Heart failure symptom clusters and functional status - a cross-sectional study

Symptom prevalence in patients with advanced heart failure and its association with quality of life and activities of daily living

BACKGROUND

Quality of life (QOL) and functional status are two key outcomes for patients with advanced heart failure (HF). We examined the association of eleven symptoms with QOL and functional status impairment in patients with advanced HF.

METHODS AND RESULTS

This was a retrospective analysis of baseline data from a multi-center, cluster-randomized controlled trial (NCT01459744) which enrolled patients with an implanted cardioverter-defibrillator and advanced HF at high-risk for mortality. Study instruments included the Condensed Memorial Symptom Assessment Scale, the Kansas City Cardiomyopathy Questionnaire QOL subscale, and the number of activities of daily living (ADL) patients had difficulties with. The study included 413 subjects. In generalized linear models which were adjusted for baseline characteristics, the total number of symptoms was significantly associated with worse QOL, as was the presence of each individual symptom, except constipation. Lack of energy demonstrated the strongest negative association with QOL. Similarly, the total number of symptoms was associated with a higher number of ADL difficulties (i.e., worse functional status). The presence of pain, lack of energy and drowsiness was individually associated with more ADL difficulties.

CONCLUSION

Among patients with advanced HF, a higher number of symptoms and specific individual symptoms were associated with worse QOL and functional status.

Identifying Palliative Care Needs in Patients With Heart Failure Using Patient Reported Outcomes

CONTEXT

Heart failure (HF) is considered a multifaceted and life-threatening syndrome characterized by high symptom-burden and significant mortality.

OBJECTIVES

To describe the symptom-burden in patients with HF and identify their palliative care needs. In this respect, symptom burden related to sex, age and classification of HF using New York Heart Association Functional Classification (NYHA) were analyzed.

METHODS

A cross-sectional questionnaire survey included adult HF patients according to NYHA II, III, and IV. Palliative care needs were assessed using validated patient reported outcomes measures; SF-36v1, HeartQoL, EORTC- QLQ-C15-PAL, MFI-20 and HADS. Patients were recruited from the Department of Cardiology, North Zealand Hospital, Denmark.

RESULTS

In total, 314 patients (79%) completed the questionnaire (233 men). Mean age = 74 years (range 35-94 years). In all, 42% had NYHA III or IV and 53% self-rated their health to be fair or poor. In all, 19% NYHA II and 67% NYHA III/IV patients had ≥4 severe palliative symptoms according to EORTC-QLQ-C15-PAL. In addition, NYHA III/IV had a mean of 8.9 symptoms and a mean of 5.4 severe symptoms. Women, older patients, and those with NYHA III/IV had worse outcomes regarding health-related quality of life, functional capacity, and symptom burden.

CONCLUSIONS

Patients with HF have a high prevalence of symptoms and, thus, potential palliative care needs. Predominantly, women, older patients, and those with higher severity of disease have the highest symptom burden. PROMs can help cardiologists address the palliative care needs and systematic assessment may be a prerequisite to integrate symptom-modifying and palliative care interventions.

Symptoms and negative emotions in patients with advanced thyroid cancer: a prospective cross-sectional study

BACKGROUND

There is no relevant research on the symptoms and emotions of patients with advanced thyroid cancer in mainland China.

AIM

To investigate the symptoms and negative emotions of patients with advanced thyroid cancer and to analyze the correlation between the two preliminarily.

METHODS

Using a convenience sampling method, 180 patients who visited a multidisciplinary outpatient service for advanced thyroid cancer at West China Hospital of Sichuan University from January 2023 to December 2023 were selected as the research subjects. A cross-sectional survey was conducted using the M.D. Anderson Symptom Inventory-Thyroid Cancer module (MDASI-THY) and Hospital Anxiety and Depression Scale (HADS). The correlation between symptom severity and negative emotions was determined by Spearman correlation analysis.

