What is HFpEF? Why it may not be Real Heart Failure.

Background Despite evidence that guideline-directed medical therapy (GDMT) improves outcomes in heart failure with reduced ejection fraction (HFrEF), many eligible patients remain untreated in the United States (US). Purpose To explore reasons why patients are not receiving GDMT and physician perceptions in management of their patients. Methods We conducted a cross-sectional survey of HF treatment practices (Adelphi Real World Heart Failure Disease Specific Programme) between August 2022 and February 2023, following publication of the 2022 US HF guidelines recommended that patients with HFrEF receive: angiotensin receptor/neprilysin inhibitors (ARNI), beta-blocker, mineralocorticoid receptor antagonists (MRA), and SGLT-2 inhibitors (SGLT2i). A total of 63 cardiologists and 39 primary care physicians in the US provided clinical and treatment patterns data on adult patients with HFrEF (ejection fraction ≤ 40%) and completed an attitudinal survey detailing reasons for treatment initiation. Results The study group included 323 patients with HFrEF (median age of 67 years [IQR 56-74]; 39% females) of which 59.4% were White, 19.8% African American and 9.6% Hispanic; half of the sample was insured by Medicare (50.2%), followed by commercial insurance (36.5%). GDMT prescription rates are presented in Table 1. Overall, 57.3% were not prescribed ARNI (185/323), 16.4% (53/323) were not prescribed a beta-blocker; 71.5% (231/323) were not prescribed MRA, and 65.3% (211/323) were not prescribed SGLT2i. Among patients not receiving GDMT, the most frequently reported physician reason for not prescribing ARNIs (54.1%), beta-blockers (43.4%), MRAs (54.5%) or SGLT-2is (53.6%) was physician deemed the patient to be clinically stable (Table 2). Most physicians (93.5%) reported being satisfied with treatment for patients with HFrEF and most (80.3%) believed that their patients with HFrEF were fully compliant with their treatments. Most physicians (91.2%) stated that they based their treatment decisions on both clinical experience and laboratory tests, as opposed to laboratory tests/imaging only (9.8%) or personal judgement only (16.7%). Conclusions In this cohort of patients with HFrEF from the US, the most common primary reason physicians reported for their patients not receiving GDMT was that the patient was clinically stable. Patient medication costs, contraindications, and proven intolerance were each reported as primary reasons for non-treatment in only a small minority of cases. These data suggest a strong culture of clinical inertia and lack of therapeutic urgency as the dominant driver of large gaps in use of GDMT in the US.GDMT prescriptions in HFrEF (n = 323)Physician-reasons for no GDMT

For normal cardiac performance, the left ventricle (LV) must be able to eject an adequate stroke volume at arterial pressure (systolic function) and fill without requiring an elevated left atrial (LA) pressure (diastolic function). These systolic and diastolic functions must be adequate to meet the needs of the body both at rest and during stress. Response by Tschope and Paulus on p 809 Systolic function is conveniently (although not always accurately) measured as the ejection fraction (EF), calculated as stroke volume divided by end-diastolic volume.1 The LV EF is easily interpreted. The lower limit of normal is ≈50%. The lower the EF is, the greater the reduction in systolic function. Diastolic function has been more difficult to evaluate.2 Traditionally, invasive measures of LV diastolic pressure-volume relations and the rate of LV pressure fall during isovolumetric relaxation have been used. However, these methods are not practical for routine clinical use and do not adequately evaluate all aspects of diastolic filling.3 Comprehensive echocardiographic evaluation of the dynamics of LV filling using blood pool and tissue Doppler has now progressed so that it provides clinically important information that can be used to direct patient care. We present data that support the use of echocardiographic evaluation of diastolic function to recognize cardiac dysfunction in patients with heart failure, especially those with preserved EF; to guide the management of patients by identifying those with and without elevated left filling pressures regardless of underlying EF; and to determine prognosis in a wide variety of patient populations. Although the LV end-diastolic pressure-volume relation describes the passive properties of the LV, LV filling is not a passive or slow process.3 In fact, the peak flow rate across the mitral valve is equal to or greater than the peak flow rate across the aortic valve. …

