Risk Of Heart Failure Decompensation Research Articles

Safety and Efficacy of Veverimer in Acidotic Patients With CKD and Heart Failure

Safety and Efficacy of Veverimer in Acidotic Patients With CKD and Heart Failure

The Utility of Predicting Hospitalizations Among Patients With Heart Failure Using mHealth: Observational Study.

BackgroundHeart failure decompensation is a major driver of hospitalizations and represents a significant burden to the health care system. Identifying those at greatest risk of admission can allow for targeted interventions to reduce this risk.ObjectiveThis paper aims to compare the predictive value of objective and subjective heart failure respiratory symptoms on imminent heart failure decompensation and subsequent hospitalization within a 30-day period.MethodsA prospective observational pilot study was conducted. People living at home with heart failure were recruited from a single-center heart failure outpatient clinic. Objective (blood pressure, heart rate, weight, B-type natriuretic peptide) and subjective (4 heart failure respiratory symptoms scored for severity on a 5-point Likert scale) data were collected twice weekly for a 30-day period.ResultsA total of 29 participants (median age 79 years; 18/29, 62% men) completed the study. During the study period, 10 of the 29 participants (34%) were hospitalized as a result of heart failure. For objective data, only heart rate exhibited a between-group difference. However, it was nonsignificant for variability (P=.71). Subjective symptom scores provided better prediction. Specifically, the highest precision of heart failure hospitalization was observed when patients with heart failure experienced severe dyspnea, orthopnea, and bendopnea on any given day (area under the curve of 0.77; sensitivity of 83%; specificity of 73%).ConclusionsThe use of subjective respiratory symptom reporting on a 5-point Likert scale may facilitate a simple and low-cost method of predicting heart failure decompensation and imminent hospitalization. Serial collection of symptom data could be augmented using ecological momentary assessment of self-reported symptoms within a mobile health monitoring strategy for patients at high risk for heart failure decompensation.

562 Can 2D speckle tracking echocardiography have an additional impact on prediction of hospitalizations due to heart failure decompensation in patients with ischemic left ventricular systolic dysfunction

Abstract Funding Acknowledgements NA Background Despite advancements in medical therapy and device-based treatment, heart failure (HF) continues to impose enormous burden for both patients and health care system worldwide. Hospitalizations due to HF decompensation is well-known cause of mortality. Objectives were to verify whether 2D speckle tracking echocardiography (2D STE) provides independently of other well-known clinical and echocardiographic parameters, information on the risk of HF decompensation in patients with left ventricular systolic dysfunction of ischemic origin. Materials and Methods In 193 stable ischemic HF patients with left ventricular ejection fraction (LVEF) ≤ 50%, global longitudinal strain (GLS), as well as other echocardiographic (GE VIVID E9, EchoPAC v201) and well-known clinical parameters were analyzed. During 34 (14 – 71) months of follow-up, 58 patients were hospitalized due to HF decompensation (EVENT). Results LVEF, GLS, diastolic function and well-known clinical parameters (age, renal function, hemoglobin, brain natriuretic peptide level, history of diabetes, diuretic treatment and the absence of beta-blockers), as well as cut-off values of these parameters identified in ROC analysis were significantly associated with the risk of EVENT in univariate Cox hazard regression analysis (Table). GLS value of -9.4% was the most accurate predictor of EVENT (AUC 80.7% [CI 57.6 – 100%]), whereas other parameters were characterized by lower discriminatory power. In multivariate Cox analyses GLS of -9.4% was still a significant predictor of the EVENT. Conclusions 2D STE can provide additional information, independently of other well-known clinical and echocardiographic parameters, on the risk of HF decompensation in the patients with left ventricular systolic dysfunction of ischemic origin. GLS value worse than -9.4% can identify the patients with higher risk of this EVENT. Hazard Ratio 95% CI p Age ≥ 71 yo 2.48 1.46 - 4.23 <0.001 GFR ≤ 30 ml/min/1.73 m² 4.67 1.65 - 13.22 <0.004 Hemoglobin ≤ 14.7 g/dl 3.02 1.19 - 7.70 <0.020 BNP ≥ 214 pg/ml 2.64 1.31 - 5.31 <0.007 LVEF ≤ 32% 2.76 1.55 - 4.90 <0.001 GLS ≥ -9.4% 15.16 1.81 - 56.91 <0.012 E/A ≥ 2.0 8.64 1.91 - 39.05 0.005

Global longitudinal strain can predict heart failure exacerbation in stable outpatients with ischemic left ventricular systolic dysfunction.