RESULTS

Disturbed sleep was the symptom with the highest incidence (74.4%) and the greatest severity (3.0 points), while mood distress was the symptom with the highest incidence (63.3%) and the greatest severity (2.0 points). 71 patients (39.4%) had anxiety, and 62 patients (34.4%) had depression. All symptoms and symptom interference were positively correlated with anxiety and depression (P < 0.05).

CONCLUSION

Patients with advanced thyroid cancer have multiple symptoms that seriously affect their daily lives and emotions. Medical staff should conduct targeted observation and preventive treatment to reduce the burden of symptoms and improve the negative emotions of patients.

Physical Heart Failure Symptom Clusters Predictive of Delay in Seeking Treatment

BACKGROUND

Recent research has focused on the relationship between heart failure (HF) symptom clusters and outcomes, including mortality, hospitalization, functional status, and quality of life. No known studies to date have explored the role of physical HF symptom clusters and delays in seeking treatment.

OBJECTIVES

Describe physical symptom clusters in a population of HF patients and determine if a specific cluster is predictive of delay in seeking treatment for HF symptoms.

METHOD

We analyzed combined data from two studies ( n = 406) collected during acute HF hospitalization. The Heart Failure Somatic Awareness Scale quantified physical HF symptoms. Delay, measured in days, was collected from the medical record and confirmed by interview. Hierarchical agglomerative clustering techniques determined physical HF symptom clusters. Hierarchical multiple regression analysis was computed to explore predictors of delay.

RESULTS

Participants were primarily White, male sex older adults. Three physical HF symptom clusters were identified: discordant, edema-related, and dyspnea-related symptoms. Hierarchical multiple regression analysis revealed in Step 1 that age was a significant predictor of delay.

DISCUSSION

Our findings provide valuable insight into the role of physical symptom clusters on delay in persons with HF. Through agglomerative hierarchical clustering techniques, we found three physical HF symptom clusters that were then used to determine differences in cluster membership by demographic and clinical variables. Significant age differences were noted by cluster membership with youngest older adults in a discordant symptom cluster.

The Effect of Heart Failure Symptom Clusters on Quality of Life: The Moderating Effect of Self-Care Behaviours

BACKGROUND

Although heart failure (HF) symptoms affect patients' quality of life (QoL), improving patients' QoL requires certain self-care behaviours. However, the specific role of self-care behaviours in the relationship between HF symptoms and QoL has not been clarified.

AIMS

To evaluate the status of symptom clusters, self-care behaviours and QoL in HF patients, and to analyse and test the moderating effect of self-care behaviours between symptom clusters and QoL.

DESIGN

This study is a cross-sectional study.

METHODS

A total of 320 HF patients who treated in the three hospitals in Chengdu, China, from December 2022 to July 2023 were selected as the research subjects. The patients were evaluated using The General Information Questionnaire, Memorial Symptom Assessment Scale Heart Failure, Self-Care of Heart Failure Index and Minnesota Living with Heart Failure Questionnaire. The statistical analysis methods were exploratory factor analysis, Pearson correlation analysis, hierarchical regression analysis and simple slope analysis.

RESULTS

There were five symptom clusters in HF patients: emotional symptom cluster (sadness, anxiety, irritability, feeling nervous), digestive symptom cluster (lack of appetite, dry mouth, weight loss, nausea, abdominal distension), ischemic symptom cluster (dizziness, chest pain, palpitations, fatigue), dyspnoea symptom cluster (difficulty breathing when lying flat, waking up breathless at night, sleep difficulty) and congestion symptom cluster (cough, shortness of breath, oedema). There was a significant correlation between HF symptom group, self-care behaviours and QoL (p < 0.05). Both self-care maintenance (β = -0.262, p < 0.001) and self-care management (β = -0.258, p < 0.001) had a moderating effect between symptom clusters and QoL.

CONCLUSION

There are a variety of symptom clusters in HF patients. Improving the self-care behaviours ability of HF patients is conducive to reducing the impact of HF symptom clusters on QoL.

REPORTING METHOD

The study used the STROBE checklist for reporting.

