Incidence Of Heart Failure In Patients Research Articles

Diabetic Cardiomyopathy-From Basics through Diagnosis to Treatment.

Diabetic cardiomyopathy (DCM) is the development of myocardial dysfunction in patients with diabetes despite the absence of comorbidities such as hypertension, atherosclerosis or valvular defect. The cardiovascular complications of poorly controlled diabetes are very well illustrated by the U.K. Prospective Diabetes Study (UKPDS), which showed a clear association between increasing levels of glycated hemoglobin and the development of heart failure (HF). The incidence of HF in patients with diabetes is projected to increase significantly, which is why its proper diagnosis and treatment is so important. Providing appropriate therapy focusing on antidiabetic and hypolipemic treatment with the consideration of pharmacotherapy for heart failure reduces the risk of CMD and reduces the incidence of cardiovascular complications. Health-promoting changes made by patients such as a low-carbohydrate diet, regular exercise and weight reduction also appear to be important in achieving appropriate outcomes. New hope for the development of therapies for DCM is offered by novel methods using stem cells and miRNA, which, however, require more thorough research to confirm their efficacy.

Prevalence of heart failure among hospitalized patient with T2D: results of a prospective observational multicenter study (CREDO)

BACKROUND: Heart failure (HF) is in the first place in the structure of cardiovascular death in patients with type 2 diabetes mellitus (T2D). One of the factors determining the prognosis of patients with this pathology is hospitalization. The difficulties of managing patients are related to the heterogeneity of the population. In some cases, HF in patients with T2D remains undiagnosed, and data on the true frequency of HF in patients with T2D and their clinical and laboratory characteristics in real clinical practice remain limited.AIM: To assess the prevalence of HF, clinical and demographic characteristics and therapy profile in patients with T2D admitted to multidisciplinary hospitals.MATERIALS AND METHODS: A prospective observational multicenter study was conducted at the city clinical hospitals of the Moscow. For the period from August 2022 to April 2023, data from patients with T2D were analyzed. Data collection was carried out at one visit. The study design did not involve any intervention in routine clinical practice, including the choice of diagnostic method or treatment.RESULTS: The study included 445 patients in accordance with the main inclusion criteria - T2D, age over 50 years, duration of T2D more than 3 years. The incidence of HF in patients with type 2 diabetes at discharge was 76.6%. The diagnosis of HF was confirmed in 48.7% (n=217), newly diagnosed HF occurred in 27.9% (n=124) of cases, in 12.6% of patients (n=56) the diagnosis of HF was withdrawn, in 10.8% (n=48) of cases the diagnosis of HF was not established. The frequency of prescribing drugs at discharge was iSGLT-2 — 77.3% (n=344), statins — 86.7% (n= 386), MRAs — 23.1% (n=103), diure­tics — 46.1% (n=205).CONCLUSION: 76.6% of patients with T2D admitted to multidisciplinary Moscow hospitals were diagnosed with HF at discharge. The results obtained confirm the possibility of detecting HF and initiating cardioprotective therapy at the hospital stage, using inpatient clinical diagnostic examination, and patients with type 2 diabetes lasting more than 3 years and aged over 50 years can be classified as a high risk group for developing HF.

Association of cardiometabolic and vascular atherosclerosis phenotypes on non-contrast chest CT with incident heart failure in patients with severe hypercholesterolemia

Coronary artery calcium (CAC), thoracic aorta calcification (TAC), non-alcoholic fatty liver disease (NAFLD), and epicardial adipose tissue (EAT) are associated with atherosclerotic cardiovascular disease (ASCVD) and heart failure (HF). We aimed to determine whether these cardiometabolic and atherosclerotic risk factors identified by non-contrast chest computed tomography (CT) are associated with HF hospitalizations in patients with LDL-C≥ 190 mg/dL. We conducted a retrospective cohort analysis of patients with LDL-C ≥190 mg/dL, aged ≥40 years without established ASCVD or HF, who had a non-contrast chest CT within 3 years of LDL-C measurement. Ordinal CAC, ordinal TAC, EAT, and NAFLD were measured. Kaplan-Meier curves and multivariable Cox regression models were built to ascertain the association with HF hospitalization. We included 762 patients with median age 60 (53-68) years, 68% (n=520) female, and median LDL-C level of 203 (194-216) mg/dL. Patients were followed for 4.7 (IQR 2.75-6.16) years, and 107 (14%) had a HF hospitalization. Overall, 355 (47%) patients had CAC=0, 210 (28%) had TAC=0, 116 (15%) had NAFLD, and median EAT was 79 mL (49-114). Moderate-Severe CAC (log-rank p<0.001) and TAC (log-rank p=0.006) groups were associated with increased HF hospitalizations. This association persisted when considering myocardial infarction (MI) as a competing risk. NAFLD and EAT volume were not associated with HF. In patients without established ASCVD and LDL-C≥190 mg/dL, CAC was independently associated with increased HF hospitalizations while TAC, NAFLD and EAT were not.

