761 research outputs found

    The long-term prognostic significance of 6-minute walk test distance in patients with chronic heart failure

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    Background. The 6-minute walk test (6-MWT) is used to assess patients with chronic heart failure (CHF). The prognostic significance of the 6-MWT distance during long-term followup ( > 5 years) is unclear. Methods. 1,667 patients (median [inter-quartile range, IQR]) (age 72 [65-77] ; 75% males) with heart failure due to left ventricular systolic impairment undertook a 6-MWT as part of their baseline assessment and were followed up for 5 years. Results. At 5 years' followup, those patients who died (n = 959) were older at baseline and had a higher log NT pro-BNP than those who survived to 5 years (n = 708). 6-MWT distance was lower in those who died [163 (153) m versus 269 (160) m; P 360 m. 6-MWT distance was a predictor of all-cause mortality (HR 0.97; 95% CI 0.96-0.97; Chi-square = 184.1; P < 0.0001). Independent predictors of all-cause mortality were decreasing 6-MWT distance, increasing age, increasing NYHA classification, increasing log NT pro-BNP, decreasing diastolic blood pressure, decreasing sodium, and increasing urea. Conclusion. The 6-MWT is an important independent predictor of all-cause mortality following long-term followup in patients with CHF. © 2014 Lee Ingle et al

    Clinical trials with endothelin receptor antagonists: What went wrong and where can we improve?

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    In the early 1990s, within three years of cloning of endothelin receptors, orally active endothelin receptor antagonists (ERAs) were tested in humans and the first clinical trial of ERA therapy in humans was published in 1995. ERAs were subsequently tested in clinical trials involving heart failure, pulmonary arterial hypertension, resistant arterial hypertension, stroke/subarachnoid hemorrhage and various forms of cancer. The results of most of these trials – except those for pulmonary arterial hypertension and scleroderma-related digital ulcers – were either negative or neutral. Problems with study design, patient selection, drug toxicity, and drug dosing have been used to explain or excuse failures. Currently, a number of pharmaceutical companies who had developed ERAs as drug candidates have discontinued clinical trials or further drug development. Given the problems with using ERAs in clinical medicine, at the Twelfth International Conference on Endothelin in Cambridge, UK, a panel discussion was held by clinicians actively involved in clinical development of ERA therapy in renal disease, systemic and pulmonary arterial hypertension, heart failure, and cancer. This article provides summaries from the panel discussion as well as personal perspectives of the panelists on how to proceed with further clinical testing of ERAs and guidance for researchers and decision makers in clinical drug development on where future research efforts might best be focused

    Design and usage of the HeartCycle education and coaching program for patients with heart failure

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    Background: Heart failure (HF) is common, and it is associated with high rates of hospital readmission and mortality. It is generally assumed that appropriate self-care can improve outcomes in patients with HF, but patient adherence to many self-care behaviors is poor. Objective: The objective of our study was to develop and test an intervention to increase self-care in patients with HF using a novel, online, automated education and coaching program. Methods: The online automated program was developed using a well-established, face-to-face, home-based cardiac rehabilitation approach. Education is tailored to the behaviors and knowledge of the individual patient, and the system supports patients in adopting self-care behaviors. Patients are guided through a goal-setting process that they conduct at their own pace through the support of the system, and they record their progress in an electronic diary such that the system can provide appropriate feedback. Only in challenging situations do HF nurses intervene to offer help. The program was evaluated in the HeartCycle study, a multicenter, observational trial with randomized components in which researchers investigated the ability of a third-generation telehealth system to enhance the management of patients with HF who had a recent (&lt;60 days) admission to the hospital for symptoms or signs of HF (either new onset or recurrent) or were outpatients with persistent New York Heart Association (NYHA) functional class III/IV symptoms despite treatment with diuretic agents. The patients were enrolled from January 2012 through February 2013 at 3 hospital sites within the United Kingdom, Germany, and Spain. Results: Of 123 patients enrolled (mean age 66 years (SD 12), 66% NYHA III, 79% men), 50 patients (41%) reported that they were not physically active, 56 patients (46%) did not follow a low-salt diet, 6 patients (5%) did not restrict their fluid intake, and 6 patients (5%) did not take their medication as prescribed. About 80% of the patients who started the coaching program for physical activity and low-salt diet became adherent by achieving their personal goals for 2 consecutive weeks. After becoming adherent, 61% continued physical activity coaching, but only 36% continued low-salt diet coaching. Conclusions: The HeartCycle education and coaching program helped most nonadherent patients with HF to adopt recommended self-care behaviors. Automated coaching worked well for most patients who started the coaching program, and many patients who achieved their goals continued to use the program. For many patients who did not engage in the automated coaching program, their choice was appropriate rather than a failure of the program