RELEVANCE TO CLINICAL PRACTICE

Medical staff should focus on the impact of HF symptom clusters and self-care behaviours on QoL, and formulate corresponding interventions for HF symptom clusters and self-care behaviours to improve the QoL of patients.

PATIENT OR PUBLIC CONTRIBUTION

The head nurse of the cardiovascular department actively assisted us in collecting questionnaires from HF patients, and all HF patients surveyed participated in this study seriously.

Functional Capacity, Functional Performance, and Symptoms in People With Heart Failure: An Integrative Review

BACKGROUND

Heart failure (HF) is a clinical syndrome that has a negative effect on functional status, a multidimensional concept characterizing one's ability to provide for the necessities of life. Symptoms might be associated with different aspects of functional status in HF. However, the terms functional capacity and performance have been misused interchangeably, and no previous review has focused on the extent to which symptoms contribute to functional capacity and performance among people with HF.

OBJECTIVE

The aim of this study was to comprehensively review and synthesize the existing literature on the relationship between symptoms, functional capacity, and functional performance in people with HF.

METHODS

We conducted an integrated review of observational studies in which authors examined the relationship between at least 1 symptom and at least 1 aspect of functional capacity or performance in people with HF 18 years or older. The Joanna Briggs Institute's critical appraisal tools were used to analyze the quality of studies.

RESULTS

We included 23 studies with 7219 participants and an age range of 40 to 86 years. Fifteen symptom measures were used to measure dyspnea, fatigue, pain, insomnia symptoms, depressive symptoms, and anxiety symptoms. Three functional capacity measures were assessed in 9 studies, and 7 functional performance measures were assessed in 17 studies. As often measured with the Six-Minute Walk Test, functional capacity was inversely associated with pain/discomfort, insomnia symptoms, and psychological symptoms. Functional performance, often measured by the New York Heart Association functional class and Medical Outcome Scale Short Form 36, was associated with sleep difficulties, fatigue, depressive symptoms, and anxiety. Four studies combined functional capacity and performance measures to elicit functional status. Depressive symptoms, fatigue, pain, and insomnia symptoms are associated with decreased functional performance and capacity.

CONCLUSIONS AND CLINICAL IMPLICATIONS

Commonly, symptoms experienced in HF are associated with declining functional status. However, this finding depends on the measures or metrics used to assess symptoms, functional capacity, and performance. The observed dissimilarities in the relationship between symptoms and functional capacity and performance highlight the conceptual distinctions, suggesting that authors of future studies should judiciously select appropriate dimensions and measures of functional status based on the study's purposes, design, and available resource.

Somatic symptom disorder symptoms in individuals at risk for heart failure: A cluster analysis with cross-sectional data from a population-based cohort study

OBJECTIVE

Identifying whether experienced symptom burden in individuals with medical predisposition indicates somatic symptom disorder (SSD) is challenging, given the high overlap in the phenomenology of symptoms within this group. This study aimed to enhance understanding SSD in individuals at risk for heart failure.

SUBJECTS AND METHODS

Cross-sectional data from the Hamburg City Health Study was analyzed including randomly selected individuals from the general population of Hamburg, Germany recruited from February 2016 to November 2018. SSD symptoms assessed with the Somatic Symptom Scale-8 and the Somatic Symptom Disorder-12 scale were categorized by applying cluster analysis including 412 individuals having at least 5% risk for heart failure-related hospitalization within the next ten years. Clusters were compared for biomedical and psychological factors using ANOVA and chi-square tests. Linear regressions, adjusting for sociodemographic, biomedical, and psychological factors, explored associations between clusters with general practitioner visits and quality of life.

RESULTS

Three clusters emerged: none (n = 215; 43% female), moderate (n = 151; 48% female), and severe (n = 46; 54% female) SSD symptom burden. The SSS-8 mean sum scores were 3.4 (SD = 2.7) for no, 6.4 (SD = 3.4) for moderate, and 12.4 (SD = 3.7) for severe SSD symptom burden. The SSD-12 mean sum scores were 3.1 (SD = 2.6) for no, 12.2 (SD = 4.2) for moderate, and 23.5 (SD = 6.7) for severe SSD symptom burden. Higher SSD symptom burden correlated with biomedical factors (having diabetes: p = .005 and dyspnea: p ≤ .001) and increased psychological burden (depression severity: p ≤ .001; anxiety severity: p ≤ .001), irrespective of heart failure risk (p = .202). Increased SSD symptoms were associated with more general practitioner visits (β = 0.172; p = .002) and decreased physical quality of life (β = -0.417; p ≤ .001).