Association of neighbourhood-level material deprivation with adverse outcomes and processes of care among patients with heart failure in a single-payer healthcare system: A population-based cohort study.

We studied the association between neighbourhood material deprivation, a metric estimating inability to attain basic material needs, with outcomes and processes of care among incident heart failure patients in a universal healthcare system. In a population-based retrospective study (2007-2019), we examined the association of material deprivation with 1-year all-cause mortality, cause-specific hospitalization, and 90-day processes of care. Using cause-specific hazards regression, we quantified the relative rate of events after multiple covariate adjustment, stratifying by age ≤65 or ≥66 years. Among 395 763 patients (median age 76 [interquartile range 66-84] years, 47% women), there was significant interaction between age and deprivation quintile for mortality/hospitalization outcomes (p ≤ 0.001). Younger residents (age ≤65 years) of the most versus least deprived neighbourhoods had higher hazards of all-cause death (hazard ratio [HR] 1.19, 95% confidence interval [CI] 1.10-1.29]) and cardiovascular hospitalization (HR 1.29 [95% CI 1.19-1.39]). Older individuals (≥66 years) in the most deprived neighbourhoods had significantly higher hazard of death (HR 1.11 [95% CI 1.08-1.14]) and cardiovascular hospitalization (HR 1.13 [95% CI 1.09-1.18]) compared to the least deprived. The magnitude of the association between deprivation and outcomes was amplified in the younger compared to the older age group. More deprived individuals in both age groups had a lower hazard of cardiology visits and advanced cardiac imaging (all p < 0.001), while the most deprived of younger ages were less likely to undergo implantable cardioverter-defibrillator/cardiac resynchronization therapy-pacemaker implantation (p = 0.023), compared to the least deprived. Patients with newly-diagnosed heart failure residing in the most deprived neighbourhoods had worse outcomes and reduced access to care than those less deprived.

Prognostic value of monocyte-to-high-density lipoprotein-cholesterol ratio for all-cause mortality and heart failure in new-onset atrial fibrillation: a population-based cohort study

Abstract Background A growing body of evidence suggests that inflammation plays a role in the onset and progression of atrial fibrillation (AF). Monocyte-to-high-density lipoprotein-cholesterol ratio (MHR) has emerged as a novel and accessible biomarker that reflects both inflammation and oxidative stress. Previous studies have demonstrated the predictive value of MHR in several cardiovascular diseases including ischaemic stroke and acute coronary syndrome, but the association between MHR and adverse outcomes of AF remains unclear. Purpose With this study, we aimed to investigate the relationship of MHR with all-cause mortality and incident heart failure in patients with new-onset AF. Methods Patients with newly diagnosed AF from 1998-2021 (n=80,911) were included in this Hong Kong population-based cohort study. MHR was obtained by dividing fasting monocyte count by high-density lipoprotein-cholesterol, and patients were grouped according to MHR tertiles. We followed up patients until occurrence of outcomes, death or 1st September, 2022. The primary outcome was all-cause mortality, and the secondary outcome was incident heart failure. We evaluated the associations of MHR with all-cause mortality and heart failure both on a continuous scale using restricted cubic spline curves and by categories using multivariate Cox proportional hazards regression model. Results The median age of the cohort was 77.9 years old and 41,536 (51.3%) were male. Over a median follow-up of 3.7 years, 43,902 (54.3%) deaths and 14,114 (17.4%) incident heart failure occurred. The restricted cubic spline curves illustrated that MHR had a non-linear association with all-cause mortality and heart failure. Univariate Cox regression indicated that increased MHR at tertiles 2 and 3 were significantly associated with higher risks of all-cause mortality (HR: 1.06 [1.04-1.09], P&amp;lt;0.001, 1.25 [1.22-1.28], P&amp;lt;0.001, respectively) and new onset heart failure (1.07 [1.02-1.11], P=0.002, 1.23 [1.18-1.28], P&amp;lt;0.001, respectively) when compared to those in tertile 1. MHR remained a significant predictor of mortality (tertile 2 HR: 1.06 [1.04-1.09], P&amp;lt;0.001, tertile 3 HR: 1.22 [1.19-1.25], P&amp;lt;0.001) and heart failure (tertile 2 HR: 1.06 [1.02-1.10], P=0.007, tertile 3 HR: 1.21 [1.16-1.26], P&amp;lt;0.001) after multivariable adjustment. Conclusion MHR is a promising prognostic biomarker for all-cause mortality and heart failure in patients with new-onset AF.

