Heart Failure Class Research Articles

First-phase ejection fraction to predict adverse outcomes in patients with heart failure

BackgroundFirst-phase ejection fraction (EF1) is a novel measurement of early left ventricular systolic dysfunction. We investigate its prognostic value in patients with heart failure (HF). Methods and resultsPatients with HF were prospectively enrolled from July 2019 to September 2021. A total of 228 patients were included in the final analysis. The primary endpoint was the composite of all-cause mortality or rehospitalization for HF, which occurred in 74 patients (32.46%). EF1 as well as other parameters for left ventricular function were measured in echocardiography. Time-dependent ROC showed the cutoff value of EF1 was 18.55%. Kaplan–Meier analysis indicated a higher rate of adverse events in the lower EF1 group (EF1 ≤ 18.55%) (Log-rank test P < 0.001). Cox regression analyses showed EF1 was an independent predictor with adverse events as a continuous variable (Cox model 1: per 1% change in EF1: HR = 0.92, 95%CI: 0.87–0.97, P < 0.001), as well as a categorical variable (Cox model 2: EF1 > 18.55%: HR = 0.21, 95%CI: 0.08–0.53, P < 0.001) after adjustment for hypertension, coronary artery disease (CAD), Log10 (NT-proBNP), eGFR, E/e’ and loop diuretics. Restricted cubic splines revealed a linear association between EF1 levels and the incidence of adverse events (P for non-linearity = 0.145). The subgroup analyses showed the predictive ability of elevated EF1 on the decreased risk of adverse events did not change substantially stratified by HF classification, age, CAD and hypertension. ConclusionEF1, as a novel measurement of early systolic function, is a promising predictor of adverse events among HF patients. EF1 might be considered a new measurement for risk stratification of HF.

Does sacubitril/valsartan work in children with heart failure?—a pilot study

BackgroundSacubitril/valsartan is an angiotensin receptor neprilysin antagonist (ARNI) approved for adult heart failure (HF). Its safety and efficacy in pediatric HF patients with cardiomyopathy or congenital heart disease are poorly understood. A pilot study was conducted to assess the clinical response, efficacy and safety of sacubitril/valsartan in this population at a tertiary care hospital in China.MethodsClinical parameters of patients who received sacubitril/valsartan from January 2019 to March 2023 were retrospectively collected and analyzed. Children over 1 month with a left ventricular ejection fraction (LVEF) &amp;lt;45% were included. Clinical efficacy was evaluated by echocardiographic LVEF, N-terminal pro-brain natriuretic peptide (NT-proBNP), New York Heart Association (NYHA) HF classification, HF re-admission, and death or transplantation. The initial dose was either 0.2 mg/kg bid or 0.4 mg/kg bid, with a target dose of 2.3 mg/kg bid or 3.1 mg/kg bid.ResultsForty-five patients (60% male) with a median age of 7.86 years were enrolled. Among them, 23 had congenital heart disease and 22 had cardiomyopathies. The median maintenance dose was 0.76 mg/kg. The primary endpoint of LVEF up to 45% was reached by 24 patients (53.3%). The median NT-proBNP was significantly decreased from 5,501.5 pg/ml to 2,241.5 pg/ml (P &amp;lt; 0.001), more in congenital heart disease than in cardiomyopathies (P = 0.032). The NYHA HF class was improved or remained stable in 42 cases (93.3%). During a median follow-up of 1.23 years, 13 patients (28.9%) were re-hospitalized due to HF, and 9 patients (20%) died or underwent transplantation. Hypotension was the main adverse event, occurring in 8 patients.ConclusionsSacubitril/valsartan may be effective in children with HF, but its safety and outcomes may differ depending on the etiology and anatomy of HF. Early post-operative congenital heart disease patients had less tolerance, more hypotension but better recovery and outcomes, while mid- and late- post-operative congenital heart disease patients and cardiomyopathy patients had less side effects but poorer clinical outcomes.

Time-domain heart rate variability features for automatic congestive heart failure prediction.

