Optimal Screening for Predicting and Preventing the Risk of Heart Failure Among Adults With Diabetes Without Atherosclerotic Cardiovascular Disease: A Pooled Cohort Analysis.

BACKGROUND: The optimal approach to identify individuals with diabetes who are at a high risk for developing heart failure (HF) to inform implementation of preventive therapies is unknown, especially in those without atherosclerotic cardiovascular disease (ASCVD). METHODS: Adults with diabetes and no HF at baseline from 7 community-based cohorts were included. Participants without ASCVD who were at high risk for developing HF were identified using 1-step screening strategies: risk score (WATCH-DM [Weight, Age, Hypertension, Creatinine, HDL-C, Diabetes Control, QRS Duration, MI, and CABG] ≥12), NT-proBNP (N-terminal pro-B-type natriuretic peptide ≥125 pg/mL), hs-cTn (high-sensitivity cardiac troponin T ≥14 ng/L; hs-cTnI ≥31 ng/L), and echocardiography-based diabetic cardiomyopathy (echo-DbCM; left atrial enlargement, left ventricular hypertrophy, or diastolic dysfunction). High-risk participants were also identified using 2-step screening strategies with a second test to identify residual risk among those deemed low risk by the first test: WATCH-DM/NT-proBNP, NT-proBNP/hs-cTn, NT-proBNP/echo-DbCM. Across screening strategies, the proportion of HF events identified, 5-year number needed to treat and number needed to screen to prevent 1 HF event with an SGLT2i (sodium-glucose cotransporter 2 inhibitor) among high-risk participants, and cost of screening were estimated. RESULTS: The initial study cohort included 6293 participants (48.2% women), of whom 77.7% without prevalent ASCVD were evaluated with different HF screening strategies. At 5-year follow-up, 6.2% of participants without ASCVD developed incident HF. The 5-year number needed to treat to prevent 1 HF event with an SGLT2i among participants without ASCVD was 43 (95% CI, 29-72). In the cohort without ASCVD, high-risk participants identified using 1-step screening strategies had a low 5-year number needed to treat (22 for NT-proBNP to 37 for echo-DbCM). However, a substantial proportion of HF events occurred among participants identified as low risk using 1-step screening approaches (29% for echo-DbCM to 47% for hs-cTn). Two-step screening strategies captured most HF events (75-89%) in the high-risk subgroup with a comparable 5-year number needed to treat as the 1-step screening approaches (30-32). The 5-year number needed to screen to prevent 1 HF event was similar across 2-step screening strategies (45-61). However, the number of tests and associated costs were lowest for WATCH-DM/NT-proBNP ($1061) compared with other 2-step screening strategies (NT-proBNP/hs-cTn: $2894; NT-proBNP/echo-DbCM: $16 358). CONCLUSIONS: Selective NT-proBNP testing based on the WATCH-DM score efficiently identified a high-risk primary prevention population with diabetes expected to derive marked absolute benefits from SGLT2i to prevent HF.

Frailty Status Modifies the Efficacy of Exercise Training Among Patients With Chronic Heart Failure and Reduced Ejection Fraction: An Analysis From the HF-ACTION Trial.

BACKGROUND: Supervised aerobic exercise training (ET) is recommended for stable outpatients with heart failure (HF) with reduced ejection fraction (HFrEF). Frailty, a syndrome characterized by increased vulnerability and decreased physiologic reserve, is common in patients with HFrEF and associated with a higher risk of adverse outcomes. The effect modification of baseline frailty on the efficacy of aerobic ET in HFrEF is not known. METHODS: Stable outpatients with HFrEF randomized to aerobic ET versus usual care in the HF-ACTION (Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training) trial were included. Baseline frailty was estimated using the Rockwood frailty index (FI), a deficit accumulation-based model of frailty assessment; participants with FI scores >0.21 were identified as frail. Multivariable Cox proportional hazard models with multiplicative interaction terms (frailty × treatment arm) were constructed to evaluate whether frailty modified the treatment effect of aerobic ET on the primary composite end point (all-cause hospitalization or mortality), secondary end points (composite of cardiovascular death or cardiovascular hospitalization, and cardiovascular death or HF hospitalization), and Kansas City Cardiomyopathy Questionnaire score. Separate models were constructed for continuous (FI) and categorical (frail versus not frail) measures of frailty. RESULTS: Among 2130 study participants (age, 59±13 years; 28% women), 1266 (59%) were characterized as frail (FI>0.21). Baseline frailty burden significantly modified the treatment effect of aerobic ET (P interaction: FI × treatment arm=0.02; frail status [frail versus nonfrail] × treatment arm=0.04) with a lower risk of primary end point in frail (hazard ratio [HR], 0.83 [95% CI, 0.72-0.95]) but not nonfrail (HR, 1.04 [95% CI, 0.87-1.25]) participants. The favorable effect of aerobic ET among frail participants was driven by a significant reduction in the risk of all-cause hospitalization (HR, 0.84 [95% CI, 0.72-0.99]). The treatment effect of aerobic ET on all-cause mortality and other secondary endpoints was not different between frail and nonfrail patients (P interaction>0.1 for each). Aerobic ET was associated with a nominally greater improvement in Kansas City Cardiomyopathy Questionnaire scores at 3 months among frail versus nonfrail participants without a significant treatment interaction by frailty status (P interaction>0.2). CONCLUSIONS: Among patients with chronic stable HFrEF, baseline frailty modified the treatment effect of aerobic ET with a greater reduction in the risk of all-cause hospitalization but not mortality.