BackgroundDespite advancements in pharmacological and device-based treatment, heart failure (HF) continues to impose an enormous burden for health care system worldwide. Decompensation of HF is one of the main causes of hospitalization, therefore the identification of patients with the highest risk of such complication is still of great clinical importance. The prognostic significance and utility of global longitudinal strain (GLS) has been previously studied in patients with the broad spectrum of cardiovascular diseases in various endpoints, however its role in assessing the risk of hospitalization due to HF exacerbation of optimally treated outpatients has not been fully explored. Therefore, the aim of the study was to verify whether the GLS of the left ventricle (LV) derived by 2D speckle tracking echocardiography has, independently of other well-known clinical parameters, an additional impact on the risk of HF decompensation in stable patients with LV systolic dysfunction of ischemic origin.MethodsIn 193 clinically stable HF outpatients with LV ejection fraction (LVEF) ≤ 50%, GLS, additionally to other clinical parameters, was analyzed. During 34 (14–71) months of follow-up, 58 patients were hospitalized due to HF decompensation (EVENT).ResultsEVENT was significantly associated with age, QRS width, NYHA functional class, left atrium diameter, LV systolic and diastolic volume, LVEF, hemoglobin, brain natriuretic peptide, diuretic treatment, absence of beta-blockers, impaired renal function and history of diabetes in univariate Cox analyzes. GLS with pre-specified cut-off value of -9.4% was also significantly associated with the EVENT (HR 15.16; 95% CI 1.81–126.91). After adjusting for above-mentioned parameters GLS was still a significant predictor of hospitalization due to HF decompensation.ConclusionsGLS measurement can provide incremental information on the risk of HF decompensation in stable outpatients with LV systolic dysfunction of ischemic origin.

P4386Sleep disordered breathing (SDB) increases the risk of heart failure decompensation: clinical factors and bioelectrical impedance analysis

P4386Sleep disordered breathing (SDB) increases the risk of heart failure decompensation: clinical factors and bioelectrical impedance analysis

Autonomic Predictors of Hospitalization Due to Heart Failure Decompensation in Patients with Left Ventricular Systolic Dysfunction.

IntroductionAutonomic nervous system balance can be significantly deteriorated during heart failure exacerbation. However, it is still unknown whether these changes are only the consequence of heart failure decompensation or can also predict development thereof. Objectives were to verify if simple, non-invasive autonomic parameters, such as baroreflex sensitivity and short-term heart rate variability can provide independent of other well-known clinical parameters information on the risk of heart failure decompensation in patients with left ventricular systolic dysfunction.MethodsIn 142 stable patients with left ventricular ejection fraction ≤ 40%, baroreflex sensitivity and short-term heart rate variability, as well as other well-known clinical parameters, were analyzed. During 23 ± 9 months of follow-up 19 patients were hospitalized due to the heart failure decompensation (EVENT).ResultsPre-specified cut-off values of baroreflex sensitivity (≤2.4 ms/mmHg) and low frequency power index of heart rate variability (≤19 ms2) were significantly associated with the EVENTs (hazard ratio 4.43, 95% confidence interval [CI] 1.35–14.54 and 5.41, 95% CI 1.87–15.65 respectively). EVENTs were also associated with other parameters, such as left ventricular ejection fraction, NYHA class, diuretic use, renal function, brain natriuretic peptide and hemoglobin level, left atrial size, left and right ventricular heart failure signs. After adjusting baroreflex sensitivity and low frequency power index for each of the abovementioned parameters, autonomic parameters were still significant predictors of hospitalization due to the heart failure decompensation.ConclusionSimple, noninvasive autonomic indices can be helpful in identifying individuals with increased risk of hospitalization due to the heart failure decompensation among clinically stable patients with left ventricular systolic dysfunction, even when adjusted for other well-known clinical parameters.