    Development of a composite model derived from cardiopulmonary exercise tests to predict mortality risk in patients with mild-to-moderate heart failure

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    Objective: Cardiopulmonary exercise testing (CPET) is used to predict outcome in patients with mild-to-moderate heart failure (HF). Single CPET-derived variables are often used, but we wanted to see if a composite score achieved better predictive power. Methods: Retrospective analysis of patient records at the Department of Cardiology, Castle Hill Hospital, Kingston-upon-Hull. 387 patients [median (25th-75th percentile)] [age 65 (56-72) years; 79% males; LVEF 34 (31-37) %] were included. Patients underwent a symptomlimited, maximal CPET on a treadmill. During a median follow up of 8.6 ± 2.1 years in survivors, 107 patients died. Survival models were built and validated using a hybrid approach between the bootstrap and Cox regression. Nine CPET-derived variables were included. Z-score defined each variable's predictive strength. Model coefficients were converted to a risk score. Results: Four CPET-related variables were independent predictors of all-cause mortality in the survival model: the presence of exertional oscillatory ventilation (EOV), increasing slope of the relation between ventilation and carbon dioxide production (VE/VCO2 slope), decreasing oxygen uptake efficiency slope (OUES), and an increase in the lowest ventilatory equivalent for carbon dioxide (VEqCO2 nadir). Individual predictors of mortality ranged from 0.60 to 0.71 using Harrell’s C-statistic, but the optimal combination of EOV + VE/VCO2 slope + OUES + VEqCO2 nadir reached 0.75. The Hull CPET risk score had a significantly higher area under the curve (0.78) when compared to the Heart Failure Survival Score (AUC=0.70;

    Early indication of decompensated heart failure in patients on home-telemonitoring: a comparison of prediction algorithms based on daily weight and noninvasive transthoracic bio-impedance

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    Background: Heart Failure (HF) is a common reason for hospitalization. Admissions might be prevented by early detection of and intervention for decompensation. Conventionally, changes in weight, a possible measure of fluid accumulation, have been used to detect deterioration. Transthoracic impedance may be a more sensitive and accurate measure of fluid accumulation. Objective: In this study, we review previously proposed predictive algorithms using body weight and noninvasive transthoracic bio-impedance (NITTI) to predict HF decompensations. Methods: We monitored 91 patients with chronic HF for an average of 10 months using a weight scale and a wearable bio-impedance vest. Three algorithms were tested using either simple rule-of-thumb differences (RoT), moving averages (MACD), or cumulative sums (CUSUM). Results: Algorithms using NITTI in the 2 weeks preceding decompensation predicted events (P&lt;.001); however, using weight alone did not. Cross-validation showed that NITTI improved sensitivity of all algorithms tested and that trend algorithms provided the best performance for either measurement (Weight-MACD: 33%, NITTI-CUSUM: 60%) in contrast to the simpler rules-of-thumb (Weight-RoT: 20%, NITTI-RoT: 33%) as proposed in HF guidelines. Conclusions: NITTI measurements decrease before decompensations, and combined with trend algorithms, improve the detection of HF decompensation over current guideline rules; however, many alerts are not associated with clinically overt decompensation

    Development of a human model for the study of effects of hypoxia, exercise, and sildenafil on cardiac and vascular function in chronic heart failure