Diabetes Status Modifies the Association Between Different Measures of Obesity and Heart Failure Risk Among Older Adults: A Pooled Analysis of Community-Based NHLBI Cohorts.

BACKGROUND: Obesity and diabetes are associated with a higher risk of heart failure (HF). The interrelationships between different measures of adiposity-overall obesity, central obesity, fat mass (FM)-and diabetes status for HF risk are not well-established. METHODS: Participant-level data from the ARIC study (Atherosclerosis Risk in Communities; visit 5) and the CHS (Cardiovascular Health Study; visit 1) cohorts were obtained from the National Heart, Lung, and Blood Institute Biologic Specimen and Data Repository Information Coordinating Center, harmonized, and pooled for the present analysis, excluding individuals with prevalent HF. FM was estimated in all participants using established anthropometric prediction equations additionally validated using the bioelectrical impedance-based FM in the ARIC subgroup. Incident HF events on follow-up were captured across both cohorts using similar adjudication methods. Multivariable-adjusted Fine-Gray models were created to evaluate the associations of body mass index (BMI), waist circumference (WC), and FM with risk of HF in the overall cohort as well as among those with versus without diabetes at baseline. The population attributable risk of overall obesity (BMI≥30 kg/m2), abdominal obesity (WC>88 and 102 cm in women and men, respectively), and high FM (above sex-specific median) for incident HF was evaluated among participants with and without diabetes. RESULTS: The study included 10 387 participants (52.9% ARIC; 25.1% diabetes; median age, 74 years). The correlation between predicted and bioelectrical impedance-based FM was high (R2=0.90; n=5038). During a 5-year follow-up, 447 participants developed HF (4.3%). Higher levels of each adiposity measure were significantly associated with higher HF risk (hazard ratio [95% CI] per 1 SD higher BMI=1.15 [1.05, 1.27], WC=1.22 [1.10, 1.36]; FM=1.13 [1.02, 1.25]). A significant interaction was noted between diabetes status and measures of BMI (P interaction=0.04) and WC (P interaction=0.004) for the risk of HF. In stratified analysis, higher measures of each adiposity parameter were significantly associated with higher HF risk in individuals with diabetes (hazard ratio [95% CI] per 1 SD higher BMI=1.29 [1.14-1.47]; WC=1.48 [1.29-1.70]; FM=1.25 [1.09-1.43]) but not those without diabetes, including participants with prediabetes and euglycemia. The population attributable risk percentage of overall obesity, abdominal obesity, and high FM for incident HF was higher among participants with diabetes (12.8%, 29.9%, and 13.7%, respectively) versus those without diabetes (≤1% for each). CONCLUSIONS: Higher BMI, WC, and FM are strongly associated with greater risk of HF among older adults, particularly among those with prevalent diabetes.

Gender-Based Differences in Outcomes Among Resuscitated Patients With Out-of-Hospital Cardiac Arrest.