Abstract 16324: A Deep Learning Electrocardiogram Model Identifies Risk of Incident Heart Failure in Patients With Subclinical Hypothyroidism

Introduction: Subclinical hypothyroidism (SH) is associated with an increased risk of heart failure (HF). However, there are no established measures to predict HF development within the SH population. Hypothesis: Risk of incident heart failure in SH can be predicted from a 12-lead electrocardiogram using features extracted by a convolutional neural network-based model. Methods: To test the hypothesis, we developed a convolutional neural network (CNN)-based model to detect ECG features linked with low thyroid function by training to discriminate the presence of hypothyroidism from 10,745 ECGs (2,693 from patients with low free T4 (FT4) and 8,052 from age, sex-matched patients without evidence of low FT4). The model was applied to baseline ECGs from an external cohort of 2,293 patients with SH (defined TSH &gt;4.5mIU/L and FT4 within 0.9-1.9ng/dl) to estimate the cardiac phenotype induced by hypothyroidism (ECG-hypothyroidism score). Cumulative incidences of HF admission were compared between groups stratified by the tertile of the model output (low, intermediate, and high score groups). Adjusted hazard ratios (aHR) were calculated using Cox proportional hazard model. Results: HF admission was more frequent in the high score group (9.60/100 person-year), compared with the intermediate or low score groups (5.08 and 2.29 per 100 person-year in the, respectively; Fig ). Subgroup analyses by sex and age group yielded similar results. The association between the ECG-hypothyroidism score and HF admission remained significant after adjustment for patient characteristics, conventional ECG abnormalities, and baseline thyroid function (high vs low score group: aHR 3.56, [95%CI, 2.26-5.61]; high vs intermediate score group: aHR 1.78, [95%CI, 1.25-2.54]). Conclusions: The CNN-based model, trained to detect prevalent hypothyroidism, accurately identified patients at high risk for HF admission within the SH population using baseline ECG.

Hospital Resource Utilization and Costs in Patients with Heart Failure in France.

Heart failure (HF) is one of the leading causes of morbidity and mortality, and economic burden on the healthcare system. The aim of this study was to estimate the current hospital resource utilization and costs for HF patients in France. This retrospective cohort study included adult HF patients hospitalized in France between January 1, 2019 and December 31, 2019. Data related to sociodemographic characteristics, number and duration of hospital stays, use of medical procedures or expensive and innovativedrugs/medical devices included in the "liste-en-sus", and comorbidities were retrieved from the French national hospital discharge database. Data were further stratified based on the presence or absence of cardiac decompensation, comorbidities, ejection fraction (EF) status, and incident/prevalent patients. In 2019, a total of 430,544 patients were hospitalized in France with HF as a primary or associated diagnosis, with 51.9% male and 48.1% female and a mean age of 79.0years. More than 75% of the study population was composed of prevalent HF patients. About 3.1% of patients were diagnosed with at least one event of cardiac decompensation during follow-up. Also, 20.2% and 9.9% of patients were identified with preserved and reduced EFs, respectively. The average number and length of hospital stays were 1.7 per patient and 10.4 days per patient, respectively. The annual cost of hospitalization for HF was €8341.3 per patient. Presence of cardiac decompensation at index date or during follow-up, reduced EF, and comorbidities were associated with numerically higher frequency and length of hospitalization, and hospitalization cost. For hospitalization and 'liste-en-sus' medical devices, higher cost was observed in incident than prevalent HF patients, while for 'liste-en-sus' drugs, higher cost was reported in prevalent than incident HF patients. This study highlighted the high economic hospital burden of HF in France. More studies investigating different HF patient profiles must be conducted to help determine the main factors of hospital cost for HF.