CONCLUSION

Biomedical factors appear relevant in characterizing individuals at risk for heart failure, while psychological factors affect SSD symptom experience. Understanding SSD symptom diversity and addressing subgroup needs could prove beneficial.

An Evolutionary Concept Analysis in People With Heart Failure-Symptom Clusters or Symptom Cluster Profiles?

The concept of symptom clusters in heart failure (HF) has been defined and measured inconsistently. We used Rodgers' evolutionary method to review related concepts in the HF literature. Symptom clusters and symptom cluster profiles are characterized by multiple symptoms, a synergistic relationship, and result in a myriad of poor outcomes. Researchers should carefully consider the conceptual differences underpinning symptom clusters and symptom cluster profiles and choose the appropriate concept aligned with their research questions, empirical methods, and target HF population.

Correlates of cognition among people with chronic heart failure and insomnia

PURPOSE

This study aimed to describe cognitive characteristics and their associations with demographic and clinical factors among adults with chronic heart failure (HF) and insomnia.

METHODS

We performed a cross-sectional analysis of baseline data from the HeartSleep Study (NCT#02,660,385), a randomized controlled trial designed to evaluate the effects of cognitive-behavioral therapy for insomnia. Demographic characteristics and health history were obtained. We measured sleep characteristics with the Insomnia Severity Index, the PROMIS Sleep Disturbance Questionnaire, and wrist actigraphy. Sleepiness, stress, and quality of life were measured with validated questionnaires. Measures of cognition included frequency of lapses on the psychomotor vigilance test and the PROMIS cognitive abilities scale where ≥ 3 lapses and a score of ≤ 50, respectively, suggested impairment. These variables were combined into a composite score for multivariable analyses.

RESULTS

Of a sample that included 187 participants (58% male; mean age 63.1 [SD = 12.7]), 77% had New York Heart Association class I or II HF and 66% had HF with preserved ejection fraction. Common comorbidities were diabetes (35%), hypertension (64%), and sleep apnea (54%). Impaired vigilant attention was associated with non-White race, higher body mass index, less education, and more medical comorbidities. Self-reported cognitive impairment was associated with younger age, higher body mass index, and pulmonary disease. On adjusted analysis, significant risk factors for cognitive impairment included hypertension (OR 1.94), daytime sleepiness (OR 1.09), stress (OR 1.08), and quality of life (OR 0.12).

CONCLUSIONS

Impaired cognition is common among people with chronic HF and insomnia and associated with hypertension, daytime sleepiness, stress, and poor quality of life.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: Insomnia Self-management in Heart Failure; NCT#02,660,385.

Examining how congruence in and satisfaction with dyadic care type appraisal contribute to quality of life in heart failure care dyads

AIMS

Given the complexity of heart failure (HF) management, persons with HF and their informal caregivers often engage in dyadic illness management. It is unknown how congruent appraisal of dyadic HF care type is associated with dyadic health. Our aim was to examine how congruence in and satisfaction with appraisal of dyadic HF care type contribute to quality of life (QOL) for dyads.

METHODS AND RESULTS

This is a secondary analysis of cross-sectional data on 275 HF care dyads (patients 45.1% female, caregivers 70.5% female). Congruent appraisal and satisfaction were assessed using the Dyadic Symptom Management Type instrument. Quality of life was measured using the Short Form-12. Multilevel dyadic models were estimated to examine the contribution of congruence and satisfaction with dyadic care type to physical and mental QOL. Congruent appraisal of dyadic care type was positively associated with caregivers' mental QOL (B = 2.69, P = 0.026). Satisfaction with dyadic care type was positively associated with physical and mental QOL for persons with HF (B = 1.58, P = 0.011 and B = 2.09, P = 0.002, respectively) and informal caregivers (B = 1.70, P = 0.004 and B = 2.90, P < 0.001, respectively), while controlling for age, New York Heart Association class, daily hours spent together, relationship type, and congruence with dyadic care type.