BACKGROUND: Studies examining gender-based differences in outcomes of patients experiencing out-of-hospital cardiac arrest have demonstrated that, despite a higher likelihood of return of spontaneous circulation, women do not have higher survival. METHODS: Patients successfully resuscitated from out-of-hospital cardiac arrest enrolled in the CCC trial (Trial of Continuous or Interrupted Chest Compressions during CPR) were included. Hierarchical multivariable logistic regression models were constructed to evaluate the association between gender and survival after adjustment for age, gender, cardiac arrest rhythm, witnessed status, bystander cardiopulmonary resuscitation, episode location, epinephrine dose, emergency medical services response time, and duration of resuscitation. Do not resuscitate (DNR) and withdrawal of life-sustaining therapy (WLST) order status were used to assess whether differences in postresuscitation outcomes were modified by baseline prognosis. The analysis was replicated among ALPS trial (Amiodarone, Lidocaine, or Placebo in Out-of-Hospital Cardiac Arrest) participants. RESULTS: Among 4875 successfully resuscitated patients, 1825 (37.4%) were women and 3050 (62.6%) were men. Women were older (67.5 versus 65.3 years), received less bystander cardiopulmonary resuscitation (49.1% versus 54.9%), and had a lower proportion of cardiac arrests that were witnessed (55.1% versus 64.5%) or had shockable rhythm (24.3% versus 44.6%, P<0.001 for all). A significantly higher proportion of women received DNR orders (35.7% versus 32.1%, P=0.009) and had WLST (32.8% versus 29.8%, P=0.03). Discharge survival was significantly lower in women (22.5% versus 36.3%, P<0.001; adjusted odds ratio, 0.78 [95% CI, 0.66-0.93]; P=0.005). The association between gender and survival to discharge was modified by DNR and WLST order status such that women had significantly reduced survival to discharge among patients who were not designated DNR (31.3% versus 49.9%, P=0.005; adjusted odds ratio, 0.74 [95% CI, 0.60-0.91]) or did not have WLST (32.3% versus 50.7%, P=0.002; adjusted odds ratio, 0.73 [95% CI, 0.60-0.89]). In contrast, no gender difference in survival was noted among patients receiving a DNR order (6.7% versus 7.4%, P=0.90) or had WLST (2.8% versus 2.4%, P=0.93). Consistent patterns of association between gender and postresuscitation outcomes were observed in the secondary cohort. CONCLUSIONS: Among patients resuscitated after experiencing out-of-hospital cardiac arrest, discharge survival was significantly lower in women than in men, especially among patients considered to have a favorable prognosis.

Development and Validation of Machine Learning-Based Race-Specific Models to Predict 10-Year Risk of Heart Failure: A Multicohort Analysis.

BACKGROUND: Heart failure (HF) risk and the underlying risk factors vary by race. Traditional models for HF risk prediction treat race as a covariate in risk prediction and do not account for significant parameters such as cardiac biomarkers. Machine learning (ML) may offer advantages over traditional modeling techniques to develop race-specific HF risk prediction models and to elucidate important contributors of HF development across races. METHODS: We performed a retrospective analysis of 4 large, community cohort studies (ARIC [Atherosclerosis Risk in Communities], DHS [Dallas Heart Study], JHS [Jackson Heart Study], and MESA [Multi-Ethnic Study of Atherosclerosis]) with adjudicated HF events. The study included participants who were >40 years of age and free of HF at baseline. Race-specific ML models for HF risk prediction were developed in the JHS cohort (for Black race-specific model) and White adults from ARIC (for White race-specific model). The models included 39 candidate variables across demographic, anthropometric, medical history, laboratory, and electrocardiographic domains. The ML models were externally validated and compared with prior established traditional and non-race-specific ML models in race-specific subgroups of the pooled MESA/DHS cohort and Black participants of ARIC. The Harrell C-index and Greenwood-Nam-D'Agostino χ2 tests were used to assess discrimination and calibration, respectively. RESULTS: The ML models had excellent discrimination in the derivation cohorts for Black (n=4141 in JHS, C-index=0.88) and White (n=7858 in ARIC, C-index=0.89) participants. In the external validation cohorts, the race-specific ML model demonstrated adequate calibration and superior discrimination (Black individuals, C-index=0.80-0.83; White individuals, C-index=0.82) compared with established HF risk models or with non-race-specific ML models derived with race included as a covariate. Among the risk factors, natriuretic peptide levels were the most important predictor of HF risk across both races, followed by troponin levels in Black and ECG-based Cornell voltage in White individuals. Other key predictors of HF risk among Black individuals were glycemic parameters and socioeconomic factors. In contrast, prevalent cardiovascular disease and traditional cardiovascular risk factors were stronger predictors of HF risk in White adults. CONCLUSIONS: Race-specific and ML-based HF risk models that integrate clinical, laboratory, and biomarker data demonstrated superior performance compared with traditional HF risk and non-race-specific ML models. This approach identifies distinct race-specific contributors of HF.

Development and validation of a model to predict cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke in patients with type 2 diabetes mellitus and established atherosclerotic cardiovascular disease.

