Cross-classification of physical and affective symptom clusters and 180-day event-free survival in moderate to advanced heart failure

Cluster analysis of heart failure patients based on their psychological and physical symptoms and predictive analysis of cluster membership

AIM

Patients with heart failure experience multiple co-occurring symptoms that lower their quality of life and increase hospitalization and mortality rates. So far, no heart failure symptom cluster study recruited patients from community settings or focused on symptoms predicting most clinical outcomes. Considering physical and psychological symptoms together allows understanding how they burden patients in different combinations. Moreover, studies predicting symptom cluster membership using variables other than symptoms are lacking. We aimed to (a) cluster heart failure patients based on physical and psychological symptoms and (b) predict symptom cluster membership using sociodemographic/clinical variables.

DESIGN

Secondary analysis of MOTIVATE-HF trial, which recruited 510 heart failure patients from a hospital, an outpatient and a community setting in Italy.

METHODS

Cluster analysis was performed based on the two scores of the Hospital Anxiety-Depression scale and two scores of the Heart-Failure Somatic Perception Scale predicting most clinical outcomes. ANOVA and chi-square test were used to compare patients' characteristics among clusters. For the predictive analysis, we split the data into a training set and a test set and trained three classification models on the former to predict patients' symptom cluster membership based on 11 clinical/sociodemographic variables. Permutation analysis investigated which variables best predicted cluster membership.

RESULTS

Four clusters were identified based on the intensity and combination of psychological and physical symptoms: mixed distress (high psychological, low physical symptoms), high distress, low distress and moderate distress. Clinical and sociodemographic differences were found among clusters. NYHA-class (New York Heart Association) and sleep quality were the most important variables in predicting symptom cluster membership.

CONCLUSIONS

These results can support the development of tailored symptom management intervention and the investigation of symptom clusters' effect on patient outcomes. The promising results of the predictive analysis suggest that such benefits may be obtained even when direct access to symptoms-related data is absent.

IMPLICATIONS

These results may be particularly useful to clinicians, patients and researchers because they highlight the importance of addressing clusters of symptoms, instead of individual symptoms, to facilitate symptom detection and management. Knowing which variables best predict symptom cluster membership can allow to obtain such benefits even when direct access to symptoms-data is absent.

IMPACT

Four clusters of heart failure patients characterized by different intensity and combination of psychological and physical symptoms were identified. NYHA class and sleep quality appeared important variables in predicting symptom cluster membership.

REPORTING METHOD

The authors have adhered to the EQUATOR guidelines STROBE to report observational cross-sectional studies.

PATIENT OR PUBLIC CONTRIBUTION

Patients were included only for collecting their data.

Sympathetic dysfunction is associated with worse fatigue and early and subtle symptoms in heart failure: an exploratory sex-stratified analysis

AIMS

Physical symptoms impact patients with heart failure (HF) despite treatment advancements; however, our understanding of the pathogenic mechanisms underlying HF symptoms remains limited, including sex differences therein. The objective of this study was to quantify associations between sympathetic markers [norepinephrine (NE) and 3,4-dihydroxyphenylglycol (DHPG)] and physical symptoms in patients with HF and to explore sex differences in these associations.

METHODS AND RESULTS

We performed a secondary analysis of combined data from two studies: outpatients with HF (n = 111), and patients prior to left ventricular assist device implantation (n = 38). Physical symptoms were measured with the Heart Failure Somatic Perception Scale (HFSPS) dyspnoea and early/subtle symptom subscales and the Functional Assessment in Chronic Illness Therapy Fatigue Scale (FACIT-F) to capture dyspnoea, early symptoms of decompensation, and fatigue. Norepinephrine and DHPG were measured with high-performance liquid chromatography with electrochemical detection. Multivariate linear regression was used to quantify associations between symptoms and sympathetic markers. The sample (n = 149) was 60.8 ± 15.7 years, 41% women, and 71% non-ischaemic aetiology. Increased plasma NE and NE:DHPG ratio were associated with worse FACIT-F scores (P = 0.043 and P = 0.013, respectively). Increased plasma NE:DHPG ratio was associated with worse HFSPS early/subtle symptoms (P = 0.025). In sex-stratified analyses, increased NE:DHPG ratio was associated with worse FACIT-F scores (P = 0.011) and HFSPS early/subtle scores (P = 0.022) among women but not men.

CONCLUSION

In patients with HF, sympathetic dysfunction is associated with worse fatigue and early/subtle physical symptoms with associations stronger in women than men.

