Understanding and Measuring Symptom Burden in Heart Failure: A Concept Analysis

2019 ◽  
Vol 41 (10) ◽  
pp. 1423-1447 ◽  
Author(s):  
Macy L. Stockdill ◽  
Patricia A. Patrician ◽  
Marie Bakitas
Keyword(s):  
Heart Failure ◽  
Hospital Admissions ◽  
Negative Impact ◽  
Symptom Burden ◽  
Concept Analysis ◽  
Symptom Experience ◽  
Heart Failure Symptom ◽  
Failure Classification ◽  
Measurement Strategies ◽  
No Gold Standard

Heart failure is a common, complex, and costly condition accompanied by a high degree of symptom burden. The concept of heart failure symptom burden has been used and measured inconsistently in research. To develop effective symptom management and palliation strategies, a clear conceptual understanding is needed. Rodgers’ evolutionary method of concept analysis was used to identify articles in CINAHL, Embase, Scopus, and PubMed focused on chronic heart failure. Analysis of 20 articles revealed key attributes (subjectivity, negative impact on daily life and/or overall functioning, synergistic symptom associations, and symptom exacerbation), related terms (symptom distress and symptom experience), a surrogate term (heart failure burden), antecedents (heart failure classification or stage), and consequences (increased morbidity/mortality, decreased functioning, increased symptom prevalence/severity, decreased quality of life, and recurrent hospital admissions). No gold standard for measurement was identified. Research is needed to validate heart failure symptom burden measurement strategies across populations.

scholarly journals Exercise-Based Rehabilitation Delivery Models in Comorbid Chronic Pulmonary Disease and Chronic Heart Failure

2021 ◽  
Vol 8 ◽  
Author(s):  
Audrey Borghi-Silva ◽  
Adriana S. Garcia-Araújo ◽  
Eliane Winkermann ◽  
Flavia R. Caruso ◽  
Daniela Bassi-Dibai ◽  
...  
Keyword(s):  
Heart Failure ◽  
Chronic Heart Failure ◽  
Pulmonary Disease ◽  
Exercise Capacity ◽  
Aging Process ◽  
Hospital Admissions ◽  
Negative Impact ◽  
Hospital Readmissions ◽  
Chronic Obstructive ◽  
Delivery Models

Among the most prevalent multimorbidities that accompany the aging process, chronic obstructive pulmonary disease (COPD) and chronic heart failure (CHF) stand out, representing the main causes of hospital admissions in the world. The prevalence of COPD coexistence in patients with CHF is higher than in control subjects, given the common risk factors associated with a complex process of chronic diseases developing in the aging process. COPD-CHF coexistence confers a marked negative impact on mechanical-ventilatory, cardiocirculatory, autonomic, gas exchange, muscular, ventilatory, and cerebral blood flow, further impairing the reduced exercise capacity and health status of either condition alone. In this context, integrated approach to the cardiopulmonary based on pharmacological optimization and non-pharmacological treatment (i.e., exercise-based cardiopulmonary and metabolic rehabilitation) can be emphatically encouraged by health professionals as they are safe and well-tolerated, reducing hospital readmissions, morbidity, and mortality. This review aims to explore aerobic exercise, the cornerstone of cardiopulmonary and metabolic rehabilitation, resistance and inspiratory muscle training and exercise-based rehabilitation delivery models in patients with COPD-CHF multimorbidities across the continuum of the disease. In addition, the review address the importance of adjuncts to enhance exercise capacity in these patients, which may be used to optimize the gains obtained in these programs.

scholarly journals Meditation interventions among heart failure patients: An integrative review

2019 ◽  
Vol 18 (8) ◽  
pp. 720-728 ◽  
Author(s):  
Jennifer Viveiros ◽  
Brianna Chamberlain ◽  
Aminda O’Hare ◽  
Kristen A Sethares
Keyword(s):  
Quality Of Life ◽  
Heart Failure ◽  
Symptom Burden ◽  
The United States ◽  
Future Research ◽  
Meditation Practice ◽  
Heart Failure Patients ◽  
Heart Failure Symptom ◽  
Definition Of