BACKGROUND: Among individuals with atherosclerotic cardiovascular disease (ASCVD), type 2 diabetes mellitus (T2DM) is common and confers increased risk for morbidity and mortality. Differentiating risk is key to optimize efficiency of treatment selection. Our objective was to develop and validate a model to predict risk of major adverse cardiovascular events (MACE) comprising the first event of cardiovascular death, myocardial infarction (MI), or stroke for individuals with both T2DM and ASCVD. METHODS: Using data from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS), we used Cox proportional hazards models to predict MACE among participants with T2DM and ASCVD. All baseline covariates collected in the trial were considered for inclusion, although some were excluded immediately because of large missingness or collinearity. A full model was developed using stepwise selection in each of 25 imputed datasets, and comprised candidate variables selected in 20 of the 25 datasets. A parsimonious model with a maximum of 10 degrees of freedom was created using Cox models with least absolute shrinkage and selection operator (LASSO), where the adjusted R-square was used as criterion for selection. The model was then externally validated among a cohort of participants with similar criteria in the ACCORD (Action to Control Cardiovascular Risk in Diabetes) trial. Discrimination of both models was assessed using Harrell's C-index and model calibration by the Greenwood-Nam-D'Agostino statistic based on 4-year event rates. RESULTS: Overall, 1491 (10.2%) of 14,671 participants in TECOS and 130 (9.3%) in the ACCORD validation cohort (n = 1404) had MACE over 3 years' median follow-up. The final model included 9 characteristics (prior stroke, age, chronic kidney disease, prior MI, sex, heart failure, insulin use, atrial fibrillation, and microvascular complications). The model had moderate discrimination in both the internal and external validation samples (C-index = 0.65 and 0.61, respectively). The model was well calibrated across the risk spectrum-from a cumulative MACE rate of 6% at 4 years in the lowest risk quintile to 26% in the highest risk quintile. CONCLUSION: Among patients with T2DM and prevalent ASCVD, this 9-factor risk model can quantify the risk of future ASCVD complications and inform decision making for treatments and intensity.

Mediators of ertugliflozin effects on heart failure and kidney outcomes among patients with type 2 diabetes mellitus.

AIMS: Sodium-glucose cotransporter 2 (SGLT2) inhibitors have been shown to reduce the risk of hospitalization for heart failure (HHF) and composite kidney outcomes, but the mediators underlying these benefits are unknown. MATERIALS AND METHODS: Among participants from VERTIS CV, a trial of patients with type 2 diabetes mellitus and atherosclerotic cardiovascular disease randomized to ertugliflozin versus placebo, Cox proportional hazards regression models were used to evaluate the percentage mediation of ertugliflozin efficacy on the first HHF and kidney composite outcome in 26 potential mediators. Time-dependent approaches were used to evaluate associations between early (change from baseline to the first post-baseline measurement) and average (weighted average of change from baseline using all post-baseline measurements) changes in covariates with clinical outcomes. RESULTS: For the HHF analyses, early changes in four biomarkers (haemoglobin, haematocrit, serum albumin and urate) and average changes in seven biomarkers (early biomarkers + weight, chloride and serum protein) were identified as fulfilling the criteria as mediators of ertugliflozin effects on the risk of HHF. Similar results were observed for the composite kidney outcome, with early changes in four biomarkers (glycated haemoglobin, haemoglobin, haematocrit and urate), and average changes in five biomarkers [early biomarkers (not glycated haemoglobin) + weight, serum albumin] mediating the effects of ertugliflozin on the kidney outcome. CONCLUSIONS: In these analyses from the VERTIS CV trial, markers of volume status and haemoconcentration and/or haematopoiesis were the strongest mediators of the effect of ertugliflozin on reducing risk of HHF and composite kidney outcomes in the early and average change periods. GOV IDENTIFIER: NCT01986881.

Development and validation of optimal phenomapping methods to estimate long-term atherosclerotic cardiovascular disease risk in patients with type 2 diabetes.

AIMS/HYPOTHESIS: Type 2 diabetes is a heterogeneous disease process with variable trajectories of CVD risk. We aimed to evaluate four phenomapping strategies and their ability to stratify CVD risk in individuals with type 2 diabetes and to identify subgroups who may benefit from specific therapies. METHODS: Participants with type 2 diabetes and free of baseline CVD in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial were included in this study (N = 6466). Clustering using Gaussian mixture models, latent class analysis, finite mixture models (FMMs) and principal component analysis was compared. Clustering variables included demographics, medical and social history, laboratory values and diabetes complications. The interaction between the phenogroup and intensive glycaemic, combination lipid and intensive BP therapy for the risk of the primary outcome (composite of fatal myocardial infarction, non-fatal myocardial infarction or unstable angina) was evaluated using adjusted Cox models. The phenomapping strategies were independently assessed in an external validation cohort (Look Action for Health in Diabetes [Look AHEAD] trial: n = 4211; and Bypass Angioplasty Revascularisation Investigation 2 Diabetes [BARI 2D] trial: n = 1495). RESULTS: Over 9.1 years of follow-up, 789 (12.2%) participants had a primary outcome event. FMM phenomapping with three phenogroups was the best-performing clustering strategy in both the derivation and validation cohorts as determined by Bayesian information criterion, Dunn index and improvement in model discrimination. Phenogroup 1 (n = 663, 10.3%) had the highest burden of comorbidities and diabetes complications, phenogroup 2 (n = 2388, 36.9%) had an intermediate comorbidity burden and lowest diabetes complications, and phenogroup 3 (n = 3415, 52.8%) had the fewest comorbidities and intermediate burden of diabetes complications. Significant interactions were observed between phenogroups and treatment interventions including intensive glycaemic control (p-interaction = 0.042) and combination lipid therapy (p-interaction < 0.001) in the ACCORD, intensive lifestyle intervention (p-interaction = 0.002) in the Look AHEAD and early coronary revascularisation (p-interaction = 0.003) in the BARI 2D trial cohorts for the risk of the primary composite outcome. Favourable reduction in the risk of the primary composite outcome with these interventions was noted in low-risk participants of phenogroup 3 but not in other phenogroups. Compared with phenogroup 3, phenogroup 1 participants were more likely to have severe/symptomatic hypoglycaemic events and medication non-adherence on follow-up in the ACCORD and Look AHEAD trial cohorts. CONCLUSIONS/INTERPRETATION: Clustering using FMMs was the optimal phenomapping strategy to identify replicable subgroups of patients with type 2 diabetes with distinct clinical characteristics, CVD risk and response to therapies.

