were abstracted from the hospital record. Obstructive CAD was defined as > 49% stenosis in the left main coronary artery or >74% stenosis in the other major coronary arteries. Associations between obstructive CAD and 28-day mortality were analyzed separately for heart failure with preserved ejection fraction (HFpEF) and reduced ejection fraction (HFrEF), adjusting for age, race, sex, year of admission, and coronary revascularization procedures. All analyses were weighted by the inverse of the sampling probability.Results:A total of 5115 patients admitted with ADHF underwent coronary angiography during the hospital visit (mean age = 72, 45% women, 28% Black, 30% HFpEF). Obstructive CAD was more prevalent with HFrEF (Figure 1), whether at the left main coronary artery (16% vs 12%), left anterior descending artery (50% vs 35%), left circumflex artery (42% vs 34%), right coronary artery (45% vs 34%), or multiple coronary vessels (47% vs 34%). A similar proportion of patients with obstructive CAD underwent revascularization, irrespective of HF type (HFrEF: 55%, HFpEF: 61%). After adjustments, obstructive CAD (in any vessel) was associated with higher 28-day mortality, both for HFrEF (OR: 3.21; CI: 1.91 - 5.97) and HFpEF (OR: 3.62; 95% CI: 1.43 - 9.18) with no significant interaction by HF type (P-interaction = 0.9).Conclusion:Patients hospitalized with ADHF and coexisting obstructive CAD are at greater risk of short-term mortality, irrespective of the HF type, warranting the need for effective interventions as well as secondary preventive measures in this population.

Background:Low socioeconomic status (SES) is associated with atherosclerotic cardiovascular disease (ASCVD) and possible underestimation of risk by the pooled cohort equations (PCE). Whether coronary artery calcium (CAC) scores can improve risk discrimination in those with low SES is unknown.Methods:Individuals from the Dallas Heart Study free of ASCVD and with CAC scanning were evaluated. Low SES was defined as an annual income <$16,000 or an educational attainment level ≤11 years. Unadjusted and adjusted analyses assessing the relationships between SES and 1) CAC scores and 2) ASCVD events (fatal or non-fatal MI or stroke) were performed. The incremental predictive value of CAC in those at low and higher SES was assessed using c-statistics (PCE alone vs PCE + CAC).Results:Among 2246 individuals (mean age 44 yrs, 55% women, 45% Black), 115 ASCVD events occurred over a median of 12.5 years. Low SES by income (n=451) was associated with increased risk of ASCVD after adjustment for risk factors (HR 2.16, 95% CI 1.37-3.42), but was not independently associated with CAC. Higher CAC scores (0, 1-99, ≥100) tracked with increased 10-year ASCVD event rates in those at low (5, 10, and 22%) and higher SES (0.002, 4, and 11%), with low SES groups carrying greater ASCVD risk for every stratum of CAC, including with CAC=0. In multivariable models compared with CAC=0, those with CAC 1-99 and ≥100 had a greater risk of ASCVD events for individuals at higher SES [HR 3.40 (1.5-7.8), and 4.8 (1.9-12.6)], but not for those with low SES [HR 1.00 (0.4-2.4), and 1.6 (0.6-4.6)], (p-interaction CAC x SES=0.002). Similar results were found for low SES defined by education. The addition of CAC to PCE improved risk discrimination for individuals at higher SES, but not for individuals at low SES (Table 1).Conclusion:Individuals at low SES have significantly increased risk of ASCVD, however, CAC scores are not independently associated with ASCVD in this population and may be less useful in risk discrimination.

Introduction:The WATCH-DM score can predict risk of heart failure (HF) in patients with diabetes.Hypothesis:Addition of natriuretic peptide (NP) levels will improve WATCH-DM performance in individuals with dysglycemia.Methods:Adults with diabetes/pre-diabetes free of HF at baseline from 4 cohort studies (ARIC, CHS, FHS, and MESA) were included. The integer- [WATCH-DM(i)] and machine learning-based [WATCH-DM(ml)] scores were used to estimate the 5-year risk of incident HF. Discrimination was assessed by Harrell's concordance index (C-index) and calibration by the Greenwood-Nam-D'Agostino (GND) statistic. Improvement in model performance with the addition of NP-levels was assessed by C-index, Brier score, and continuous net reclassification improvement (NRI).Results:Of the 8,938 participants included, 3,554 (39.8%) had diabetes and 432 (4.8%) developed HF within 5-years. Among 5,384 (60.2%) participants with pre-diabetes, 647 (12.0%) developed incident HF. The WATCH-DM(ml) and (i) scores demonstrated high discrimination for predicting HF risk in diabetes (C-indices=0.76 and 0.69), pre-diabetes (0.83 and 0.72), and overall cohort (0.80 and 0.71), respectively, with no evidence of miscalibration (GND=P >0.10). A greater improvement in C-index was observed with the addition of NP-levels at lower WATCH-DM(i) scores with degradation of risk discrimination at higher scores (Fig. A). Calibration was also improved with addition of NP-levels at lower compared to higher WATCH-DM(i) scores (Fig. B). A greater improvement in reclassification was observed by combing WATCH-DM(i) score with selected NP-levels assessment in low (score<13) vs. high-risk (≥13) participants (NRI=0.45 vs. 0.17; p-value<0.001).Conclusions:The WATCH-DM risk score can accurately predict incident HF risk in community-based individuals with dysglycemia. The addition of NP-levels improves risk prediction among adults with low/intermediate but not high HF risk.