Triglyceride-glucose index and heart failure: a systematic review and meta-analysis

BackgroundInsulin resistance (IR) is a major metabolic disorder observed in heart failure (HF) and is tightly associated with patients’ poor prognosis. The triglyceride-glucose index (TyG) has been proposed as a surrogate marker of IR in HF. Yet, whether TyG is a reliable clinical marker is still under debate. Hence, we aimed to respond to this relevant question via a systematic review and meta-analysis of existing studies.MethodsA systematic search was conducted in PubMed, Embase, Scopus, and Web of Science to find studies investigating the TyG index in patients with HF or its association with the incidence of HF. Adjusted hazard ratios (HR) and 95% confidence intervals (CI) were pooled through random-effect meta-analysis. HRs were calculated using TyG as a continuous variable (1 unit increase) and by comparing the group with the highest TyG to the lowest TyG group.ResultsThirty studies, involving 772,809 participants, were included in this systematic review. Meta-analysis of seven studies comparing the highest-TyG to the lowest-TyG group showed a significantly increased risk of HF in the former group (HR 1.21, 95% CI 1.14 to 1.29, P < 0.01). The same result was found when pooling the HRs for a one-unit increase in the TyG index (HR 1.17, 95% CI 1.08 to 1.26). Similarly, a more elevated TyG index was associated with a higher incidence of HF in patients with type 2 diabetes or coronary artery disease. Additionally, the incidence of adverse events (readmission and mortality) in patients with HF was associated with TyG.ConclusionOur findings support the TyG index as a valuable marker to assess the risk of HF incidence in different populations and as a prognostic marker in patients with HF. Further studies should be conducted to confirm these associations and investigate the clinical utility of the TyG index.

The Association of Metformin With Heart Failure in Patients With Diabetes Mellitus Receiving Anthracycline Chemotherapy

BackgroundThe prevention of heart failure (HF) is an important issue in patients treated with anthracyclines. Metformin, widely used to treat diabetes mellitus (DM), protects from anthracycline-induced cardiotoxicity in vitro and in animal models. ObjectivesThe aim of our study was to test the association of metformin with the occurrence of symptomatic HF in patients with DM receiving anthracyclines. MethodsA total of 561 patients with DM received new anthracycline therapy between 2008 and 2021 in a tertiary care center; propensity score matching was used to compare patients with or without metformin treatment. The primary outcome was new onset symptomatic HF occurring within 1 year of the initiation of anthracyclines. ResultsA total of 315 patients (65 ± 11 years of age, 33.7% male) were included. Patients with and without metformin were well matched for age, sex, type of cancer, medications, and cardiovascular risk factors. Six patients treated with metformin and 17 matched patients developed HF within 1 year of anthracycline initiation. The incidence of HF in patients treated with metformin was lower than patients without metformin within 1 year after anthracyclines (cumulative incidence: 3.6% vs 10.5%; P = 0.022; HR: 0.35; 95% CI: 0.14-0.90; P = 0.029). The use of metformin (HR: 0.71; 95% CI: 0.50-1.00; P = 0.049), was also associated with lower mortality. ConclusionsThe use of metformin was associated with a lower incidence of HF and overall mortality in patients with DM receiving anthracyclines. Our findings should be further confirmed by randomized control trials.

Trends in Medical and Device Therapies Following Incident Heart Failure in Denmark during 1996-2019: A Nationwide Register-Based Follow-Up Study.