Heart failure and its complications are significant causes of mortality and morbidity in most societies. Major parts of the studies that constitute the base of modern treatment of heart failure have been limited to the study of heart failure associated with reduced left ventricular ejection fraction (HFrEF). Only during the past 10–15 years, heart failure associated with preserved left ventricular ejection fraction (HFpEF) or primarily right-sided heart failure have come more into focus as our understanding of the critical role of other etiologies for the clinical syndrome of heart failure than a reduced left ventricular (LV) ejection fraction has increased. Furthermore, whilst the powerful prognostic role of a reduced LV ejection fraction has long since been well validated, only relatively recently it was realized that patients with heart failure symptoms and preserved LV ejection fraction also have a substantially impaired prognosis. Previously, these patients had often been dismissed as not having "real heart failure". In parallel, it has become clear that diagnoses like hypertensive heart disease, diabetic cardiomyopathy and heart failure associated with atrial fibrillation, among others, can be understood as forms of HFpEF.

Funding AcknowledgementsType of funding sources: Public hospital(s). Main funding source(s): Leiden University Medical CenterBackgroundHospitalizations for decompensated heart failure are a marker for poor prognosis and pose a burden on patients and resources. The mainstay in preventing these hospitalizations is early detection of fluid retention and timely pharmacological intervention. The multisensory cardiac implantable electronic device (CIED) based HeartLogic™ algorithm can alert in case of upcoming congestion. The cumulative HeartLogic™ index is based on the following sensors: heart sounds, thoracic impedance, respiratory rate, night heart rate and patient activity levels. The current analysis investigates the performance of the HeartLogicTM algorithm in a real-world ambulant heart failure population.MethodsAll consecutive heart failure patients with a CIED and an activated HeartLogic™ algorithm were included for analysis. Patients were followed from 01-01-2018 until 01-09-2022 according to the heart failure care path (figure 1). HeartLogic™ automatically generated an alert if the index surpassed the preset threshold of 16. An alert was either true positive (≥2 signs/symptoms of fluid retention on top of the alert) or false positive (≤1 signs/symptoms). Without an alert a patient was true negative (≤1 signs/symptoms) or false negative (≥2 signs/symptoms). A logistic regression model with linear mixed models was used. Furthermore, patients with ≥2 true positive alerts and ≤1 false positive alerts per year were compared to patients without alerts to identify characteristics of patients who benefit most from the HeartLogic™ algorithm supported management.ResultsData of 138 patients were included, median age was 69 [60 – 77], 78% was male and 50% had an ischemic etiology of heart failure. Majority of the patients had a CRT-D (n=90, 65%) and the remaining 48 patients had an ICD (35%). Total follow-up entailed of 297 patient years, median follow-up was 26 months [14 – 36]. During follow-up, 231 alerts were observed. After exclusion of 14 alerts (incomplete clinical information), 217 alerts were available for analysis. Majority of these alerts were true positive for fluid retention(n=161, 74%). Of interest, 21 of these alerts (13%) were not primarily heart failure related, but prompted clinical action (e.g. pneumonia or anemia). The remaining 59 (26%) alerts were deemed false positive. The sensitivity to detect impending fluid retention was 86%, the specificity 88%. The positive predictive value was 73% and the negative predictive value was 94%. Patients with HeartLogicTM alerts had a significantly higher baseline NT-Pro BNP, when compared to patients without alerts, p<0.05 (Figure 2). No differential response was observed based on age, gender or BMI.ConclusionsIn a real world heart failure population the HeartLogic™ algorithm supported care path adequately detects impending fluid retention. Patients who benefited most had higher levels of NT-Pro BNP at baseline.Overview of the Heart Failure care pathNT-Pro BNP levels