Introduction:Left ventricular (LV) systolic dysfunction is associated with a higher risk of adverse cardiovascular (CV) outcomes. However, the prognostic implication of supranormal LV ejection fraction (LVEF), as assessed by cardiac MRI, among adults with no prior CV disease (CVD) is unknown.Methods:Participants from the Multi-Ethnic Study of Atherosclerosis (MESA) and Dallas Heart Study (DHS) who were free of CVD at baseline and underwent cardiac MRI with LVEF above the normal MRI cutoff (≥57%) were included. The association between cohort specific LVEF categories and risk of clinically adjudicated major adverse CV events (MACE) was assessed using adjusted Cox models. The association between continuous measures of LVEF and risk of MACE was assessed in a pooled cohort analysis using cohort-specific Z-scores of LVEF.Results:There were 4,703 participants from MESA (mean age 62, 25% black, 54% women, median follow up 13.1 years) and 2,287 participants from DHS (mean age 44, 46% black, 57% women, median follow up 12 years) with 747 and 151 MACE events, respectively. In both cohorts, participants across increasing LVEF quartiles (MESA Q1 mean LVEF=63% vs. Q4 mean LVEF=78%) were older and had a higher burden of CV risk factors. Among cardiac parameters, across increasing quartiles, LV end-diastolic volume (Q1: 69.9 vs. Q4: 64.6 ml/m2) and LV mass (Q1: 79.1 vs. Q4: 74.9 gm/m2) significantly decreased (p<0.001), while LV stroke volume (Q1: 43.8 vs. Q4: 49.8 ml/m2) increased (p<0.001). In adjusted Cox models, the risk of MACE was highest among individuals in LVEF Q4 (vs. Q1) in both cohorts (Figure A). Similar patterns of association were observed between continuous distribution of LVEF and risk of MACE in the pooled analysis (Figure B).Conclusions:Among community-dwelling adults without CVD, supranormal LVEF is associated with elevated risk of MACE. Future studies are needed to elucidate the mechanisms underlying risk of CVD among individuals with supranormal LVEF.

Background:Prior prognostic models for acute decompensated HF (ADHF) have incorporated race as a covariate may not have completely account for the social and biological factors that underlie the racial disparities in outcomes. We developed race-specific models to improve risk prediction and better identify race-specific predictors of mortality in patients with ADHF using machine learning (ML) methods.Methods:Race-specific ML-models for in-hospital mortality were developed and validated in ADHF patients enrolled in the GWTG-HF registry between 2007 to 2020 (14,586 Black and 50,351 Non-Black adults) using over 40 candidate variables. External validation was performed among participants from the ARIC study with ADHF (n=1,115 Black and 2,028 Non-Black adults). The discrimination and calibration was compared with a previously validated risk score and cohort-specific logistic regression (LR) models. The changes in model reclassification performance with addition of zip-code level data of socioeconomic (SES) parameters was also assessed.Results:In the GWTG-HF cohort, the ML models had superior performance in both Black and Non-Black participants compared with the traditional GWTG-HF risk score (Table). The superior performance of the ML-model was also observed in the external validation cohort as compared with the other LR models (Table). Addition of measures of SES did not meaningfully change the performance but improved the reclassification metrics of the ML-models with net up-classification of risk in Black [NRI = 0.21 (0.07, 0.35)] and down-classification in Non-Black patients [NRI = -0.08 (-0.12, -0.04)]. SES was responsible for 21.7% of the total attributable mortality risk in Black adults compared to 0.4% in Non-Black adults.Conclusion:Race-specific, ML-based mortality models demonstrated superior performance when compared to traditional HF mortality risk models. Socioeconomic distress is an important contributor to risk in Black adults.