Spectral probabilities of top-down tandem mass spectra.

BACKGROUND: In mass spectrometry-based proteomics, the statistical significance of a peptide-spectrum or protein-spectrum match is an important indicator of the correctness of the peptide or protein identification. In bottom-up mass spectrometry, probabilistic models, such as the generating function method, have been successfully applied to compute the statistical significance of peptide-spectrum matches for short peptides containing no post-translational modifications. As top-down mass spectrometry, which often identifies intact proteins with post-translational modifications, becomes available in many laboratories, the estimation of statistical significance of top-down protein identification results has come into great demand. RESULTS: In this paper, we study an extended generating function method for accurately computing the statistical significance of protein-spectrum matches with post-translational modifications. Experiments show that the extended generating function method achieves high accuracy in computing spectral probabilities and false discovery rates. CONCLUSIONS: The extended generating function method is a non-trivial extension of the generating function method for bottom-up mass spectrometry. It can be used to choose the correct protein-spectrum match from several candidate protein-spectrum matches for a spectrum, as well as separate correct protein-spectrum matches from incorrect ones identified from a large number of tandem mass spectra.

Cardiovascular Disease Management With Sodium-Glucose Cotransporter-2 Inhibitors in Patients With Type 2 Diabetes: A Cardiology Primer.

Patients with type 2 diabetes face an elevated risk of cardiovascular disease. This review centers on sodium-glucose cotransporter-2 (SGLT2) inhibitors, a class of drugs that, according to a growing body of evidence, may have major potential for managing cardiovascular disease in patients with type 2 diabetes. This review presents findings from multiple clinical trials suggesting that SGLT2 inhibitors can not only serve as preventive therapeutic agents but also play a role in the active management of heart failure. The discussion includes the mechanism of action of SGLT2 inhibitors, emphasizing that they enhance urinary glucose excretion, which could lead to improved glycemic control and contribute to metabolic shifts beneficial to cardiac function. Alongside these cardiometabolic effects, safety concerns and practical considerations for prescribing these agents are addressed, taking into account potential adverse effects such as genitourinary infections and diabetic ketoacidosis as well as the financial implications for patients. Despite these drawbacks, therapeutic indications for SGLT2 inhibitors continue to expand, including for kidney protection, although further research is necessary to fully understand the mechanisms driving the cardioprotective and kidney-protective effects of SGLT2 inhibitors. By synthesizing current knowledge, this review intends to inform and guide clinical decision-making, thereby enhancing cardiovascular disease outcomes in patients with type 2 diabetes.

Postoperative atrial fibrillation (POAF) after cardiac surgery: clinical practice review.

Postoperative atrial fibrillation (POAF) after cardiac surgery is associated with elevated morbidity and mortality. Although current prediction models have limited efficacy, several perioperative interventions can reduce patients' risk of POAF. These begin with preoperative medications, including beta-blockers and amiodarone. Moreover, patients should be screened for preexisting atrial fibrillation (AF) so that concomitant surgical ablation and left atrial appendage occlusion can be performed in appropriate candidates. Intraoperative interventions such as posterior pericardiectomy can reduce mediastinal fluid accumulation, which is a trigger for POAF. Furthermore, many preventive strategies for POAF are implemented in the immediate postoperative period. Initiating beta-blockers, amiodarone, or both is reasonable for most patients. Overdrive atrial pacing, colchicine, and steroids have been used by some, although the evidence base is less robust. For patients with POAF, rate-control and rhythm-control strategies have comparable outcomes. Decision-making regarding anticoagulation should recognize that the stroke risk associated with POAF appears to be lower than that for general nonvalvular AF. The evidence that oral anticoagulation reduces stroke risk is less clear for POAF patients than for patients with general nonvalvular AF. Given that POAF tends to be shorter-lived and is associated with greater bleeding risks in the perioperative period, decisions regarding anticoagulation should be individualized. Finally, wearable technology and machine learning algorithms for better predicting and managing POAF appear to be coming soon. These technologies and a comprehensive clinical program could meaningfully reduce the incidence of this common complication.