Introduction: Data on temporal trends in guideline-based medical and device therapies in real-world chronic heart failure (HF) patients are lacking. Methods: Register-based nationwide follow-ups of temporal trends in characteristics, guideline-recommended therapies, one-year all-cause mortality, and HF rehospitalizations in incident HF patients in Denmark during 1996-2019. Results: Among 291,720 incident HF patients, the age at the onset of HF was stable over time. While initially fairly equal, the sex distribution markedly changed over time with more incidents occurring in men overall. Hypertension and diabetes increased significantly over time, while other comorbidities remained stable. Between 1996 and 2019, significant increases in angiotensin-converting enzyme inhibitor and angiotensin II-receptor blocker (ACEi/ARB) therapy (38.2% to 69.9%), beta-blocker therapy (15.5% to 70.6%), and mineralocorticoid receptor antagonist (MRA) therapy (11.8% to 34.5%) were seen. Angiotensin receptor-neprilysin inhibitor (ARNI) and sodium-glucose cotransporter-2 inhibitors (SGLT2i) were introduced in the middle of the past decade, with minor increases but overall low uses: ARNI (2015: 0.1% vs. 2019: 3.9%) and SGLT2i (2012: <0.1% vs. 2019: 3.9%). Between 1999 and 2019, implantable cardioverter-defibrillator (ICD) use increased significantly: 0.1% to 3-4%. Cardiac resynchronization therapy (CRT) use similarly increased between 2000 and 2019: 0.2% to 2.3%. Between 1996 and 2019, one-year all-cause mortality decreased significantly: 34.6% to 20.9%, as did HF rehospitalizations (6% to 1.3%). Conclusions: Among 291,720 incident HF patients in Denmark during 1996-2019, significant increases in the use of ACEi/ARB, beta-blockers, MRAs, and devices were seen, with concurrent significant decreases in the one-year all-cause mortality and HF rehospitalization rates. The use of CRT, ARNI, and SGLT2i remained low, and MRAs were relatively underutilized, thereby representing future targets to potentially further improve HF prognoses.

C-Reactive Protein and Risk of Incident Heart Failure in Patients With Cardiovascular Disease

BackgroundPatients with established cardiovascular disease (CVD) are at high risk of incident heart failure (HF), which may in part reflect the impact of systemic inflammation. ObjectivesThe goal of this study was to determine the association between C-reactive protein (CRP) and incident HF in patients with established CVD. MethodsPatients from the prospective UCC-SMART (Utrecht Cardiovascular Cohort-Second Manifestations of ARTerial disease) cohort with established CVD, but without prevalent HF were included (n = 8,089). Incident HF was defined as a first hospitalization for HF. The association between baseline CRP and incident HF was assessed using Cox proportional hazards models adjusted for established risk factors (ie, age, sex, myocardial infarction, smoking, diabetes mellitus, body mass index, blood pressure, cholesterol, and kidney function). ResultsDuring a median follow-up of 9.7 years (IQR 5.4-14.1 years), 810 incident HF cases were observed (incidence rate 1.01/100 person-years). Higher CRP was independently associated with an increased risk of incident HF: HR per 1 mg/L: 1.10 (95% CI: 1.07-1.13), and for last vs first CRP quartile: 2.22 (95% CI: 1.76-2.79). The association was significant for both HF with reduced (HR: 1.09; 95% CI: 1.04-1.14) and preserved ejection fraction (HR: 1.12; 95% CI: 1.07-1.18) (P for difference = 0.137). Additional adjustment for medication use and interim myocardial infarction did not attenuate the association, and the association remained consistent beyond 15 years after the CRP measurement. ConclusionsIn patients with established CVD, CRP is an independent risk marker of incident HF. These data support ongoing trial efforts to assess whether anti-inflammatory agents can reduce the burden of HF.

Depression is associated with heart failure in patients with type 2 diabetes mellitus.