Symptom Burden and Quality of Life Among Patients With Heart Failure

Introduction

Heart failure is a debilitating condition that is associated with several burdensome symptoms that impede patients' quality of life. However, patients' experience of distressing symptoms and their impacts on their quality of life is not studied in Jordan.

Objectives

To assess the severity of distressing symptoms and to assess the relationships between these symptoms and the quality of life among patients with heart failure in Jordan.

Methods

A descriptive cross-sectional design was used. A convenience sampling approach was used to recruit the participants. Heart failure patients (n  =  167) who visited the outpatient clinics in three hospitals in Amman between July and November 2021 were included. The Edmonton Symptom Assessment System and Short-Form 36 tool were used.

Results

Participants were more likely males with a mean age of 55.2 years (SD  =  13.7). The most distressing symptoms among patients with heart failure were tiredness (M  =  4.56, SD  =  3.24), worse well-being (M  =  4.34, SD  =  2.52), and drowsiness (M  =  3.5, SD  =  3.06), respectively. Symptoms burden were negatively associated with the physical and the mental components summary of the quality of life. Pain, tiredness, nausea, loss of appetite, anxiety, and poor well-being were significant predictors of the physical components. The predictors of the mental components were tiredness, nausea, loss of appetite, and anxiety.

Conclusions

This study revealed that patients with heart failure facing significant symptom burden. The patients showed inadequate quality of life in both physical and mental components that were inversely associated with symptom burden. Given the debilitating effects of symptom burden on heart failure patients' quality of life, therefore, symptom assessment and management have to be a priority.

State of the Science: The Relevance of Symptoms in Cardiovascular Disease and Research: A Scientific Statement From the American Heart Association

Symptoms of cardiovascular disease drive health care use and are a major contributor to quality of life. Symptoms are of fundamental significance not only to the diagnosis of cardiovascular disease and appraisal of response to medical therapy but also directly to patients' daily lives. The primary purpose of this scientific statement is to present the state of the science and relevance of symptoms associated with cardiovascular disease. Symptoms as patient-reported outcomes are reviewed in terms of the genesis, manifestation, and similarities or differences between diagnoses. Specifically, symptoms associated with acute coronary syndrome, heart failure, valvular disorders, stroke, rhythm disorders, and peripheral vascular disease are reviewed. Secondary aims include (1) describing symptom measurement methods in research and application in clinical practice and (2) describing the importance of cardiovascular disease symptoms in terms of clinical events and other patient-reported outcomes as applicable.

The prognostic impact of symptom clusters in patients with heart failure: A systematic review and meta-analysis

AIM

To determine the impact of symptom clusters on clinical outcomes among heart failure patients.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

Peer-reviewed articles were searched from 12 English and Chinese language databases from inception to August 2021.

REVIEW METHODS

Narrative syntheses were first conducted to integrate symptom clusters reported in the identified studies. This was followed by meta-analysis to synthesize the evidence on the association or predictive effects of symptom clusters on clinical outcomes.

RESULTS

Twelve studies were identified. Among studies which identified highly correlated symptoms as in a cluster, meta-analysis indicated that severe congestive (r = .45, 95% CI = 0.38-0.52), weary (r = .41, 95% CI = 0.33-0.50), ischaemic (r = .29, 95% CI = 0.04-0.51) and stress-related (r = .62, 95% CI = 0.31-0.81) symptom clusters were correlated with a poorer health-related quality of life. As for studies used latent class to identified patient cohorts of similar symptom pattern, high symptom cohorts (hazard ratio = 1.86, 95% CI = 1.39-2.48) and incongruent physical and psycho-cognitive symptom cohorts was associated with a significantly higher risk (hazard ratio = 2.10, 95% CI = 1.44-3.07) of combined event rate relative to low symptom presentation.

CONCLUSIONS

This review has identified the impact of symptom clusters on clinical outcomes in heart failure patients. In addition to the classical physical symptoms highlighted in the clinical management guidelines, our findings suggested the important predictive role of psycho-cognitive and weary symptoms in determining the clinical outcomes of HF patients.

IMPACT

This review concluded the promising prospect of symptom clusters in shaping clinical outcomes of heart failure. The findings highlighted the importance of integrating care to minimize the disease impact on psycho-cognitive function and weary symptoms among this clinical cohort. The review also inform the direction on how to advance the knowledge on symptom clusters among this clinical cohort.