Association of Beta-Blocker Use With Exercise Capacity in Participants With Heart Failure With Preserved Ejection Fraction: A Post Hoc Analysis of the RELAX Trial.

Patients with heart failure with preserved ejection fraction (HFpEF) often receive ß-blocker (BB) therapy for management of co-morbidities. However, the association of BB therapy with exercise capacity and health-related quality of life (HRQL) in HFpEF is not well-studied. In this post hoc analysis of the Phosphodiesterase-5 Inhibition to Improve Clinical Status and Exercise Capacity in HFpEF (RELAX) trial, which included patients with chronic stable HFpEF with peak exercise capacity assessment at baseline and at 12 and 24 weeks of follow-up, we evaluated the association of BB use with the measures of exercise capacity (peak exercise oxygen uptake), anaerobic threshold, and HRQL (Minnesota living with heart failure questionnaire). Separate linear mixed-effect models were constructed for each outcome with adjustment for treatment arm, demographics, medical history, left ventricular ejection fraction, and duration of heart failure. Of the 216 study participants (median age 69 years, 48.2% women), 76% reported BB use at baseline. Participants with (vs without) BB therapy were older (70 vs 63.5 years, p = 0.001) and had a higher prevalence of ischemic heart disease (44% vs 23%, p = 0.01). In the adjusted linear mixed model, BB use over time was not associated with peak exercise oxygen uptake (ß 95% confidence interval [CI] 0.2 (-0.31 to 0.7), p = 0.5) and 6-minute walk distance (ß 95% CI 14.69 [-14.25 to 43.63], p = 0.3). However, BB use was associated with a higher anaerobic threshold (ß 95% CI 0.32 (0.02 to 0.62), p = 0.036) and better HRQL (lower quality of life as assessed by Minnesota living with heart failure questionnaire score) (ß 95% CI -6.68 [-10.96 to -2.4], p = 0.002). Future trials are needed to better evaluate the effects of BB on exercise capacity in patients with chronic stable HFpEF.

Frailty Status Modifies the Efficacy of ICD Therapy for Primary Prevention Among Patients With HF.

BACKGROUND: Implantable cardioverter-defibrillator (ICD) therapy is recommended to reduce mortality risk in patients with heart failure with reduced ejection fraction (HFrEF). Frailty is common among patients with HFrEF and is associated with increased mortality risk. Whether the therapeutic efficacy of ICD is consistent among frail and nonfrail patients with HFrEF remains unclear. OBJECTIVES: The aim of this study was to evaluate the effect modification of baseline frailty burden on ICD efficacy for primary prevention among participants of the SCD-HeFT (Sudden Cardiac Death in Heart Failure Trial). METHODS: Participants in SCD-HeFT with HFrEF randomized to ICD vs placebo were included. Baseline frailty was estimated using the Rockwood Frailty Index (FI), and participants were stratified into high (FI > median) vs low (FI ≤ median) frailty burden groups. Multivariable Cox models with multiplicative interaction terms (frailty × treatment arm) were constructed to evaluate whether baseline frailty status modified the treatment effect of ICD for all-cause mortality. RESULTS: The study included 1,676 participants (mean age: 59 ± 12 years, 23% women) with a median FI of 0.30 (IQR: 0.23-0.37) in the low frailty group and 0.54 (IQR: 0.47-0.60) in the high frailty group. In adjusted Cox models, baseline frailty status significantly modified the treatment effect of ICD therapy (Pinteraction = 0.047). In separate stratified analysis by frailty status, ICD therapy was associated with a lower risk of all-cause mortality among participants with low frailty burden (HR: 0.56; 95% CI: 0.40-0.78) but not among those with high frailty burden (HR: 0.86; 95% CI: 0.68-1.09). CONCLUSIONS: Baseline frailty modified the efficacy of ICD therapy with a significant mortality benefit observed among participants with HFrEF and a low frailty burden but not among those with a high frailty burden.

Effect of liraglutide on thigh muscle fat and muscle composition in adults with overweight or obesity: Results from a randomized clinical trial.