Type 2 diabetes mellitus (T2DM) is associated with an increased risk of heart failure (HF). Depression, a common comorbidity of T2DM, may further increase the risk of heart failure (HF). We investigated the association between depression and incident HF in patients with T2DM. Depressive symptoms were assessed in the ACCORD Health-Related Quality of Life study participants at baseline, 12, 36, and 48 months using the nine-item Patient Health Questionnaire (PHQ-9). The severity of depressive symptoms was categorized as none (0-4 points), mild (5-9 points), or moderate-severe (10-24 points). Cox regression with PHQ-9 as a time-dependent covariate was used to assess the association between depression and incident HF. During the median follow-up of 8.1 years, 104 participants developed HF (incidence: 7.1/1,000 person-years). Half of the participants with moderate-severe depression were relieved and a significant percentage of participants without depression or with mild depression worsened to mild or moderate-severe depression during the follow-up period, respectively. Each unit increase in the PHQ-9 score was associated with a 5% higher risk of HF (hazard ratio [HR]:1.05, 95% confidence interval [CI]: 1.01-1.10). Patients with depression ever (HR: 2.23, 95% CI: 1.25-3.98) or persistent depression (HR: 2.13, 95% CI: 1.05-4.44) had a higher risk of HF than those without depression ever. Depressive symptoms change greatly in T2DM patients, depressive symptoms are an independent risk factor for HF. These results reinforce the importance of continuous evaluation and management of mental health status in T2DM patients with high HF risk.

Trends in Incidence of Chronic Heart Failure in Patients With Rheumatoid Arthritis: A Population-Based Study Validating Different Heart Failure Definitions.

To assess trends in the incidence of heart failure (HF) in patients with incident rheumatoid arthritis (RA) from 1980 to 2009 and to compare different HF definitions in RA. The study population comprised Olmsted County, Minnesota residents with incident RA (age ≥ 18 yrs, 1987 American College of Rheumatology criteria met in 1980-2009). All subjects were followed until death, migration, or April 30, 2019. Incident HF events were defined as follows: (1) meeting the Framingham criteria for HF, (2) diagnosis of HF (outpatient or inpatient) by a physician, or (3) International Classification of Diseases, 9th revision (ICD-9), or ICD, 10th revision (ICD-10), codes for HF. Patients with HF prior to the RA incidence/index date were excluded. Cox proportional hazards models were used to compare incident HF events by decade, adjusting for age, sex, and cardiovascular risk factors. HF definitions 2 and 3 were compared to the Framingham criteria. The study included 905 patients with RA (mean age 55.9 years; 68.6% female; median follow-up 13.4 years). The 10-year cumulative incidence of HF events by any chart-reviewed method in the RA cohort in the 1980s was 11.66% (95% CI 7.86-17.29), in the 1990s it was 12.64% (95% CI 9.31-17.17), and in the 2000s it was 7.67% (95% CI 5.36-10.97). The incidence of HF did not change across the decades of RA incidence using any of the HF definitions. Physician diagnosis of HF and ICD-9/10 code-based definitions of HF performed well compared to the Framingham criteria, showing moderate to high sensitivity and specificity. The incidence of HF in patients with incident RA in the 2000s vs the 1980s was not statistically significantly different. Physician diagnosis of HF and ICD-9/10 codes for HF performed well against the Framingham criteria.

Deep-learning-based prognostic modeling for incident heart failure in patients with diabetes using electronic health records: A retrospective cohort study.

Patients with type 2 diabetes mellitus (T2DM) have more than twice the risk of developing heart failure (HF) compared to patients without diabetes. The present study is aimed to build an artificial intelligence (AI) prognostic model that takes in account a large and heterogeneous set of clinical factors and investigates the risk of developing HF in diabetic patients. We carried out an electronic health records- (EHR-) based retrospective cohort study that included patients with cardiological clinical evaluation and no previous diagnosis of HF. Information consists of features extracted from clinical and administrative data obtained as part of routine medical care. The primary endpoint was diagnosis of HF (during out-of-hospital clinical examination or hospitalization). We developed two prognostic models using (1) elastic net regularization for Cox proportional hazard model (COX) and (2) a deep neural network survival method (PHNN), in which a neural network was used to represent a non-linear hazard function and explainability strategies are applied to estimate the influence of predictors on the risk function. Over a median follow-up of 65 months, 17.3% of the 10,614 patients developed HF. The PHNN model outperformed COX both in terms of discrimination (c-index 0.768 vs 0.734) and calibration (2-year integrated calibration index 0.008 vs 0.018). The AI approach led to the identification of 20 predictors of different domains (age, body mass index, echocardiographic and electrocardiographic features, laboratory measurements, comorbidities, therapies) whose relationship with the predicted risk correspond to known trends in the clinical practice. Our results suggest that prognostic models for HF in diabetic patients may improve using EHRs in combination with AI techniques for survival analysis, which provide high flexibility and better performance with respect to standard approaches.