CONCLUSION

Satisfaction with dyadic care type appraisal was a stronger contributor to QOL for HF care dyads, compared with congruent appraisals. It is important to understand reasons for dissatisfaction within the dyad to assist dyad members in reaching shared appraisals while managing HF.

Symptom clusters, associated factors and health-related quality of life in patients with chronic obstructive pulmonary disease: A structural equation modelling analysis

AIMS AND OBJECTIVES

To identify symptom clusters and develop a symptom cluster model among people living with chronic obstructive pulmonary disease (COPD).

BACKGROUND

The examination of symptom clusters in COPD patients is an emerging field of scientific inquiry directed towards symptom management. However, no studies have modelled the relationships among symptom clusters, associated factors and health-related quality of life.

DESIGN

A cross-sectional design with convenience sampling following STROBE guidelines.

METHODS

Data were collected from 450 COPD participants in three university teaching hospitals. Participants were invited to complete a structured questionnaire comprised of a socio-demographic/clinical questionnaire, Integrated Palliative Care Outcome Scale and Clinical Respiratory Questionnaire. Exploratory factor analysis and confirmatory factor analysis were used to identify symptom clusters. Structural equation modelling was used to examine the proposed model.

RESULTS

The respiratory related symptom cluster, psychological symptom cluster and cough-insomnia related symptom cluster were identified. The final model demonstrated a good fit with the data. Gender, stage of disease and monthly income were significant factors associated with symptom clusters. Respiratory related and cough-insomnia related symptom clusters had a direct negative impact on health-related quality of life, while the psychological symptom cluster was found to have a direct and indirect negative effect on health-related quality of life.

CONCLUSIONS

Final COPD symptom cluster model should serve as a framework to guide intervention research targeting symptom clusters to improve health-related quality of life of people living with COPD.

RELEVANCE TO CLINICAL PRACTICE

Nurses should be especially attuned to identify those at most risk of facing a higher symptom burden in this case those who are female, have advanced stage COPD and/or lower income. During the clinical symptom assessment, nurses should pay attention to the close relationships among symptoms within a cluster to identify any 'trigger' symptom that could cause the development or exacerbation of other symptoms.

Relationships between Depressive Symptoms, Appetite, and Quality of Life in Heart Failure

This analytical, cross-sectional study aimed to analyze the relationship between depressive symptoms, appetite, and quality of life (QoL) in 86 patients hospitalized with heart failure. Patients were assessed for depressive symptoms, appetite, and QoL using the Beck Depression Inventory-II, the Simplified Nutritional Appetite Questionnaire, and the Minnesota Living with Heart Failure Questionnaire, respectively. Relationships between sociodemographic and clinical variables, depressive symptoms, appetite, and QoL were analyzed using bivariate tests and linear regression models, with p < .05 considered significant. The factors associated with QoL were dependence for four activities of daily living (ADLs) (estimate = 15.4, 95% CI = 0.23 to 30.64, p = .046), minor depressive symptoms (estimate = –20.0, 95% CI = –28.3 to −11.73, p < .001), and appetite (estimate = –11.08, 95% CI = –20.5 to −1.62, p = .022). These results can support multi-professional assessment and development of interventions to promote better QoL, including addressing impaired appetite and food intake, the presence or increased intensity of depressive symptoms, especially in patients dependent for ADLs.

Identification of Distinct Symptom Profiles in Cancer Patients Using a Pre-Specified Symptom Cluster

CONTEXT

Pain, fatigue, sleep disturbance, and depression often co-occur in oncology patients and negatively impact quality of life (QOL).