Heart failure is a serious condition that often goes undiagnosed in primary care due to the lack of reliable diagnostic tools and the similarity of its symptoms with other diseases. Non-invasive monitoring of heart rate variability (HRV), which reflects the activity of the autonomic nervous system, could offer a novel and accurate way to detect and manage heart failure patients. This study aimed to assess the feasibility of using machine learning techniques on HRV data as a non-invasive biomarker to classify healthy adults and those with heart failure. We used digitized electrocardiogram recordings from 54 adults with normal sinus rhythm and 44 adults categorized into New York Heart Association classes 1, 2, and 3, suffering from congestive heart failure. All recordings were sourced from the PhysioNet database. Following data pre-processing, we performed time-domain HRV analysis on all individual recordings, including root mean square of the successive difference in adjacent RR interval (RRi) (RMSSD), the standard deviation of RRi (SDNN, the NN stands for natural or sinus intervals), the standard deviation of the successive differences between successive RRi (SDSD), the number or percentage of RRi longer than 50ms (NN50 and pNN50), and the average value of RRi [mean RR interval (mRRi)]. In our experimental classification performance evaluation, on the computed HRV parameters, we optimized hyperparameters and performed five-fold cross-validation using four machine learning classification algorithms: support vector machine, k-nearest neighbour (KNN), naïve Bayes, and decision tree (DT). We evaluated the prediction accuracy of these models using performance criteria, namely, precision, recall, specificity, F1 score, and overall accuracy. For added insight, we also presented receiver operating characteristic (ROC) plots and area under the ROC curve (AUC) values. The overall best performance accuracy of 77% was achieved when KNN and DT were trained on computed HRV parameters with a 5min time window. KNN obtained an AUC of 0.77, while DT attained 0.78. Additionally, in the classification of severe congestive heart failure, KNN and DT had the best accuracy of 91%, with KNN achieving an AUC of 0.88 and DT obtaining 0.92. The results show that HRV can accurately predict severe congestive heart failure. The findings of this study could inform the use of machine learning approaches on non-invasive HRV, to screen congestive heart failure individuals in primary care.

Two is better than one: the double diffusion technique in classifying heart failure.

Heart failure (HF) is a chronic condition in which the heart does not pump enough blood to meet the body's demands. Diffusing capacity of the lung for nitric oxide (DLNO) and carbon monoxide (DLCO) may be used to classify patients with HF, as DLNO and DLCO are lung function measurements that reflect pulmonary gas exchange. Our objectives were to determine 1) if DLNO added to DLCO testing predicts HF better than DLCO alone and 2) whether the binary classification of HF is better when DLNO z-scores are combined with DLCO z-scores than using DLCO z-scores alone. This was a retrospective secondary data analysis in 140 New York Heart Association Class II HF patients (ejection fraction <40%) and 50 patients without HF. z-scores for DLNO, DLCO and DLNO+DLCO were created from reference equations from three articles. The model with the lowest Bayesian Information Criterion was the best predictive model. Binary HF classification was evaluated with the Matthews Correlation Coefficient (MCC). The top two of 12 models were combined z-score models. The highest MCC (0.51) was from combined z-score models. At most, only 32% of the variance in the odds of having HF was explained by combined z-scores. Combined z-scores explained 32% of the variation in the likelihood of an individual having HF, which was higher than models using DLNO or DLCO z-scores alone. Combined z-score models had a moderate ability to classify patients with HF. We recommend using the NO-CO double diffusion technique to assess gas exchange impairment in those suspected of HF.

Surgical management of breast fat necrosis: Multi-institutional data analysis of early outcomes and risk factors for complications

BackgroundBreast fat necrosis (BFN) is a non-cancerous condition affecting the adipose tissue. Despite incidence rates of up to 25% after breast surgery, little is known about risk factors and postoperative outcomes following the surgical treatment of BFN. MethodsThe National Surgical Quality Improvement Program of the American College of Surgeons (2008–2021) was queried to identify female patients diagnosed with and surgically treated for BFN. Outcomes of interest included 30-day surgical and medical complications, reoperation, and readmission. We performed confounder-adjusted multivariable analyses to determine risk factors. ResultsThe study population included 1179 female patients (mean age: 55.8 ± 13.8 years), of whom 96% (n = 1130) underwent direct excision and 4.2% (n = 49) received debridement of necrotic tissue. The majority of cases were operated on by general surgeons (n = 867; 74%) in the outpatient setting (n = 1107; 94%). Overall, 74 patients (6.3%) experienced postoperative adverse events, most of which were surgical complications (n = 43; 3.7%). Twenty-one (1.8%) women had to return to operating room, while readmission was reported in 18 (1.5%) cases. Adverse events were significantly more likely to occur in patients with chronic heart failure (p = 0.002) and higher wound classes (p = 0.033). ConclusionComplication rates following the surgical management of BFN were found to be relatively high and seen to correlate with the setting. We identified chronic heart failure and wound contamination as risk factors for complication occurrence. These evidence-based insights may sensitize surgeons to critically balance patients’ eligibility for BFN surgery and refine perioperative algorithms.