Background Sodium glucose co-transporter 2 inhibitors (SGLT2-i) are one of the four pillars of guideline-directed medical therapy in heart failure with reduced ejection fraction and preserved ejection fraction according to the current ESC and AHA/ACC heart failure guidelines 1,2. As a result, there has been a significant increase in their use worldwide. Although SGLT2 inhibitors are known to increase hemoglobin and hematocrit levels, there is a lack of data on the burden of erythrocytosis or polycythemia in pivotal trials 3,4. Purpose In this retrospective cohort study, we investigated the prevalence and clinical outcomes of SGLT2-i related erythrocytosis in a tertiary heart failure outpatient clinic. Methods We reviewed clinical data from heart failure patients treated with an SGLT2 inhibitor at our tertiary centre between September 2019 and October 2023. Patients were included if they were taking SGLT2-i continuously for more than one month. Data were collected on Hb/Hct levels at baseline before initiation of SGLT2-i, at peak levels during therapy and at the last follow-up. Erythrocytosis was defined according to the 2017 WHO classification as Hb&amp;gt; 10.3 mmol/L and/or Hct&amp;gt; 49% in men and Hb&amp;gt; 10.0 mmol/L and/or Hct&amp;gt; 48% in females. Results A total of 173 patients with heart failure were included (median age 58 [49-66] years, 65% male). One hundred and fifty-six patients (90%) were using dapagliflozin, while 16 patients (9%) were using empagliflozin. The overall prevalence of SGLT2i related erythrocytosis was 39/173 (22.5%; median age 60 and 82% males). Eleven (6.3%) patients had pre-existing erythrocytosis at baseline. During a mean follow-up of 14±10 months, 28/173 (16.2%) patients developed new onset erythrocytosis. The median time to the peak of the Hb/Hct level was 6.5 months. Although the group with erythrocytosis had significantly higher Hb and Hct at baseline compared to the group without erythrocytosis (Hb 9.7 mmol/L ± 1.0 vs. 8.5 mmol/L ± 1.0; p&amp;lt;0.001 in men and 9.1 mmol/L ± 0.8 mmol/L vs. 8.1 ± 0.8; p=0.006 in females), they also experienced a significantly greater median increase in Hb from baseline to peak (1.05 mmol/L vs. 0.60mmol/L; p=0.01) (see Figure 1) There were significantly more males (82% vs 60%; p=0.01) in the erythrocytosis group compared to the non-erythrocytosis group. In addition, the prevalence of OSAS was significantly higher in the group with erythrocytosis compared to the group without erythrocytosis (31% vs. 8%; p&amp;lt;0.001). Conclusion Secondary erythrocytosis or polycythemia is common in patients with chronic heart failure. It is particularly common in men and in patients with obstructive sleep apnoea syndrome (OSAS). There were no excess thrombotic or thromboembolic events, probably because of the routine use of anticoagulants/antiplatelets and limited follow-up. To avoid unnecessary haematological referrals and potential clinical adverse events, increased awareness among clinicians is needed.Table 1.Baseline and clinical outcomesFig1.Hemoglobin levels over time

Background There is few data about programmed lower rate limit (LRL) in real world heart failure (HF) patients with cardiac resynchronization therapy–defibrillators (CRT-Ds) and its influence in clinical outcomes. Heart rate score (HRS) is the percentage of all atrial-paced and sensed events in the single tallest 10 beats/min device histogram bin and may indicate impaired heart rate variability. Purpose We hypothesized that higher LRL programming is associated with worse clinical outcomes as arrhythmic events and HF decompensations in chronic HF patients with CRT-Ds. Methods LRL was evaluated and HRS was calculated from remote monitoring in 126 HF patients with CRT-D. Primary outcome was defined as HF hospitalizations and related admissions to the emergency department and secondary outcome as number of device therapies, sustained ventricular tachycardia (VT) and ventricular fibrillation (VF). Results Mean age was 69,03±10,39 years, 81 (64,3%) were males and mean follow-up was 53,72±46,13 months. Mean left ventricular ejection fraction was 30,31±8,33% and 29 (23,0%) were in NYHA III–IV. HF aetiology was idiopathic in 39 (43,3%), ischemic in 32 (25,4%) and alcoholic cardiomyopathy in 8 (6,3%). Thirty-seven (29,4%) patients had atrial fibrillation and 33 (26,2%) coronary disease. LRL ranged from to 40 to 80 bpm and mean LRL was 52,64±9,64 and mean HRS 49,60±23,17%. Programmed LRL was higher in women (p=0,014), patients with atrial fibrillation (AF) (p=0,012) and coronary disease (p=0,015). Higher LRL correlated with HF hospitalizations and related admissions to the emergency department (ED) (r=0,541, p=0,001), VT or VF episodes (r=0,337, p=0,005) and CRT-D number of therapies (r=0,342, p=0,004) and higher HRS (r=0,547, p&amp;lt;0,05). Conclusion Higher LRL programming was associated with higher HRS, HF decompensations with hospitalization or admission to the emergency department, VT or VF episodes and CRT-D therapies in a real world population. More studies are required but lower LRL may be preferred in HF patients. Funding Acknowledgement Type of funding sources: None.