Background: There has been growing interest in meditation techniques as an intervention in chronic disease populations. Little is known of the effect meditation practice has on outcomes among patients with heart failure. Purpose: To identify and examine current literature on meditation interventions on heart failure outcomes. Method: The review utilized methods described by Whittemore and Knafl. Three electronic databases were searched through March 2018. Terms used were “mindfulness OR meditation” and “heart failure” in combination, generating 58 articles after duplicates were removed. After inclusion and exclusion criteria were applied, six studies qualified for review, including four articles with samples from the United States and two with samples from Brazil and Sweden, respectively. Results: Among the six studies in the final sample, the total number of participants was 320 heart failure patients. Interventional design and length varied among the studies, and 20 different dependent variables were identified. This study distinguished four categories of outcome measures with significant findings: psychosocial, biophysical, quality of life and heart failure symptom burden. Compared with controls meditation practice significantly improved depression ( p<.05), social support ( p<.05), biophysical factors and quality of life ( p<.05), in addition to reducing heart failure symptom burden. Across-study comparisons were limited due to variation in intervention definitions and designs. Additionally, the intervention dose and reporting method varied, limiting comparisons. The sample size in five out of six studies was fewer than 50 participants. Over 20 different measures were used across the six studies to measure outcome variables. Conclusion: Meditation may offer a patient-driven practice to reduce heart failure symptoms as well as improve psychosocial wellness and quality of life. Future research among heart failure patients should include the following: rigorous definition of meditation interventions, consistency in intervention characteristics, larger controlled trials, and standardized outcome instruments.

scholarly journals Readmissions in elderly patients with heart failure. A retrospective study

2020 ◽  
Vol 6 (4) ◽  
Author(s):  
Rita Vieira Alves ◽  
Marília Fernandes ◽  
Inês Figueiredo ◽  
Diogo Drummond Borges ◽  
Filipa Louenço
Keyword(s):  
Quality Of Life ◽  
Heart Failure ◽  
Retrospective Study ◽  
Elderly Patients ◽  
Primary Outcome ◽  
Hospital Admissions ◽  
Symptom Burden ◽  
Natural Progression ◽  
Clinical Records

Heart failure is a major cause of morbidity and mortality worldwide. The prevalence increases with age and usually progresses, leading to repeated hospital admissions and significant symptom burden for patients. The correct management of these patients may decrease readmissions and increase quality of life. Our aim is to compare elderly patients with and without 1-year readmissions in an internal medicine ward, particularly in terms of mortality. Retrospective study, consulting patient’s clinical records, with a diagnosis of heart failure. The patients were characterized and divided in groups: with (wR) and without readmission (woR) within 1 year. Mortality was the primary outcome. Eighty-nine patients were included; 60 woR and 29 wR. There was no gender difference between groups, the wR group had older patients. The most frequent comorbidities included atrial fibrillation, hypertension and chronic renal failure stage 3 or higher. The most frequent cause of hospitalization was heart failure due to insufficient therapy or natural progression of the disease. The etiology of heart failure was mainly hypertensive and ischemic. The wR group had more patients classified as NYHA >III. In relation to the primary outcome; mortality at 12 months was higher in the group with repeated admissions. The characterization of this population allows us to highlight the causes of decompensation and to review medication in order to increase the quality of life.

scholarly journals Biomarkers-based personalized follow-up in chronic heart failure improves patient’s outcomes and reduces care associate cost

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Antonio Leon-Justel ◽  
Jose I. Morgado Garcia-Polavieja ◽  
Ana Isabel Alvarez-Rios ◽  
Francisco Jose Caro Fernandez ◽  
Pedro Agustin Pajaro Merino ◽  
...  
Keyword(s):  
Heart Failure ◽  
Hospital Admissions ◽  
Left Ventricular ◽  
Left Ventricular Ejection ◽  
Secondary Outcome ◽  
Ventricular Ejection Fraction ◽  
Number Of Patients ◽  
Ed Visits ◽  
The Impact

Abstract Background Heart failure (HF) is a major and growing medical and economic problem, with high prevalence and incidence rates worldwide. Cardiac Biomarker is emerging as a novel tool for improving management of patients with HF with a reduced left ventricular ejection fraction (HFrEF). Methods This is a before and after interventional study, that assesses the impact of a personalized follow-up procedure for HF on patient’s outcomes and care associated cost, based on a clinical model of risk stratification and personalized management according to that risk. A total of 192 patients were enrolled and studied before the intervention and again after the intervention. The primary objective was the rate of readmissions, due to a HF. Secondary outcome compared the rate of ED visits and quality of life improvement assessed by the number of patients who had reduced NYHA score. A cost-analysis was also performed on these data. Results Admission rates significantly decreased by 19.8% after the intervention (from 30.2 to 10.4), the total hospital admissions were reduced by 32 (from 78 to 46) and the total length of stay was reduced by 7 days (from 15 to 9 days). The rate of ED visits was reduced by 44% (from 64 to 20). Thirty-one percent of patients had an improved functional class score after the intervention, whereas only 7.8% got worse. The overall cost saving associated with the intervention was € 72,769 per patient (from € 201,189 to € 128,420) and €139,717.65 for the whole group over 1 year. Conclusions A personalized follow-up of HF patients led to important outcome benefits and resulted in cost savings, mainly due to the reduction of patient hospitalization readmissions and a significant reduction of care-associated costs, suggesting that greater attention should be given to this high-risk cohort to minimize the risk of hospitalization readmissions.