Introduction:Dapagliflozin (DAPA-CKD) and finerenone (FIDELIO-DKD) have shown to improve renal and cardiovascular (CV) outcomes in patients with type 2 diabetes (T2D) and chronic kidney disease (CKD).Hypothesis:We hypothesize individuals in a community-cohort who meet trial criteria will have higher rates of adverse outcomes.Methods:Adults with CKD from the Chronic Renal Insufficiency Cohort (CRIC) study were included. The inclusion criteria from each trial were applied to participants with T2D. Differences in characteristics and composite kidney and CV outcomes were assessed between trial eligibility groups. The estimated number of events prevented (NEP) over 3 years were calculated based on relative risk reduction estimates.Results:Among 2816 participants (mean [SD] age 62 [10], 41% female, 48% Black), 1545 (54.9%), 1458 (51.8%), and 1314 (46.7%) met DAPA-CKD, FIDELIO-DKD, and both inclusion criteria, respectively. Participants who met DAPA-CKD but not FIDELIO-DKD enrollment criteria were more likely to be Black and have higher CV, T2D, and kidney disease severity. Participants who met DAPA-CKD criteria (vs. ineligible) had higher rates of composite kidney (17.6% vs. 14.6%; p=0.006) and CV (15.5% vs. 12.6%; p=0.03) outcomes. Conversely, FIDELIO-DKD eligible participants had lower incidence of composite kidney outcomes (12.6% vs. 19.4%; p<0.001) and no differences in CV outcomes (14.2 vs. 14.2%; p=0.99). The estimated NEP per 1000 patients with dapagliflozin was 60 and 43 for kidney and CV outcomes, respectively, compared with 21 and 19 for finerenone (Fig). Notable differences in NEP were observed between races for dapagliflozin but not finerenone treatment, with Black patients having significantly higher kidney and CV NEP (Fig).Conclusions:In a community-based registry of CKD patients, approximately half of patients would be eligible for dapagliflozin or finerenone. The estimated NEP was higher with dapagliflozin compared to finerenone.

Introduction:COVID-19’s impact on in-hospital care quality and outcomes of patients hospitalized with acute heart failure (HF) has not been systematically evaluated nationally.Methods:Patients hospitalized with HF with ejection fraction (EF) <40% in the AHA GWTG-HF registry during the pandemic (3/1/2020 - 4/1/ 2021) and pre-pandemic (2/1/2019 - 2/29/2020) periods were included. Adherence to HF process of care measures, in-hospital mortality, and length of stay (LOS) were compared in the pre-pandemic vs pandemic period and among hospitalized HF patients with vs without COVID-19 across both periods.Results:40,005 pre-pandemic and 35,561 pandemic period patients admitted across 346 centers (median age 68, 33% women, 58% White) were included. There were no differences in clinical characteristics, comorbidities, presentation vital signs, or EF during the pandemic vs pre-pandemic periods. Among process of care measures, utilization of guideline-directed medical therapy at discharge was comparable across both periods. In contrast, rates of ICD placement or prescription and blood pressure control at discharge were lower during the pandemic (vs pre-pandemic period) (Table). In-hospital death (2.5% vs. 3.0%, p<0.001) and LOS (mean 5.4 vs. 5.7 days, p=0.008) were higher during the pandemic vs pre-pandemic. Substantial geographic variation was seen in the in-hospital death rates during the pandemic, with highest rates among patients hospitalized in the Northeast region (3.36%). Among HF patients hospitalized during the pandemic with COVID-19 (N = 527 [1.5%]), adherence to ICD placement or prescription at discharge and prescription of aldosterone antagonist or ACE/ARB/ARNi were lower, and risk of in-hospital death and length of stay were significantly higher than those without COVID-19.Conclusion:In-hospital mortality and adherence to certain quality measures worsened during COVID-19 pandemic among patients admitted for acute decompensated HFrEF.

Background:Physical frailty is common among older patients with acute decompensated HF (ADHF) and is associated with worse quality of life (QOL) and a higher risk of adverse CV events. In the REHAB-HF trial, a 12-week, multidomain physical function intervention improved functional status and QOL in older ADHF patients. Whether baseline frailty status modifies the benefits of the intervention remains unclear.Objective:Evaluate the interaction between baseline frailty and treatment effects of the physical function intervention in the REHAB-HF trial.Methods:Frailty status was assessed by the modified Fried criteria. Outcomes were change in physical function (Short Physical Performance Battery [SPPB] score and 6-minute walk distance [6-MWD]), QOL (Overall KCCQ score), and Geriatric Depression Scale (GDS) score at the end of the 12-week intervention. Association between changes in frailty score and rates all-cause hospitalization were assessed using adjusted linear regression models.Results:At baseline, among 337 participants (age: 72 y, 54% women) 57% were frail, and 43% were prefrail. At 12-week f/u, both prefrail and frail groups improved with the intervention; however, the frail group had significantly greater improvements over the prefrail group in SPPB score, 6MWD, and KCCQ (Table). A significant improvement was also noted in the GDS score with the intervention among frail but not prefrail participants (Table). In adjusted analysis, an improvement in frailty score at 12-weeks was significantly associated with lower rates of all-cause hospitalization in the 3 months following the intervention period (rate ratio [95%CI] = 0.65[0.55-0.76], p<0.001).Conclusion:ADHF patients with worse frailty status at baseline had greater improvement in functional status and QOL than those who were prefrail. Furthermore, improvement in frailty burden with the rehabilitation intervention was significantly associated with a lower risk of rehospitalization.