FEATURES OF THE MORPHO-FUNCTIONAL MYOCARDIUM STATE AND RELATIONSHIP WITH GALECTIN-3 IN PATIENTS WITH CHRONIC HEART FAILURE OF ISCHEMIC ORIGIN ON THE BACKGROUND OF METABOLIC PATHOLOGY

The aim. To evaluate the presence and nature of changes in the morpho-functional state of the myocardium in patients with coronary heart disease (CHD) with concomitant type 2 diabetes mellitus (T2DM) and obesity, depending on the functional class (FC) of chronic heart failure (CHF) and the relationship with the concentration of galectin-3 in blood serum.&#x0D; Materials and methods. The study involved 75 patients with CHD with concomitant metabolic diseases such as T2DM and obesity, who were treated in the cardiology department of the State Clinical Hospital No. 27. Patients were divided into groups according to the FC of CHF. Group 1 included 30 patients with CHF FC II, group 2 – 24 patients with CHF FC III, group 3 – 21 patients with CHF FC IV.&#x0D; Results. In patients with СHD and metabolic disorders with CHF FC III, the levels of end-systolic dimension (ESD) and end-diastolic dimension (EDD) were higher by 16.3 % and 17.9 %, respectively, compared with FC II, end-systolic volume (ESV) and end-diastolic volume (EDV) also increased significantly in patients of this cohort with FC III compared with CHF FC II by 35.8 % and 16.5 %, respectively. Significantly increased ESV, EDV by 42.9 % and 37.8 %, respectively, as well as the size of the left atrium by 14.3 % in patients of the study group who had CHF FC IV compared with FC III. The ejection fraction (EF) index decreased in patients of this cohort with CHF FC IV by 14.4 % compared with FC III. The size of the right ventricle was larger by 10.8 % in CHF FC IV than in FC III in patients with CHD on the background of comorbid metabolic pathology. Indicators of the thickness of the LV posterior wall, LV relative wall thickness and intraventricular septum were lower in patients with FC IV compared with FC II, left ventricle mass (LVM) and left ventricle mass index (LVMI) increased by 32 % and 33 %, respectively. Сomparing the levels of Ea/Es in patients with CHF FC II and IV in СHD with concomitant T2DM and obesity, a significant increase in this indicator was found in FC IV (p&lt;0.05). The level of galectin-3 in patients with CHF FC III and IV of ischemic origin against the background of concomitant metabolic disorders was higher than in patients with FC II. Сomparing the concentration of galectin-3 in patients with CHF FC III and IV in patients with CHD with comorbid metabolic pathology, significantly higher levels were found in FC IV (p&lt;0.05). The study of the relationship between the fibrosis factor galectin-3 and cardiohemodynamic parameters revealed probable links, namely direct links between galectinemia and ESV (r=0.52; p&lt;0.05), EDV (r=0.58; p&lt;0.05), Еа/Es (r=0.51; p&lt;0.05).&#x0D; Conclusions. The growth of the functional class of chronic heart failure is accompanied by dilatation of the left cavities of the heart, a decrease in the inotropic function of the left ventricle, an increase in myocardial-arterial stiffness, and an increase in the levels of the galectin-3 fibrosis factor in the studied patients.

Radiomics of pericardial fat: a new frontier in heart failure discrimination and prediction

ObjectivesTo use pericardial adipose tissue (PAT) radiomics phenotyping to differentiate existing and predict future heart failure (HF) cases in the UK Biobank.MethodsPAT segmentations were derived from cardiovascular magnetic resonance (CMR) studies using an automated quality-controlled model to define the region-of-interest for radiomics analysis. Prevalent (present at time of imaging) and incident (first occurrence after imaging) HF were ascertained using health record linkage. We created balanced cohorts of non-HF individuals for comparison. PyRadiomics was utilised to extract 104 radiomics features, of which 28 were chosen after excluding highly correlated ones (0.8). These features, plus sex and age, served as predictors in binary classification models trained separately to detect (1) prevalent and (2) incident HF. We tested seven modeling methods using tenfold nested cross-validation and examined feature importance with explainability methods.ResultsWe studied 1204 participants in total, 297 participants with prevalent (60 ± 7 years, 21% female) and 305 with incident (61 ± 6 years, 32% female) HF, and an equal number of non-HF comparators. We achieved good discriminative performance for both prevalent (voting classifier; AUC: 0.76; F1 score: 0.70) and incident (light gradient boosting machine: AUC: 0.74; F1 score: 0.68) HF. Our radiomics models showed marginally better performance compared to PAT area alone.Increased PAT size (maximum 2D diameter in a given column or slice) and texture heterogeneity (sum entropy) were important features for prevalent and incident HF classification models.ConclusionsThe amount and character of PAT discriminate individuals with prevalent HF and predict incidence of future HF.Clinical relevance statementThis study presents an innovative application of pericardial adipose tissue (PAT) radiomics phenotyping as a predictive tool for heart failure (HF), a major public health concern. By leveraging advanced machine learning methods, the research uncovers that the quantity and characteristics of PAT can be used to identify existing cases of HF and predict future occurrences. The enhanced performance of these radiomics models over PAT area alone supports the potential for better personalised care through earlier detection and prevention of HF.Key Points•PAT radiomics applied to CMR was used for the first time to derive binary machine learning classifiers to develop models for discrimination of prevalence and prediction of incident heart failure.•Models using PAT area provided acceptable discrimination between cases of prevalent or incident heart failure and comparator groups.•An increased PAT volume (increased diameter using shape features) and greater texture heterogeneity captured by radiomics texture features (increased sum entropy) can be used as an additional classifier marker for heart failure.