External validation of a heart failure risk prediction model in a remote monitoring cohort submitted to cardiac resynchronization therapy

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
I Cardoso ◽  
M Coutinho ◽  
G Portugal ◽  
A Valentim ◽  
A.S Delgado ◽  
...  
Keyword(s):  
Heart Failure ◽  
Heart Rate ◽  
High Risk ◽  
Remote Monitoring ◽  
Hospital Admissions ◽  
External Validation ◽  
Left Ventricular Ejection ◽  
National Database ◽  
Failure Risk

Abstract Background Patients (P) submitted to cardiac ressynchronization therapy (CRT) are at high risk of heart failure (HF) events during follow-up. Continuous analysis of various physiological parameters, as reported by remote monitoring (RM), can contribute to point out incident HF admissions. Tailored evaluation, including multi-parameter modelling, may further increase the accuracy of such algorithms. Purpose Independent external validation of a commercially available algorithm (“Heart Failure Risk Status” HFRS, Medtronic, MN USA) in a cohort submitted to CRT implantation in a tertiary center. Methods Consecutive P submitted to CRT implantation between January 2013 and September 2019 who had regular RM transmissions were included. The HFRS algorithm includes OptiVol (Medtronic Plc., MN, USA), patient activity, night heart rate (NHR), heart rate variability (HRV), percentage of CRT pacing, atrial tachycardia/atrial fibrillation (AT/AF) burden, ventricular rate during AT/AF (VRAF), and detected arrhythmia episodes/therapy delivered. P were classified as low, medium or high risk. Hospital admissions were systematically assessed by use of a national database (“Plataforma de Dados de Saúde”). Accuracy of the HFRS algorithm was evaluated by random effects logistic regression for the outcome of unplanned hospital admission for HF in the 30 days following each transmission episode. Results 1108 transmissions of 35 CRT P, corresponding to 94 patient-years were assessed. Mean follow-up was 2.7 yrs. At implant, age was 67.6±9.8 yrs, left ventricular ejection fraction 28±7.8%, BNP 156.6±292.8 and NYHA class &gt;II in 46% of the P. Hospital admissions for HF were observed within 30 days in 9 transmissions. Stepwise increase in HFRS was significantly associated with higher risk of HF admission (odds ratio 12.7, CI 3.2–51.5). HFRS had good discrimination for HF events with receiving-operator curve AUC 0.812. Conclusions HFRS was significantly associated with incident HF admissions in a high-risk cohort. Prospective use of this algorithm may help guide HF therapy in CRT recipients. Funding Acknowledgement Type of funding source: None

scholarly journals How different combinations of comorbidities affect healthcare use by elderly patients with obstructive lung disease

2021 ◽  
Vol 31 (1) ◽  
Author(s):  
Alessandra Buja ◽  
Andrea Bardin ◽  
Giulia Grotto ◽  
Stefania Elvini ◽  
Pietro Gallina ◽  
...  
Keyword(s):  
Heart Failure ◽  
Elderly Patients ◽  
Lung Disease ◽  
Ambulatory Care ◽  
Obstructive Lung Disease ◽  
Hospital Admissions ◽  
Large Population ◽  
Healthcare Resources ◽  
Outpatient Visits ◽  
Common Causes

AbstractPrevious research had shown the number of comorbidities is a major factor influencing the burden of care for elderly patients with obstructive lung disease (OLD). This retrospective cohort study on a large population of elderly patients (age > 65 years) with OLD in northern Italy measures the use of healthcare resources associated with the most frequent combinations of comorbidities and investigates the most common reasons for hospitalization. Total health costs, pharmacy costs, emergency department (ED) visits, outpatient visits, and hospital admissions are assessed for every subject. The most common causes of hospitalization by a number of comorbidities and the most common sets of three comorbidities are identified. For each comorbidity group, we rank a list of the most frequent causes of hospitalization, both overall and avoidable with effective ambulatory care. A small group of patients suffering from major comorbidities accounts for the use of most healthcare resources. The most frequent causes of hospitalization are respiratory failure, heart failure, chronic bronchitis, and bronchopneumonia. The most common conditions manageable with ambulatory care among causes of hospitalizations are heart failure, bacterial pneumonia, and COPD. The set of three comorbidities responsible for the highest average total costs, and the highest average number of hospitalizations and outpatient visits comprised hypertension, cardiac arrhythmias, and heart failure. The main reasons for hospitalization proved to remain linked to heart failure and acute respiratory disease, regardless of specific combinations of comorbidities. Based on these findings, specific public health interventions among patients with OLD cannot be advised on the basis of specific sets of comorbidities only.