AimsThis study aims to investigate hospital readmissions and timing, as well as risk factors in a real world heart failure (HF) population.Methods and resultsAll patients discharged alive in 2016 from Sahlgrenska University Hospital/Östra, Gothenburg, Sweden, with a primary diagnosis of HF were consecutively included. Patient characteristics, type of HF, treatment, and follow‐up were registered. Time to first all‐cause or HF readmission, as well as number of 1 year readmissions from discharge were recorded. In total, 448 patients were included: 273 patients (mean age 78 ± 11.8 years) were readmitted for any cause within 1 year (readmission rate of 60.9%), and 175 patients (mean age 76.6 ± 13.7) were never readmitted. Among readmissions, 60.1% occurred during the first quarter after index hospitalization, giving a 3 month all‐cause readmission rate of 36.6%. HF‐related 1 year readmission rate was 38.4%. Patients who were readmitted had significantly more renal dysfunction (52.4% vs. 36.6%, P = 0.001), pulmonary disease (25.6% vs. 15.4%, P = 0.010), and psychiatric illness (24.9% vs. 12.0%, P = 0.001). Number of co‐morbidities and readmissions were significantly associated (P < 0.001 for all cause readmission rate and P = 0.012 for 1 year HF readmission rate). Worsening HF constituted 63% of all‐cause readmissions. Psychiatric disease was an independent risk factor for 1 month and 1 year all‐cause readmissions. Poor compliance to medication was an independent risk factor for 1 month and 1 year HF readmission.ConclusionsIn our real world cohort of HF patients, frequent hospital readmissions occurred in the early post‐discharge period and were mainly driven by worsening HF. Co‐morbidity was one of the most important factors for readmission.

Gender differences among Norwegian patients with heart failure

Funding Acknowledgements Type of funding sources: None. Background A bidirectional relationship exists between the kidney and the heart; the lower the eGFR the more challenging it is to manage the heart failure (HF) patient. Worsening renal function is common in HF patients and associated with a two-fold increase in mortality and a lower likelihood of being prescribed efficacious HF therapy. The role of cardio-renal interactions in HF is essential to identify risk and subsequent treatment strategies. Purpose The purpose of this audit is to provide insights into the assessment of renal function in a real world heart failure population by identifying the degree of renal dysfunction and changes in renal function over a five year time frame. Methods A retrospective audit included patients with HFrEF attending a heart failure service. These patients were classified using KIDGO criteria CKD 1-5. A current eGFR sample was compared with a sample taken five years earlier, identified using the electronic laboratory record. Ethical approval was granted from the Research Ethics Committee. Resultss 100 patients with HFrEF attending a heart failure service fulfilled the selection criteria of which sixty three patients with an eGFR &amp;gt;60ml/min/1.73 m2 were audited. Of this group 43 were CKD class 2 and 20 were CKD class 1. Thirty seven patients had an eGFR &amp;lt;60ml/min/1.73 m2 of which 9 were class 3b, 9 were CKD class 4 and 1 was CKD Class 5. Of the 100 patients enrolled, 6 were excluded from the analysis of kidney function decline as an eGFR from five years earlier was unavailable. Within a five year time span, 44 patients did not change their CKD class, 31 patients declined by one class, 9 patients declined by two classes, 3 patients declined by three classes and 7 patients improved their kidney function. GFR &amp;lt; 60mL/min/1.73m2, n = 37 GFR &amp;gt; 60mL/min/1.73m2, n = 63 Age – mean (range) 77.8 (49-94) 66.5 (45-89) Gender – female (%) 12 (32%) 16 (25%) Average renal function measurements (mean, range) 6.4 6.7 Total albumin creatinine ratio measurements 8 6 Actively attending renal service 6 0 Conclusion Nurses should be aware of the increasing risk conferred by the dual diagnosis of heart failure and chronic kidney disease. Patients with heart failure who have decreasing eGFR levels (especially less than 30 mL/min), should have collaborative management with nephrology services to optimise outcomes. Recognition of CKD in our institution and referral to nephrology services was suboptimal and further work is necessary to optimise the management of these patients.