BACKGROUND: Excess muscle fat is observed in obesity and associated with greater burden of cardiovascular risk factors and higher risk of mortality. Liraglutide reduces total body weight and visceral fat but its effect on muscle fat and adverse muscle composition is unknown. METHODS: This is a pre-specified secondary analysis of a randomized, double-blind, placebo-controlled trial that examined the effects of liraglutide plus a lifestyle intervention on visceral adipose tissue and ectopic fat among adults without diabetes with body mass index ≥30 kg/m2 or ≥27 kg/m2 and metabolic syndrome. Participants were randomly assigned to a once-daily subcutaneous injection of liraglutide (target dose 3.0 mg) or matching placebo for 40 weeks. Body fat distribution and muscle composition was assessed by magnetic resonance imaging at baseline and 40-week follow-up. Muscle composition was described by the combination of thigh muscle fat and muscle volume. Treatment difference (95% confidence intervals [CI]) was calculated by least-square means adjusted for baseline thigh muscle fat. The association between changes in thigh muscle fat and changes in body weight were assessed using Spearman correlation coefficients. The effect of liraglutide versus placebo on adverse muscle composition, denoted by high thigh muscle fat and low thigh muscle volume, was explored. RESULTS: Among the 128 participants with follow-up imaging (92.2% women, 36.7% Black), median muscle fat at baseline was 7.8%. The mean percent change in thigh muscle fat over median follow-up of 36 weeks was -2.87% among participants randomized to liraglutide (n = 73) and 0.05% in the placebo group (absolute change: -0.23% vs. 0.01%). The estimated treatment difference adjusted for baseline thigh muscle fat was -0.24% (95% CI, -0.41 to -0.06, P-value 0.009). Longitudinal change in thigh muscle fat was significantly associated with change in body weight in the placebo group but not the liraglutide group. The proportion of participants with adverse muscle composition decreased from 11.0% to 8.2% over follow-up with liraglutide, but there was no change with placebo. CONCLUSIONS: In a cohort of predominantly women with overweight or obesity in the absence of diabetes, once-daily subcutaneous liraglutide was associated with a reduction in thigh muscle fat and adverse muscle composition compared with placebo. The contribution of muscle fat improvement to the cardiometabolic benefits of liraglutide requires further study.

Association of global longitudinal strain by feature tracking cardiac magnetic resonance imaging with adverse outcomes among community-dwelling adults without cardiovascular disease: The Dallas Heart Study.

AIM: Left ventricular (LV) global longitudinal strain (GLS) may detect subtle abnormalities in myocardial contractility among individuals with normal LV ejection fraction (LVEF). However, the prognostic implications of GLS among healthy, community-dwelling adults is not well-established. METHODS AND RESULTS: Overall, 2234 community-dwelling adults (56% women, 47% Black) with LVEF ≥50% without a history of cardiovascular disease (CVD) from the Dallas Heart Study who underwent cardiac magnetic resonance (CMR) with GLS assessed by feature tracking CMR (FT-CMR) were included. The association of GLS with the risk of incident major adverse cardiovascular events (MACE; composite of incident myocardial infarction, incident heart failure [HF], hospitalization for atrial fibrillation, coronary revascularization, and all-cause death), and incident HF or death were assessed with adjusted Cox proportional hazards models. A total of 309 participants (13.8%) had MACE during a median follow-up duration of 17 years. Participants with the worst GLS (Q4) were more likely male and of the Black race with a history of tobacco use and diabetes with lower LVEF, higher LV end-diastolic volume, and higher LV mass index. Cumulative incidence of MACE was higher among participants with worse (Q4 vs. Q1) GLS (20.4% vs. 9.0%). In multivariable-adjusted Cox models that included clinical characteristics, cardiac biomarkers and baseline LVEF, worse GLS (Q4 vs. Q1) was associated with a significantly higher risk of MACE (hazard ratio [HR] 1.55, 95% confidence interval [CI] 1.07-2.24, p = 0.02) and incident HF or death (HR 1.57, 95% CI 1.03-2.38, p = 0.04). CONCLUSIONS: Impaired LV GLS assessed by FT-CMR among adults free of cardiovascular disease is associated with a higher risk of incident MACE and incident HF or death independent of cardiovascular risk factors, cardiac biomarkers and LVEF.

A Phenomapping Tool and Clinical Score to Identify Low Diuretic Efficiency in Acute Decompensated Heart Failure.