scholarly journals Invasive Devices and Sensors for Remote Care of Heart Failure Patients

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2014
Author(s):  
Sumant P. Radhoe ◽  
Jesse F. Veenis ◽  
Jasper J. Brugts
Keyword(s):  
Heart Failure ◽  
Remote Monitoring ◽  
Hospital Admissions ◽  
Acute Decompensated Heart Failure ◽  
Admission Rate ◽  
Decompensated Heart Failure ◽  
Hospital Admission Rate ◽  
Remote Care ◽  
New Sensors ◽  
Near Future

The large and growing burden of chronic heart failure (CHF) on healthcare systems and economies is mainly caused by a high hospital admission rate for acute decompensated heart failure (HF). Several remote monitoring techniques have been developed for early detection of worsening disease, potentially limiting the number of hospitalizations. Over the last years, the scope has been shifting towards the relatively novel invasive sensors capable of measuring intracardiac filling pressures, because it is believed that hemodynamic congestion precedes clinical congestion. Monitoring intracardiac pressures may therefore enable clinicians to intervene and avert hospitalizations in a pre-symptomatic phase. Several techniques have been discussed in this review, and thus far, remote monitoring of pulmonary artery pressures (PAP) by the CardioMEMS (CardioMicroelectromechanical system) HF System is the only technique with proven safety as well as efficacy with regard to the prevention of HF-related hospital admissions. Efforts are currently aimed to further develop existing techniques and new sensors capable of measuring left atrial pressures (LAP). With the growing body of evidence and need for remote care, it is expected that remote monitoring by invasive sensors will play a larger role in HF care in the near future.

scholarly journals Why do frail patients with chronic heart failure die and become hospitalised?

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
S Sze ◽  
P Pellicori ◽  
J Zhang ◽  
J Weston ◽  
A.L Clark
Keyword(s):  
Heart Failure ◽  
Cause Of Death ◽  
Hospital Admissions ◽  
Average Length ◽  
Significant Proportion ◽  
Length Of Hospital Stay ◽  
Clinical Frailty Scale ◽  
Frail Patients ◽  
Increased Risk

Abstract Background Frailty is common in patients with heart failure (HF) and is associated with increased morbidity and mortality. A better understanding of the causes of hospitalisations and death in frail patients might help to tailor interventional strategies for these at-risk patients. Purpose We studied the cause of death and hospitalisations in ambulatory patients with HF and frailty. Methods We assessed frailty using the clinical frailty scale (CFS) in consecutive HF patients attending a routine follow-up visit. Those with CFS ≥5 were classified as frail. Mortality and hospitalisations were ascertained from medical records (updated systematically using an NHS electronic database), discharge letters, autopsy reports and death certificates. We studied the primary cause of death and hospitalisations within one year of enrolment. Results 467 patients (67% male, median (IQR) age 76 (69–82) years, median (IQR) NT-proBNP 1156 (469–2463) ng/L) were enrolled. 206 (44%) patients were frail. Frail patients were more likely to not receive or receive suboptimal doses of ACEi/ARB and Beta-blockers; while non-frail patients were more likely to be treated with optimal doses. At 1-year follow up, there were 56 deaths and 322 hospitalisations, of which 46 (82%) and 215 (67%) occurred in frail patients. Frailty was associated with an increased risk of all-cause mortality (HR (95% CI): 4.27 (2.60–7.01)) and combined mortality/ hospitalisation (HR (95% CI): 2.85 (2.14–3.80)), all p&lt;0.001. 57% (n=26) of frail patients died of cardiovascular causes (of which 58% were due to HF progression); although deaths due to non-cardiovascular causes (43%, n=20), especially severe infections, were also common (26%, n=12). (Figure 1) The proportion of frail patients who had non-elective hospital admissions within 1 year was more than double that of non-frail patients (46% (n=96) vs 21% (n=54); p&lt;0.001). Compared to non-frail patients, frail patients had more recurrent (≥2) hospitalisations (28% (n=59) vs 9% (n=24); p&lt;0.001) but median (IQR) average length of hospital stay was not significantly different (frail: 6 (4–11) vs non-frail: 6 (2–12) days, p=0.50). A large proportion of hospitalisations (64%, n=137) in frail patients were due to non-cardiovascular causes (of which 34%, 30% and 20% were due to infections, falls and comorbidities respectively). Of cardiovascular hospitalisations (36%, n=78), the majority were due to decompensated HF (67%, n=46). (Figure 1) Conclusion Frailty is common in patients with HF and is associated with an increased risk of mortality and recurrent hospitalisations. A significant proportion suffered non-cardiovascular deaths and hospitalisations. This implies that interventions targeted at HF alone can only have limited impact on outcomes in frail patients. Figure 1 Funding Acknowledgement Type of funding source: None

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