Left ventricular ejection fraction digit bias and reclassification of heart failure with mildly reduced vs reduced ejection fraction based on the 2021 definition and classification of heart failure

Aims were to evaluate (1) reclassification of patients from heart failure with mildly reduced (HFmrEF) to reduced (HFrEF) ejection fraction when an EF=40% was considered as HFrEF, (2) role of EF digit bias, ie, EF reporting favouring 5% increments; (3) outcomes in relation to missing and biased EF reports, in a large multinational HF registry. Of 25,154 patients in the European Society of Cardiology (ESC) HF Long-Term registry, 17% had missing EF and of those with available EF, 24% had HFpEF (EF≥50%), 21% HFmrEF (40%-49%) and 55% HFrEF (<40%) according to the 2016 ESC guidelines´ classification. EF was "exactly" 40% in 7%, leading to reclassifying 34% of the HFmrEF population defined as EF=40% to 49% to HFrEF when applying the 2021 ESC Guidelines classification (14% had HFmrEF as EF=41% to 49% and 62% had HFrEF as EF≤40%). EF was reported as a value ending with 0 or 5 in ∼37% of the population. Such potential digit bias was associated with more missing values for other characteristics and higher risk of all-cause death and HF hospitalization. Patients with missing EF had higher risk of all-cause and CV mortality, and HF hospitalization compared to those with recorded EF. Many patients had reported EF=40%. This led to substantial reclassification of EF from old HFmrEF (40%-49%) to new HFrEF (≤40%). There was considerable digit bias in EF reporting and missing EF reporting, which appeared to occur not at random and may reflect less rigorous overall care and worse outcomes.

Respiratory Muscle Strength and Quality of Life in Patients With Heart Failure and Their Main Correlated Factors: A Cross-sectional Study.

Heart failure may cause peripheral and respiratory muscle alterations, dyspnea, fatigue, and exercise intolerance, worsening the quality of life of patients. The aims of this study were to analyze respiratory muscle strength and quality of life of patients with heart failure and correlate them with clinical variables and functional classification. This cross-sectional study involved patients with heart failure. A manovacuometer assessed maximum inspiratory and expiratory pressures, and quality of life was assessed using the Minnesota Living with Heart Failure Questionnaire. Functional classification was categorized according to the New York Heart Association (NYHA) class in I, II, III, or IV. We included 60 patients (66.7% male) with a mean age of 62.0 years and mean left ventricular ejection fraction of 42.0%. Maximum inspiratory pressure and maximum expiratory pressure were close to normal (>70% of predicted) in most patients; however, a subgroup composed mostly of patients with dilated heart failure and NYHA class III (n = 21) presented low maximum inspiratory pressure values (59.2%; 95% confidence interval, 55.7%-62.8%). The mean total score of the Minnesota Living with Heart Failure Questionnaire was 44.4 points, being negatively correlated with left ventricular ejection fraction ( r = -0.29, P = .02). Patients with NYHA class III and disease duration longer than 120 months presented higher total ( P < .01) and physical dimension scores. Most patients had respiratory muscle strength close to normal; however, those with dilated heart failure and NYHA class III presented low maximum inspiratory pressure values. Quality of life was moderately compromised, mainly because of long disease duration, NYHA class III, and low left ventricular ejection fraction.

Effect of a restrictive vs. liberal blood transfusion strategy among patients with acute myocardial infarction and anemia according to heart failure. A subgroup analysis of the REALITY trial