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    Background: Pulmonary hypertension is associated with poor outcome in patients with chronic heart failure (CHF) and may be a therapeutic target. Our aims were to develop a noninvasive model for studying pulmonary vasoreactivity in CHF and characterize sildenafil's acute cardiovascular effects. Methods and Results: In a crossover study, 18 patients with CHF participated 4 times [sildenafil (2 × 20 mg)/or placebo (double-blind) while breathing air or 15% oxygen] at rest and during exercise. Oxygen saturation (SaO2) and systemic vascular resistance were recorded. Left and right ventricular (RV) function and transtricuspid systolic pressure gradient (RVTG) were measured echocardiographically. At rest, hypoxia caused SaO2 (P = 0.001) to fall and RVTG to rise (5 ± 4 mm Hg; P = 0.001). Sildenafil reduced SaO2 (−1 ± 2%; P = 0.043), systemic vascular resistance (−87 ± 156 dyn·s−1·cm−2; P = 0.034), and RVTG (−2 ± 5 mm Hg; P = 0.05). Exercise caused cardiac output (2.1 ± 1.8 L/min; P &lt; 0.001) and RVTG (19 ± 11 mm Hg; P &lt; 0.0001) to rise. The reduction in RVTG with sildenafil was not attenuated by hypoxia. The rise in RVTG with exercise was not substantially reduced by sildenafil. Conclusions: Sildenafil reduces SaO2 at rest while breathing air, this was not exacerbated by hypoxia, suggesting increased ventilation–perfusion mismatching due to pulmonary vasodilation in poorly ventilated lung regions. Sildenafil reduces RVTG at rest and prevents increases caused by hypoxia but not by exercise. This study shows the usefulness of this model to evaluate new therapeutics in pulmonary hypertension

    Prediction of mortality rates in heart failure patients with data mining methods

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    Heart failure is one of the severe diseases which menace the human health and affectmillions of people. Half of all patients diagnosed with heart failure die within four years. For thepurpose of avoiding life-threatening situations and minimizing the costs, it is important to predictmortality rates of heart failure patients. As part of a HEIF-5 project, a data mining study wasconducted aiming specifically at extracting new knowledge from a group of patients suffering fromheart failure and using it for prediction of mortality rates. The methodology of knowledge discoveryin databases is analyzed within the framework of home telemonitoring. Several data mining methodssuch as a Bayesian network method, a decision tree method, a neural network method and a nearestneighbour method are employed. The accuracy for the data mining methods from the point of view ofavoiding life-threatening situations and minimizing the costs is discussed. It seems that the decisiontree method achieves the best accuracy results and is also interpretable for the clinicians

    Combined use of lung ultrasound, B-type natriuretic peptide, and echocardiography for outcome prediction in patients with acute HFrEF and HFpEF

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    Background: Lung ultrasound (LUS) can be used to assess pulmonary congestion by imaging B-lines (‘comets’) for patients with acute heart failure (AHF). Objectives: Investigate relationship of B-lines, plasma concentrations of B-type natriuretic peptide (BNP), and echocardiographic left ventricular (LV) function measured at admission and discharge and their relationship to prognosis for AHF with preserved (HFpEF) or reduced (HFrEF) LV ejection fraction. Methods: Patients with AHF had the above tests done at admission and discharge. The primary outcome was re-hospitalization for heart failure or death at 6 months. Results: Of 162 patients enrolled, 95 had HFrEF and 67 had HFpEF, median age was 80 [77–85] years, and 85 (52%) were women. The number of B-lines at admission (median 31 [27–36]) correlated with respiratory rate (r = 0.75; p &lt; 0.001), BNP (r = 0.43; p &lt; 0.001), clinical congestion score (r = 0.25; p = 0.001), and systolic pulmonary artery pressure (r = 0.42; p &lt; 0.001). At discharge, B-lines were also correlated with BNP (r = 0.69; p &lt; 0.001) and congestion score (r = 0.57; p &lt; 0.001). B-line count at discharge predicted outcome (AUC 0.83 [0.77–0.90]; univariate HR 1.12 [1.09–1.16]; p &lt; 0.001; multivariable HR 1.16 [1.11–1.21]; p &lt; 0.001). Results were similar for HFpEF and HFrEF. Conclusions: LUS appears a useful method to assess severity and monitor the resolution of lung congestion. At hospital admission, B-lines are strongly related to respiratory rate, which may be a key component of the sensation of dyspnea. Measurement of lung congestion at discharge provides prognostic information for patients with either HFpEF or HFrEF