BACKGROUND: Individuals with acute decompensated heart failure (ADHF) have a varying response to diuretic therapy. Strategies for the early identification of low diuretic efficiency to inform decongestion therapies are lacking. OBJECTIVES: The authors sought to develop and externally validate a machine learning-based phenomapping approach and integer-based diuresis score to identify patients with low diuretic efficiency. METHODS: Participants with ADHF from ROSE-AHF, CARRESS-HF, and ATHENA-HF were pooled in the derivation cohort (n = 794). Multivariable finite-mixture model-based phenomapping was performed to identify phenogroups based on diuretic efficiency (urine output over the first 72 hours per total intravenous furosemide equivalent loop diuretic dose). Phenogroups were externally validated in other pooled ADHF trials (DOSE/ESCAPE). An integer-based diuresis score (BAN-ADHF score: blood urea nitrogen, creatinine, natriuretic peptide levels, atrial fibrillation, diastolic blood pressure, hypertension and home diuretic, and heart failure hospitalization) was developed and validated based on predictors of the diuretic efficiency phenogroups to estimate the probability of low diuretic efficiency using the pooled ADHF trials described earlier. The associations of the BAN-ADHF score with markers and symptoms of congestion, length of stay, in-hospital mortality, and global well-being were assessed using adjusted regression models. RESULTS: Clustering identified 3 phenogroups based on diuretic efficiency: phenogroup 1 (n = 370; 47%) had lower diuretic efficiency (median: 13.1 mL/mg; Q1-Q3: 7.7-19.4 mL/mg) than phenogroups 2 (n = 290; 37%) and 3 (n = 134; 17%) (median: 17.8 mL/mg; Q1-Q3: 10.8-26.1 mL/mg and median: 35.3 mL/mg; Q1-Q3: 17.5-49.0 mL/mg, respectively) (P < 0.001). The median urine output difference in response to 80 mg intravenous twice-daily furosemide between the lowest and highest diuretic efficiency group (phenogroup 1 vs 3) was 3,520 mL/d. The BAN-ADHF score demonstrated good model performance for predicting the lowest diuretic efficiency phenogroup membership (C-index: 0.92 in DOSE/ESCAPE validation cohort) that was superior to measures of kidney function (creatinine or blood urea nitrogen), natriuretic peptide levels, or home diuretic dose (DeLong P < 0.001 for all). Net urine output in response to 80 mg intravenous twice-daily furosemide among patients with a low vs high (5 vs 20) BAN-ADHF score was 2,650 vs 660 mL per 24 hours, respectively. Participants with higher BAN-ADHF scores had significantly lower global well-being, higher natriuretic peptide levels on discharge, a longer in-hospital stay, and a higher risk of in-hospital mortality in both derivation and validation cohorts. CONCLUSIONS: The authors developed and validated a phenomapping strategy and diuresis score for individuals with ADHF and differential response to diuretic therapy, which was associated with length of stay and mortality.

Association of High-Density Lipoprotein Parameters and Risk of Heart Failure: A Multicohort Analysis.

BACKGROUND: High-density lipoprotein (HDL) is commonly characterized by its cholesterol concentration (HDL-C) and inverse association with atherosclerotic cardiovascular disease. OBJECTIVES: The authors sought to evaluate the association of HDL particle concentration (HDL-P), HDL particle size (HDL-size), HDL-C, and cholesterol content per particle (HDL-C/HDL-P) with risk of overall heart failure (HF) and subtypes. METHODS: Participants from the Atherosclerosis Risk In Communities Study, Dallas Heart Study, Multi-Ethnic Study of Atherosclerosis, and Prevention of Renal and Vascular End-stage Disease studies without HF history were included. Associations of HDL-P, HDL-size, HDL-C, and HDL-C/HDL-P with risk of overall HF, HF with reduced and preserved ejection fraction were assessed using adjusted Cox models. RESULTS: Among 16,925 participants (53.5% women; 21.8% Black), there were 612 incident HF events (3.6%) (HF with reduced ejection fraction, 309 [50.5%]; HF preserved ejection fraction, 303 [49.5%]) over median follow-up of 11.4 years. In adjusted models, higher HDL-P was significantly associated with lower HF risk (HR of highest vs lowest tertile of HDL-P: 0.76 [95% CI: 0.62-0.93]). Larger HDL-size was significantly associated with higher overall HF risk (HR of largest vs smallest tertile of HDL-size: 1.27 [95% CI: 1.03-1.58]). HF risk associated with HDL-P and HDL-size was similar for HF subtypes. In adjusted analyses, there was no significant association between HDL-C and HF risk. Higher HDL-C/HDL-P was significantly associated with higher overall HF risk (HR of highest vs lowest tertile of HDL-C/HDL-P: 1.29 [95% CI: 1.04-1.60]). CONCLUSIONS: Higher HDL-P was associated with a lower risk of HF. In contrast, larger HDL-size was associated with higher risk of HF and there was no significant association observed between HDL-C and HF risk after accounting for cardiovascular risk factors.