Abstract Background/Introduction The optimal Red Blood Cell (RBC) transfusion strategy in patients with acute myocardial infarction (MI) and anemia remains debated. In REALITY, the largest randomized trial to date in this population (n=666), a restrictive compared with a liberal transfusion strategy resulted in a noninferior rate of major adverse cardiovascular events (MACE; composite of all-cause death, stroke, recurrent myocardial infarction, or emergency revascularization prompted by ischemia) at 30 days, but did not achieve non-inferiority at 1 year. One of the main concerns with RBC transfusion is the risk of fluid overload and acute heart failure (HF). Therefore, the balance of benefit and risk of transfusions strategies may differ between patients with and without heart failure. Purpose We aimed to evaluate the potential interaction between HF and RBC transfusion on outcomes in REALITY. Methods HF was defined as either a history of heart failure or Killip class &amp;gt; 1 at randomization (data available for 658 patients). All events until day 30, including HF, were adjudicated by a Critical Event Committee blinded to the transfusion arm and hemoglobin levels. The primary clinical outcome was MACE at 30 days. Secondary endpoints included MACE at one year, individual components of MACE and new onset of heart failure at 30 days and 1 year. Results Among 658 patients, 311 (47.3 %) had HF. HF patients had a higher rate of MACE and a higher rate of new HF than patients without HF at 30 day and at 1 year (Fig 1). There was no interaction between HF and the effect of randomized assignment on the primary outcome or on new HF. In contrast, a liberal strategy was associated with increased all-cause death at 30 days and at 1 year in patients with HF but not in pts without HF (interaction p = 0.0088 and p = 0.049 respectively, Fig 1). Conclusion(s) Heart failure is frequent in MI patients with anemia (nearly half of the patients) and is associated with higher risks of MACE and of HF. While no interaction was observed between HF and transfusion strategies on the primary outcome of MACE, a liberal transfusion strategy was associated with higher all-cause mortality than a restrictive strategy both at 30-days and 1 year. The mechanism of this interaction deserves further investigation.

Clinician-reported EHRA and NYHA scores only moderately reflect patient-reported quality of life in atrial fibrillation and heart failure

Abstract Background In the management of heart failure (HF) and atrial fibrillation (AF), treatment decisions are often made based on the amount and severity of symptoms. It is expected that treating the patients’ symptoms positively impacts the patients’ burden of disease. Clinician-reported symptoms are expected to agree with patient-perceived symptoms. However, patients may value (the impact of) symptoms on their quality of life (QoL) differently to clinicians. Purpose This study aimed to gain insights on how patients perceive the impact of AF and HF on QoL, compared to how clinicians perceive (the impact of) patients’ symptoms. To this end, the clinician-reported severity of symptoms was assessed in relationship with patient-reported QoL within 12 months after diagnosis. Methods Newly diagnosed AF and HF patients were included between November 2014 and January 2023 in four non-academic hospitals situated in the Southeast of the Netherlands. During routine visits to AF- and HF-outpatient clinics trained nurses collected information on among others symptoms and QoL at diagnosis and 12 months of follow-up. Severity of symptoms was determined through a clinician-reported NYHA classification for HF and EHRA score for AF. QoL was assessed through the use of the CareQol questionnaire for HF and AFEQT questionnaire for AF. Medians and interquartile-ranges (IQR) were used to assess symptoms and QoL at diagnosis and 12 months of follow-up. In addition, one-way ANOVA’s were employed to assess difference in symptoms and QoL over a period of 12 months. Results In total, 890 AF patients and 292 HF patients were available for analysis with complete 12 month follow-up information. A moderate correlation was observed between EHRA score and AFEQT at diagnosis and 12 months follow-up (Pearson’s R -0.357 and -0.302, respectively). A comparable correlation was observed between NYHA classification and CareQoL (Pearson’s R 0.290 and 0.491). A clinician-reported improvement in AF or HF symptoms from diagnosis to 12 months follow-up was associated with a patient-reported improvement in QoL (AF: F(762,3) = 25.86, p &amp;lt;.001, and HF: F(256,2) = 8.87, p &amp;lt;.001). When clinicians reported no change or worsening symptoms, no significant changes in QoL were reported by patients. Furthermore, a large variation was observed in patient-reported quality of life, even if clinicians reported no symptoms (i.e. EHRA I / NYHA I) for both AF and HF (Median (IQR); 84.3 (25.1) and 2.49 (1.05), respectively) (Figure 1 &amp; 2). Conclusion In this study only a moderate correlation was observed between clinician-reported symptoms and patient-reported quality of life with large individual variation in patient reported QoL. A clinician-reported worsening of symptoms was not always reflected in a decrease of patients’ QoL. The clinician-reported EHRA and NYHA classification does often not accurately reflect the burden of disease as perceived by patients.

Abstract 12291: Impact of History of Mental Health Disorder on In-Hospital Mortality in Patients With Heart Failure. A Population-Based Cohort Study

Introduction: Mental health disorders are associated with lower life expectancy and patients with mental disorders are at an increased risk of heart failure. Data on the prognostic impact of mental disorders on heart failure outcomes is limited and inconclusive. Hypothesis: Mental health disorders are associated with increased risk of in-hospital mortality in patients with heart failure. Methods: The study population were patients aged ≥18 years in acute care hospitals with heart failure as principal diagnosis in Texas for years 2016 through 2021. Three prespecified models were applied to estimate the association between mental disorders and in-hospital mortality. Multilevel, multivariable logistic regression with propensity adjustment was the primary analysis approach with propensity score matching and multivariable logistic regression without propensity adjustment applied as alternative analyses. Additional analyses were completed for patient subgroups, categories of mental disorders, and classifications of heart failures. Results: Out of 513,565 heart failure hospitalizations, 103,675 (20.2%) had mental disorders. Heart failure hospitalizations with vs without mental disorders were more commonly female (61.3% vs 46.0%), white (55.3% vs 46.9%), and obese (31.6% vs 26.4%), but had less frequent need for mechanical ventilation (1.8% vs 2.1%); p &lt; 0.0001 for each. Unadjusted in-hospital mortality among heart failure hospitalizations with and without mental disorders was 1.7% vs 2.2%. On adjusted analyses, mental disorders remained associated with lower odds of in-hospital mortality (adjusted odds ratio 0.8650 [95% CI 0.8149-0.9183]). The results were similar for the alternative modeling approaches, subgroup analyses, and classifications of heart failure. Conclusion: Mental disorders were associated with substantially lower risk of in-hospital mortality for patients with a principal diagnosis of heart failure.