    Consensus of state of the art mortality prediction models: From all-cause mortality to sudden death prediction

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    Worldwide, many millions of people die suddenly and unexpectedly each year, either with or without a prior history of cardiovascular disease. Such events are sparse (once in a lifetime), many victims will not have had prior investigations for cardiac disease and many different definitions of sudden death exist. Accordingly, sudden death is hard to predict. This analysis used NHS Electronic Health Records (EHRs) for people aged ≥\geq50 years living in the Greater Glasgow and Clyde (GG\&C) region in 2010 (n = 380,000) to try to overcome these challenges. We investigated whether medical history, blood tests, prescription of medicines, and hospitalisations might, in combination, predict a heightened risk of sudden death. We compared the performance of models trained to predict either sudden death or all-cause mortality. We built six models for each outcome of interest: three taken from state-of-the-art research (BEHRT, Deepr and Deep Patient), and three of our own creation. We trained these using two different data representations: a language-based representation, and a sparse temporal matrix. We used global interpretability to understand the most important features of each model, and compare how much agreement there was amongst models using Rank Biased Overlap. It is challenging to account for correlated variables without increasing the complexity of the interpretability technique. We overcame this by clustering features into groups and comparing the most important groups for each model. We found the agreement between models to be much higher when accounting for correlated variables. Our analysis emphasises the challenge of predicting sudden death and emphasises the need for better understanding and interpretation of machine learning models applied to healthcare applications

    Interplay between right ventricular function and cardiac resynchronization therapy : an analysis of the CARE-HF trial (cardiac resynchronization–heart failure)

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    Objectives: The aim of this study was to investigate the impact of cardiac resynchronization therapy (CRT) on right ventricular (RV) function and the influence of RV dysfunction on the echocardiographic and clinical response to CRT among patients enrolled in the CARE-HF (Cardiac Resynchronization-Heart Failure) trial. Background: Cardiac resynchronization therapy prolongs survival in appropriately selected patients with heart failure but the benefit might be diminished in patients with RV dysfunction. Methods: Of 813 patients enrolled in the CARE-HF study, 688 had tricuspid plane systolic excursion (TAPSE) measured at baseline, and 345 of these were assigned to CRT. Their median (interquartile range) age was 66 (58 to 71) years, left ventricular (LV) ejection fraction was 24% (21% to 28%), and TAPSE was 19 (16 to 22) mm. Baseline LV function and size and QRS duration were similar among TAPSE tertiles, but those in the worst tertile (TAPSE < 17.4 mm) were more likely to have ischemic heart disease. Results: Overall, CRT improved LV but not RV structure and function with little evidence of an interaction with TAPSE. During a median (interquartile range) follow-up of 748 (582 to 950) days, 213 deaths occurred. Patients with lower TAPSE had a higher mortality, regardless of assigned treatment (p < 0.001). Greater inter-ventricular mechanical delay, New York Heart Association functional class, mitral regurgitation, and N-terminal pro-B-type natriuretic peptide, lower TAPSE, and assignment to the control group were independently associated with higher mortality. Reduction in mortality with CRT was similar in each tertile of TAPSE. Conclusions: Right ventricular dysfunction is a powerful determinant of prognosis among candidates for CRT, regardless of treatment assigned, but did not diminish the prognostic benefits of CRT among patients enrolled in the CARE-HF trial. (Care-HF CArdiac Resynchronization in Heart Failure; NCT00170300) © 2013 American College of Cardiology Foundation
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