Associations between rheumatoid arthritis, incident heart failure, and left ventricular ejection fraction

Rheumatoid arthritis (RA) is an independent risk factor for heart failure (HF). Yet, the association between RA and left ventricular ejection fraction (LVEF) in incident HF is not well studied, nor are outcomes of HF in RA by LVEF. We identified incident HF patients between 2003 and 2018 through the Swedish Heart Failure Registry, enriched with data from national health registers. Using logistic regression, associations between a prior diagnosis of RA and LVEF among HF patients and vs age, sex, and geographical area matched general population controls without HF were assessed. Additionally, associations between HF with vs without a prior diagnosis of RA, by LVEF, and outcomes up to 5 years after HF diagnosis were investigated using Cox regression. LVEF was primarily dichotomized at 40% and secondarily categorized as <40%, 40% to 49%, and ≥50%. Covariates included demographics and cardiovascular comorbidities. Among 20,916 incident HF patients, 331 (1.6%) had RA vs 1,047/103,501 (1.0%) of HF-free controls. The odds ratio (OR) for RA was 1.4 (95% CI: 1.1-1.8) in LVEF<40% vs HF-free controls and 1.6 (95% CI: 1.3-2.0) in LVEF≥40% vs HF-free controls. Among HF patients, RA was more common in HF with LVEF ≥40% (1.9%) vs LVEF<40% (1.3%), corresponding to OR 1.4 (95% CI: 1.1-1.7). No associations between RA and cardiovascular outcomes were observed across LVEF. An association between RA and all-cause mortality was observed only for patients with LVEF<40% (hazard ratio: 1.4; 95% CI: 1.1-1.8). RA was independently associated with incident HF, particularly HF with LVEF≥40%. RA did not associate with cardiovascular outcomes following HF diagnosis but was associated with increased risk of all-cause mortality in HF with LVEF<40%.

Bariatric Surgery and Incident Heart Failure: a Propensity Score Matched Nationwide Cohort Study

BackgroundBariatric surgery results in significant weight loss and a reduction in the incidence of cardiovascular disease in patients with obesity; however, relatively little research considers its effect on the incidence of heart failure (HF). We aimed to determine whether bariatric surgery reduces the incidence of HF in patients with obesity, compared to non-surgical management. MethodsA propensity-score matched, retrospective cohort study using patients records from the nationwide Clinical Practice Research Database (CPRD) was conducted. 3052 patients who received bariatric surgery were matched with 3052 patients who did not, according to propensity to receive bariatric surgery, determined through a logistic regression model. Patients were eligible if >18 years old, BMI > 35 kg/m2, and no prior diagnosis of HF. The pre-defined primary endpoint was the development of new HF, and secondary endpoints were all-cause mortality and hospitalisations due to HF. ResultsPatients who received bariatric surgery had a significantly lower incidence of new HF (hazard ratio 0.45, 95% confidence interval 0.28–0.73, p = 0.0011) and all-cause mortality (hazard ratio 0.56, 95% confidence interval 0.38–0.83, p = 0.0036). ConclusionsThis study provides evidence of lower rates of HF and all-cause mortality in patients who undergo bariatric surgery, compared to propensity-score matched controls. Future studies to understand the mechanism(s) involved in this reduction and explore the lifetime benefits in high-risk cohorts are paramount.

Estimated glucose disposal rate, a novel biomarker for insulin sensitivity, predicts risk for incident heart failure in patients with type 2 diabetes