Abstract 12069: Impact of Atrial Fibrillation on Outcomes in Patients With Heart Failure With Reduced, Mildly Reduced and Preserved Ejection Fraction. A Systematic Review and Meta-Analysis of Published Studies

Background: Atrial fibrillation (AF) is highly prevalent in patients with heart failure (HF), however the difference in outcomes between the HF sub-types is not well known. Contemporary classification of HF categorizes it into HF with reduced ejection fraction (HFrEF), HF with mildly reduced ejection fraction (HFmrEF), and HF with preserved ejection fraction (HFpEF). With the new designation of HFmrEF, there have been studies researching the risk profile of AF in the three HF categories, however there is not yet a unifying statement on these data. Aim: Systematic review and meta-analysis aimed to determine if there are any significant differences in AF-associated all-cause mortality (primary endpoint), heart failure hospitalizations, cardiovascular mortality, and stroke (secondary endpoints) between HFrEF, HFmrEF, and HFpEF. Methods: A systematic search of PubMed, EMBASE, and Cochrane Library databases until February 28 th , 2023, identified studies reporting clinical outcomes linked to AF by HF category status. Data were combined using D+L random effects model. Results: The review included 21 studies comprising 238,107 patients. Pooled AF prevalence: 32% in HFrEF, 38% in HFmrEF, and 43% in HFpEF. AF was associated with a higher risk of all-cause mortality in HFmrEF and HFpEF only (Figure for pooled hazard ratio (HR) and 95% CI). AF associated with a higher risk of HF hospitalizations, in the total population (HR=1.29, 95% CI=1.14-1.46), HFmrEF (HR=1.64, 95% CI=1.20-2.24), and HFpEF (HR=1.46, 95% CI=1.17-1.83), but not HFrEF (HR=1.01, 95% CI=0.87-1.18). AF was only associated with cardiovascular mortality in the HFpEF subcategory but was associated with stroke in all three HF subtypes. Conclusion: AF was associated with a higher risk of all-cause mortality and heart failure hospitalization in HFmrEF and HFpEF only. As treatment guidelines for AF in HFmrEF are limited, the benefit of treatments to control AF in this subgroup should be further investigated.

Abstract 16662: Factors Associated With Repeated Emergency Department Visits Among Symptomatic Patients With Heart Failure

Heart failure (HF) is a prevalent cause of emergency department (ED) visits among adults. However, there is limited understanding of the characteristics of patients with HF who frequently utilize the ED for symptom management. Aim: To describe factors associated with ED revisits among symptomatic patients with chronic HF. Methods: We identified 1,472,083 adults (age ≥ 18 years) with HF who had no history of left ventricular assist device or heart transplantation between January 2010 and March 2020 from the TriNetX Research Network, which included 47 US healthcare organizations. In this retrospective observational study, 24,070 patients presenting with dyspnea and receiving intravenous (IV) Furosemide at the ED were followed up for 1 year from the index ED visit. ED revisits related to the treatment of dyspnea with IV diuretics were tracked. Factors associated with these ED revisits were identified using multivariate Cox regression analysis. Results: A total of 3,574 ED revisits were observed from 2,559 patients (10.6% of the sample, mean age 63 years, 51% men, 39% White, 62% Non-Hispanic). The ED revisit rates were 52, 96, 125, and 148 visits per 1,000 persons within 1, 3, 6, and 12 months, respectively. The median time to the first ED revisit for symptom management with IV diuretics was 65 days (range 2-364 days). In the Cox model, younger patients (&lt; 65 years) had a higher risk of ED revisits compared to older patients (HR 1.65, 95% CI 1.50-1.82, p&lt;0.001). Men had a higher risk of ED revisits compared to women (HR 1.12, 95% CI 1.02-1.23, p=0.02). Black patients had a higher risk of ED revisits compared to other races (HR 1.36, 95% CI 1.20-1.53, p&lt;0.001). Patients with HFrEF (e.g., ICD-10 I50.2) had a higher risk of ED revisits compared to those with congestive HF (e.g., ICD-10 I50 without HF type information) (HR 1.25, 95% CI 1.12-1.40, p &lt; 0.001). Patients diagnosed with HF more than 1 year prior to the index ED visit had a higher risk of ED revisits compared to those diagnosed within 1 year (HR 1.31, 95% CI 1.19-1.44, p &lt; 0.001). Conclusions: Younger age, male gender, Black race, HFrEF classification, and longer duration of HF were associated with ED revisits among symptomatic adults with HF. To reduce repeated ED visits, targeted interventions for high-risk patients are essential.