A Dynamic Risk Score to Identify Increased Risk for Heart Failure Decompensation

A method for combining heart failure (HF) diagnostic information in a Bayesian belief network (BBN) framework to improve the ability to identify when patients are at risk for HF hospitalization (HFH) is investigated in this paper. Implantable devices collect HF related diagnostics, such as intrathoracic impedance, atrial fibrillation (AF) burden, ventricular rate during AF, night heart rate, heart rate variability, and patient activity, on a daily basis. Features were extracted that encoded information regarding out of normal range values as well as temporal changes at weekly and monthly time scales. A BBN is used to combine the features to generate a risk score defined as the probability of a HFH given the diagnostic evidence. Patients with a very high risk score at follow-up are 15times more likely to have a HFH in the next 30days compared to patients with a low-risk score. The combined score has improved ability to identify patients at risk for HFH compared to the individual diagnostic parameters. A score of this nature allows clinicians to manage patients by exception; a patient with higher risk score needs more attention than a patient with lower risk score.

Left Ventricular End Diastolic Pressure and Serum Brain Natriuretic Peptide Levels in Patients with Abnormal Impedance Cardiography Parameters

Distinct hemodynamic patterns determined by impedance cardiography (ICG) have been found to be superior to clinical assessment for the identification of patients at risk for heart failure decompensation in the outpatient setting. Correlation of these hemodynamic patterns with serum brain natriuretic peptides (BNP) and left ventricular end diastolic pressure (LVEDP) has not been established. We evaluated the correlation of low-, intermediate- and high-risk groups for acute decompensation of heart failure (ADHF) as determined by ICG parameters with LVEDP and serum BNP. Consecutive patients referred for cardiac catheterization with echocardiographic diagnosis of left ventricle dysfunction (systolic or diastolic) or history of congestive heart failure (CHF) underwent ICG evaluation, serum BNP measurement, and LVEDP by cardiac catheterization. Three groups at different levels of risk for ADHF were determined according to ICG parameters: thoracic fluid content (TFC) and stroke volume index (SVI); low risk (low TFC, high SVI), intermediate risk (low-low or high-high TFC and SVI, respectively), and high risk (high TFC and low SVI). Sixty three patients were included in the present study. Mean LVEDP and serum BNP levels were 20.2 +/- 8.2 mmHg and 814 +/- 1005 pg/mL, respectively, in the high-risk group in comparison to 12.3 +/- 6.2 mmHg and 53 +/- 38 pg/mL in the low-risk group (p = 0.01 and p = 0.009). Patients with ICG parameters that represent high risk for ADHF have higher levels of serum BNP and LVEDP in comparison with patients who have intermediate- or low-risk ICG parameters for ADHF.

Using Devices for Physiologic Monitoring in Heart Failure

Heart failure (HF) is a complex and costly disease process associated with high morbidity and mortality. Implanted cardiac rhythm management devices are increasingly used in the HF population to provide therapies such as protection from sudden death and cardiac resynchronization therapy. Device-based diagnostic monitoring provides clinicians with information that can assist in identifying patients at risk for HF decompensation and subsequent hospitalization. This article will review the evidence for using diagnostic information from cardiac rhythm management devices in the management of HF patients. Future advanced monitoring devices will also be discussed.

Use of implanted CRT device diagnostics to determine the risk of heart failure decompensation

Use of implanted CRT device diagnostics to determine the risk of heart failure decompensation

707 Determining the risk of heart failure decompensation: use of CRT device diagnostics

707 Determining the risk of heart failure decompensation: use of CRT device diagnostics