Background and Design of the Biological and Physiological Mechanisms of Symptom Clusters in Heart Failure (BIOMES-HF) Study

BACKGROUND

Symptoms, which often cluster together, are a significant problem in heart failure (HF). There is considerable heterogeneity in symptom burden, particularly in the vulnerable transition period after a hospitalization for HF, and the biological underpinnings of symptom during transitions are unclear. The purpose of this paper is to describe the background and design of a study that addresses these knowledge gaps, entitled "Biological and Physiological Mechanisms of Symptom Clusters in Heart Failure" (BIOMES-HF).

STUDY DESIGN AND METHODS

BIOMES-HF is a prospective gender- and age-balanced longitudinal study of 240 adults during the 6-month transition period after a HF hospitalization. The aims are to: 1) identify clusters of change in physical symptoms, 2) quantify longitudinal associations between biomarkers and physical symptoms, and 3) quantify longitudinal associations between physical frailty and physical symptoms among adults with heart failure. We will measure multiple symptoms, biomarkers, and physical frailty at discharge and then at 1 week and 1, 3, and 6 months post-hospitalization. We will use growth mixture modeling and longitudinal mediation modeling to examine changes in symptoms, biomarkers, and physical frailty post-HF hospitalization and associations therein.

CONCLUSIONS

This innovative study will advance HF symptom science by utilizing a multi-biomarker panel and the physical frailty phenotype to capture the multifaceted nature of HF. Using advanced quantitative modeling, we will characterize heterogeneity and identify potential mechanisms of symptoms in HF. As a result, this research will pinpoint amenable targets for intervention to provide better, individualized treatment to improve symptom burden in HF.

BRIEF LAY SUMMARY

Adults with heart failure may have significant symptom burden. This study is designed to shed light on our understanding of the role of biological and physiological mechanisms in explaining heart failure symptoms, particularly groups of co-occurring symptoms, over time. We will explore how symptoms, biomarkers, and physical frailty changes after a heart failure hospitalization. The knowledge generated from this study will be used to guide the management and self-care for adults with heart failure.

Age and gender differences in physical heart failure symptom clusters

BACKGROUND

Gender differences exist in structure and function of the heart resulting in HF symptom variation. Previous HF symptom cluster research described symptom clusters that were linked to functional status, mortality, quality of life and rehospitalization. Age and gender differences between cluster groups were described in one study.

OBJECTIVES

Identify physical HF symptom clusters and explore age and gender differences between clusters.

METHODS

Secondary analysis study of adults with HF. Cluster analysis was conducted using hierarchical agglomerative clustering techniques. A pictorial dendrogram output displays clusters.

RESULTS

Three symptom clusters were identified in this sample of 133 older HF patients that differed by gender (p = 0.04), age (p = 0.00) and beta blocker use (p = 0.01). Symptom clusters were consistent with worsening HF, acute HF and chronic HF.

CONCLUSION

Symptom clusters differ by age and gender. Education should be directed at increasing patient awareness of their individual symptom clusters.

Uncertainty levels differ by physical heart failure symptom cluster

BACKGROUND

The role of uncertainty, unpredictable symptoms, and unknown illness trajectory are frequent concerns reported in heart failure (HF) literature. Illness uncertainty can lead to difficulty interpreting symptoms, potentially impacting outcomes. Impaired functional status, quality of life, all-cause mortality, rehospitalization, and event-free survival are predicted by symptom clusters. No studies to date describe levels of uncertainty by physical symptom cluster in HF.

AIMS

Describe physical HF symptom clusters and determine if uncertainty levels differ by symptom cluster.

METHODS

Results are based on a secondary analysis of data from patients hospitalized with an acute exacerbation of HF. The Heart Failure Somatic Perception Scale (HFSPS) and Mishel's Uncertainty in Illness Scale (MUIS-C) were completed. Symptom clusters were determined by hierarchical agglomerative clustering. Controlling for age and gender, ANCOVA (post hoc LSD) analyses explored uncertainty levels by symptom cluster group.

RESULTS

One hundred and thirty-three primarily older (76.4 ± 12.1), Caucasian (92.5%) adults (55.2% male), with an ischemic HF etiology (71.6%) were enrolled. Three clusters were found: 1. Shortness of breath, n = 47, 2. Edema, n = 39, and 3. Cardiac, n = 43. Adjusting for age and gender, uncertainty levels differed by cluster group (p ≤ 0.001), with edema cluster members reporting greater illness uncertainty than cardiac cluster members (74.6 vs 69.5, respectively, p = 0.033).

CONCLUSIONS

Differences exist in illness uncertainty levels based on the symptom experience of patients with HF. Care and management of HF symptoms should include a complete assessment of unique symptom cluster profiles.