Abstract 15130: Sweat Lactate Sensor for Detecting Anaerobic Threshold in Paitents With Heart Failure: Prospective Clinical Trial (LacS-001)

Background: Exercise is essential for good health and prevention of exacerbations in patients with heart failure (HF). To determine ventilatory threshold (VT); a key to detect appropriate exercise intensity, our team developed a small, easy-to-use device for non-invasive, simple, and real-time visualization of sweat lactate dynamics during exercise. Clinical Question: Could our sweat lactate sensor (GI-1) provide a safe and accurate means of detecting VT in patients with HF in a clinical setting? Aim: This prospective clinical trial (clinical trial; jRCT2032220057) was designed to investigate the safety of a sweat lactate sensor (GI-1) and the correlation between the lactate threshold in sweat (sLT), as assessed using our sweat lactate sensor, and the VT. Methods: We recruited 50 patients with HF and New York Heart Association functional classification I-II, with a median age of 63.5 years (interquartile range: 58.0-72.0 years). Incremental exercise tests were conducted and changes in sweat lactate levels were monitored simultaneously. The sLT was defined as the first steep increase in lactate levels from baseline as seen on graphical plots and was evaluated by three independent investigators. The primary outcome measures were a correlation coefficient of 0.6 or greater between sLT and VT, the similarities as assessed by the Bland-Altman analysis, and the standard deviation of the difference between the two within 15 W. Results: Among the 50 patients, a correlation coefficient of 0.651 (95% confidence interval, 0.391-0.815) was achieved in 32 cases. The difference between the sLT and VT was -4.9±15.0 W, and no comparative error was noted in the Bland-Altman plot. No device-related adverse events were reported among the registered patients. Conclusions: Our sweat lactate sensor, GL-1, provides a safe and accurate means of detecting VT in patients with HF in a clinical setting, thereby offering valuable additional information for treatment.

Abstract 12533: Heart Failure Diagnostic Classification Criteria in Hospitalized Patients Are Associated With Increased Mortality Risk: The Atherosclerosis Risk in Communities (ARIC) Study

Introduction: Multiple diagnostic HF classification have been used to identify heart failure (HF) events. Whether these classification criteria can be used for estimating prognosis is unknown. Research Question: This study compares multiple research-derived HF classification criteria for predicting mortality in the ARIC study cohort with validated hospitalized acute decompensated heart failure (ADHF) events. Methods: There were 1,954 ARIC cohort members with hospitalized HF events from 2005-2019, validated as ADHF by ARIC study classification/adjudication. These HF events were also classified as HF present/absent at the time of hospitalization by other HF classification criteria - Framingham, Modified Boston, NHANES, and Gothenburg. Hazard ratios (HRs) for all-cause mortality at 30 days, 1 year, and 5 years were calculated using logistic regression for all included HF classification criteria compared to ARIC, stratified by ejection fraction (EF), and adjusted for demographics and comorbidities. Results: For all ADHF events, Framingham, NHANES, and Gothenburg were prognostic for survival, but not modified Boston criteria (Table). ADHF patients who were also classified as HF by Framingham criteria had a 30% or more increased mortality at 30-day, 1-year, and 5-years regardless of EF, compared to those who were not classified as HF by Framingham (p&lt;0.05). Framingham criteria were prognostic for 30-day survival for those with HFrEF, and also for 1-year and 5-year survival for those with HFpEF. Conclusion: The presence of HF as defined using different published criteria is associated with elevated risk of all-cause mortality. To our knowledge, this is a novel study comparing multiple research-derived HF classification criteria for clinical prognostication of mortality in ADHF. More studies are needed to assess the utility of these HF classification criteria for prognostication for HF morbidity and rehospitalization and by HF type.

Automatic classification of heart failure based on Cine-CMR images.