IntroductionSacubitril/Valsartan is a novel therapy in the treatment of heart failure with reduced ejection fraction, demonstrating a lower cardiovascular mortality and heart failure hospitalisation rates compared to standard therapy. We...

BackgroundHeart failure remains challenging to manage and treat globally. Much of the data on its prognosis stems from clinical trials, where cohorts are often younger and less sick than the...

ObjectiveHospital readmission costs a lot of money every year. Many hospital readmissions are avoidable, and excessive hospital readmissions could also be harmful to the patients. Accurate prediction of hospital readmission can effectively help reduce the readmission risk. However, the complex relationship between readmission and potential risk factors makes readmission prediction a difficult task. The main goal of this paper is to explore deep learning models to distill such complex relationships and make accurate predictions.Materials and methodsWe propose CONTENT, a deep model that predicts hospital readmissions via learning interpretable patient representations by capturing both local and global contexts from patient Electronic Health Records (EHR) through a hybrid Topic Recurrent Neural Network (TopicRNN) model. The experiment was conducted using the EHR of a real world Congestive Heart Failure (CHF) cohort of 5,393 patients.ResultsThe proposed model outperforms state-of-the-art methods in readmission prediction (e.g. 0.6103 ± 0.0130 vs. second best 0.5998 ± 0.0124 in terms of ROC-AUC). The derived patient representations were further utilized for patient phenotyping. The learned phenotypes provide more precise understanding of readmission risks.DiscussionEmbedding both local and global context in patient representation not only improves prediction performance, but also brings interpretable insights of understanding readmission risks for heterogeneous chronic clinical conditions.ConclusionThis is the first of its kind model that integrates the power of both conventional deep neural network and the probabilistic generative models for highly interpretable deep patient representation learning. Experimental results and case studies demonstrate the improved performance and interpretability of the model.

People with heart failure tend to develop cognitive impairments, anxiety and constant boredom due to the time they have to wait to get surgery while being hospitalised. Serious games may assist these in improving their cognitive abilities and get distracted while waiting for surgery. In this paper, we present Rivit, a collection mini-games aimed at improving cognition and mood of heart failure patients, which is still under development. We present the current state of the game and a preliminary user experience evaluation. The aim of this evaluation is to identify the strengths and weaknesses of Rivit so that it can be tested with real patients at a later stage. Although the evaluation was not conducted with real heart failure patients, we found that elderly people may need more effort than young people to understand game goals. Our work may serve as a basis for developers of games aimed at heart failure patients during early development stages.

Classification of a real live heart failure clinical dataset- Is TAN Bayes better than other Bayes?

BackgroundHeart failure (HF) is frequent and its prevalence is increasing. We aimed to evaluate the epidemiologic features of HF patients, the 1-year follow-up outcomes and the independent predictors of those outcomes at a population level.Methods and resultsPopulation-based longitudinal study including all prevalent HF cases in Catalonia (Spain) on December 31st, 2012. Patients were divided in 3 groups: patients without a previous HF hospitalization, patients with a remote (>1 year) HF hospitalization and patients with a recent (<1 year) HF admission. We analyzed 1year all-cause and HF hospitalizations, and all-cause mortality. Logistic regression was used to identify the independent predictors of each of those outcomes. A total of 88,195 patients were included. Mean age was 77 years, 55% were women. Comorbidities were frequent. Fourteen percent of patients had never been hospitalized, 71% had a remote HF hospitalization and 15% a recent hospitalization. At 1-year follow-up, all-cause and HF hospitalization were 53% and 8.8%, respectively. One-year all-cause mortality rate was 14%, and was higher in patients with a recent HF hospitalization (24%). The presence of diabetes mellitus, atrial fibrillation or chronic kidney disease was independently associated with all-cause and HF hospitalization and all-cause mortality. Hospital admissions and emergency department visits the previous year were also found to be independently associated with the three study outcomes.ConclusionsOutcomes are different depending on the HF population studied. Some comorbidity, an all-cause hospitalization or emergency department visit the previous year were associated with a worse outcome.