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Singapore National Medical Research Council Singapore Khoo Teck Puat Hospital STAR grant Background Although a low insulin sensitivity (insulin resistance) has been considered as one of the drivers for heart failure, data on the role of insulin resistance in incident HF in diabetic population are still scarce. Estimated glucose disposal rate (eGDR), a novel biomarker for insulin sensitivity derived from three clinically available variables, was developed in type 1 diabetes and recently validated in type 2 diabetes by the gold standard euglycaemic hyperinsulinaemic clamp. We hypothesize that a high level of eGDR is associated with a low risk for incident HF in patients with type 2 diabetes. Objective In this prospective cohort study, we aim to examine whether eGDR, the novel biomarker for insulin sensitivity in diabetic population, predicts risk for incident HF in individuals with type 2 diabetes. Methods 1685 outpatients with type 2 diabetes were recruited from a regional hospital and a primary care centre from January 2011 to March 2014. Incident HF was defined by European Society of Cardiology 2016 criteria (NT-proBNP &amp;gt; 125 pg/ml with echocardiographic evidence). eGDR (mg/kg/min) was calculated as: 21.158 - (0.09 × waist circumference in cm)- (3.407 × hypertension, 1=yes 0=no) - (0.551 × HbA1c%). A higher eGDR indicates a high insulin sensitivity. The association of baseline eGDR with risk for incident HF was examined by survival analysis. Results The average age of participants was 57 (SD 11) years old, diabetes duration 11 (SD 9) years, Chinese 52.4%, Malay 21.2% and Asian Indian 26.4. During 6.6 (SD 1.5) years follow-up (11092 patient-years), 155 incident HF events (88 HFpEF with LVEF &amp;gt; 50%, 67 HFrEF with LVEF &amp;lt;= 50%) were identified (crude incident rate 1.4, 95% CI 1.2-1.6, per 100 patient-years). Cox regression model suggested that, as compared to the lowest tertile, participants with eGDR in the highest tertile had 88% lower risk (unadjusted HR 0.12, 95% CI 0.06-0.22) for development of incident HF. The association was only moderately attenuated (adjusted HR 0.32, 95% CI 0.16-0.63) after adjustment for demographic (age, sex, ethnicity) and cardio-renal variables (smoking, body mass index, diabetes duration, resting heart rate, lipid profile, kidney filtration function and albuminuria). As a continuous variable, one SD increment in eGDR was associated with 57% lower risk for HF after adjustment for multiple clinical risk factors (adjusted HR 0.43, 95% CI 0.31-0.59). In the fully adjusted model, a higher level of eGDR was significantly associated with a lower risk for both HFrEF and HFpEF (adjusted HR 0.40, 95% CI 0.23-0.67, and 0.40, 95% CI 0.26-0.63, respectively). Conclusion A higher level of eGDR is strongly associated with a lower risk for incident HF in patients with type 2 diabetes, suggesting that insulin resistance may play an important role in pathogenesis of HF. This simple novel biomarker may be explored to stratify risk for incident HF in individuals with type 2 diabetes.

Development and validation of prediction models for incident atrial fibrillation in heart failure

ObjectivesAccurate prediction of heart failure (HF) patients at high risk of atrial fibrillation (AF) represents a potentially valuable tool to inform shared decision making. No validated prediction model for AF...

Abstract 15878: Relationship Between Cardiac Biomarkers and Echocardiographic Parameters of Cardiac Structure in Patients With Diabetes

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/m 2 , 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.

Machine Learning Risk Prediction for Incident HeartFailure in Patients With Atrial Fibrillation.

Atrial fibrillation (AF) increases the risk of heart failure (HF); however, little focus is placed on the risk stratification for, and prevention of, incident HF in patients with AF. This study aimed to construct and validate a machine learning (ML) prediction model for HF hospitalization in patients with AF. The Fushimi AF Registry is a community-based prospective survey of patients with AF in Fushimi-ku, Kyoto, Japan. We divided the data set of the registry into derivation (n=2,383) and validation (n=2,011) cohorts. An ML model was built to predict the incidence of HF hospitalization using the derivation cohort, and predictive ability was examined using the validation cohort. HF hospitalization occurred in 606 patients (14%) during a median follow-up period of 4.4 years in the entire registry. Data of transthoracic echocardiography and biomarkers were frequently nominated as important predictive variables across all 6 ML models. The ML model based on a random forest algorithm using 7 variables (age, history of HF, creatinine clearance, cardiothoracic ratio on x-ray, left ventricular [LV] ejection fraction, LV end-systolic diameter, and LV asynergy) had high prediction performance (area under the receiver operating characteristics curve [AUC]: 0.75) and was significantly superior to the Framingham HF risk model (AUC: 0.67; P< 0.001). Based on Kaplan-Meier curves, the ML model could stratify the risk of HF hospitalization during the follow-up period (log-rank; P< 0.001). The ML model revealed important predictors and helped us to stratify the risk of HF, providing opportunities for the prevention of HF in patients with AF.