Heart failure (HF) is a serious and complex syndrome with a high mortality rate. In clinical diagnosis, the correct classification of HF is helpful. In our previous work, we proposed a self-supervised learning framework of HF classification (SSLHF) on cine cardiac magnetic resonance images (Cine-CMR). However, this method lacks the integration of three dimensions of spatial information and temporal information. Thus, this study aims at proposing an automatic 4D HF classification algorithm. To construct a 4D classification model, we proposed an extensional framework called 4D-SSLHF. It mainly consists of self-supervised image restoration and HF classification. The image restoration proxy task utilizes three image transformation methods to enhance the exploration of spatial and temporal information in the Cine-CMR. In the classification task, we proposed a Siamese Conv-LSTM network by combining the Siamese network and bi-directional Conv-LSTM to integrate the features of the four dimensions simultaneously. Experimental results on 184 patients from Shanghai Chest Hospital achieved an AUC of 0.8794 and an ACC of 0.8402 in the five-fold cross-validation. Compared with our previous work, the improvements in AUC and ACC were 2.89 % and 1.94 %, respectively. In this study, we proposed a novel self-supervised learning framework named 4D-SSLHF for HF classification based on Cine-CMR. The proposed 4D-SSLHF can mine 3D spatial information and temporal information in Cine-CMR images well and accurately classify different categories of HF. The good classification results show our method's potential to assist physicians in choosing personalized treatment.

9 The Relationship Between Depressive Mood and Mini Mental Status Examination Scores in Individuals with Heart Failure

Objective:Heart failure occurs when the heart is unable to support a flow of blood that meets the body’s needs, ultimately resulting in decreased oxygenation throughout the body— including the brain. Results of previous research suggest that individuals with heart failure exhibit both localized and diffuse neuropsychological deficits. The aims of this study are to meta-analytically examine a) the performance of participants with heart-failure and healthy controls on the Mini Mental State Examination (MMSE), a neuropsychological test of general cognition, and b) the role of depressive mood as a potential moderator of performance on the MMSE in these participants.Participants and Methods:Two researchers independently searched eight databases for articles that examined the neuropsychological functioning of patients with heart failure.Inclusion criteria identified studies that had a heart failure group with a comparable control group and reported on neuropsychological assessment for both groups. Studies were excluded if a heart failure group had any other type of major organ failure or if the comparison was between different classes of heart failure rather than between a heart failure group and healthy controls.Results:A meta-analysis using a random-effects model revealed a statistically significant and large effect size estimate (g= 0.727, p &lt;.001) CI [.331, 1.123]. The heterogeneity was found to be statistically significant and in the large range, I2 = 83.027%, tau2 = .155, p &lt; .001. A meta-regression analyzing the relationship between depressive mood and MMSE effect size estimates was statistically significant, Q residual = 8.715, df = 3, p = .03.Conclusions:This study is the first to examine the relationship between depressive mood and general cognitive status (as measured by the MMSE) in participants with heart failure. The strong relationship between cognitive status and heart failure, and the role of depression in explaining a statistically significant portion of the heterogeneity in the relationship seen in primary studies, highlights the importance of accurately assessing depression when studying the effect of heart failure on cognition. Further research needs to examine the impact of depression on quality of life in patients with heart failure as potentially mediated by difficulties in cognition.

Use of loop diuretics in patients with chronic heart failure: an observational overview

IntroductionThis study aimed to evaluate the use and dose of loop diuretics (LDs) across the entire ejection fraction (EF) spectrum in a large, ‘real-world’ cohort of chronic heart failure (HF)...

Clinical and echocardiographic findings in patients with COVID-19 across different severity levels.

Cardiovascular pathology can complicate the course of COVID-19. The study aimed to identify echocardiographic abnormalities and key prognostic factors influencing severe and fatal COVID-19 outcomes. This retrospective cohort study included clinical and echocardiogram data from 194 medical records of hospitalized patients with COVID-19: 100 moderate cases, 34 severe cases with favorable outcomes, and 60 severe cases with fatal outcomes. Severe patients with favorable outcomes had greater reductions in left ventricular systolic fraction of left ventricle compared to moderate cases (23.5% vs. 7.0%, respectively, p=0.008) and ejection fraction of left ventricle (14.7% vs. 3.0%, respectively, p=0.013), grade I diastolic dysfunction of the left ventricle (20.6% vs. 8.0%, respectively, p=0.044), and pulmonary hypertension (29.41% vs. 10.0%, respectively, p=0.006). Patients with fatal outcomes had a mean age of 67.1±1.51 years, chronic heart failure functional class II (58.3%), hypertension (50.0%), type 2 diabetes (43.3%), and obesity (33.3%). Compared to severe cases but with favorable outcomes, fatal cases had a greater decrease in left ventricular ejection fraction (36.7% vs. 14.7%, respectively, p=0.024), various types of myocardial dysfunction (51.7% vs. 29.4%, respectively, p=0.037) and a trend towards increased pulmonary hypertension (48.3% vs. 29.4%, respectively, p=0.074). Consequently, chronic heart failure class II, reduced left ventricular ejection fraction, various myocardial dysfunctions, and pulmonary hypertension emerged as key cardiac risk factors for severe disease progression and mortality in patients with COVID-19.