OBJECTIVES

Study purposes were to identify subgroups of patients with distinct symptom profiles based on their experiences with a pre-specified symptom cluster (i.e., pain, fatigue, depression, sleep disturbance) and to identify demographic, clinical, and symptom characteristics and QOL outcomes associated with each distinct profile.

METHODS

Patients with breast, lung, gastrointestinal, and gynecologic cancers (n = 1340) were recruited from outpatient clinics during their first or second cycle of chemotherapy. They completed valid and reliable measures of pain, fatigue, sleep disturbance. depression, and QOL prior to their next dose of chemotherapy. Latent class profile analysis was used to identify the patient subgroups. Differences among the profiles were evaluated using parametric and non-parametric tests.

RESULTS

Three distinct profiles were identified (i.e., Low (44.0%), Moderate (45.1%), High (10.8%). Compared to Low class, Moderate and High classes were younger and more likely to be female. Compared to the other two classes, High class was less likely to be married/partnered and employed, more likely to have a lower income and childcare responsibilities, had lower functional status, a higher body mass index, and exercised less. For both QOL scales, differences in subscale and total scores followed the same pattern (Low>Moderate>High).

CONCLUSIONS

Over 55% of patients undergoing chemotherapy had a moderate to high symptom burden associated with these four common co-occurring symptoms. Multimodal interventions are needed to decrease symptom burden and improve QOL outcomes in these patients.

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.

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.

Machine learning for subtype definition and risk prediction in heart failure, acute coronary syndromes and atrial fibrillation: systematic review of validity and clinical utility

BACKGROUND

Machine learning (ML) is increasingly used in research for subtype definition and risk prediction, particularly in cardiovascular diseases. No existing ML models are routinely used for cardiovascular disease management, and their phase of clinical utility is unknown, partly due to a lack of clear criteria. We evaluated ML for subtype definition and risk prediction in heart failure (HF), acute coronary syndromes (ACS) and atrial fibrillation (AF).

METHODS

For ML studies of subtype definition and risk prediction, we conducted a systematic review in HF, ACS and AF, using PubMed, MEDLINE and Web of Science from January 2000 until December 2019. By adapting published criteria for diagnostic and prognostic studies, we developed a seven-domain, ML-specific checklist.

RESULTS

Of 5918 studies identified, 97 were included. Across studies for subtype definition (n = 40) and risk prediction (n = 57), there was variation in data source, population size (median 606 and median 6769), clinical setting (outpatient, inpatient, different departments), number of covariates (median 19 and median 48) and ML methods. All studies were single disease, most were North American (n = 61/97) and only 14 studies combined definition and risk prediction. Subtype definition and risk prediction studies respectively had limitations in development (e.g. 15.0% and 78.9% of studies related to patient benefit; 15.0% and 15.8% had low patient selection bias), validation (12.5% and 5.3% externally validated) and impact (32.5% and 91.2% improved outcome prediction; no effectiveness or cost-effectiveness evaluations).

CONCLUSIONS

Studies of ML in HF, ACS and AF are limited by number and type of included covariates, ML methods, population size, country, clinical setting and focus on single diseases, not overlap or multimorbidity. Clinical utility and implementation rely on improvements in development, validation and impact, facilitated by simple checklists. We provide clear steps prior to safe implementation of machine learning in clinical practice for cardiovascular diseases and other disease areas.

Chronic Obstructive Pulmonary Disease Symptom Cluster Composition, Associated Factors, and Methodologies: A Systematic Review

This systematic review details symptom clusters, their compositions, and associated factors and appraises the methodologies of studies that reported symptom clusters in patients with chronic obstructive pulmonary disease (COPD). Ten studies were eligible for inclusion in this study. Four common symptom clusters were identified. Two theoretical frameworks, four statistical methods, and various symptom assessment tools were used to identify symptom clusters. Factors associated with symptom clusters included demographic, clinical, and biological factors. No studies examined the subjective experiences of symptom clusters. Overall, inconsistencies were identified in the composition of symptom clusters across studies. This may be due to variations in study design, assessment tools, and statistical methods. Future studies should attempt to arrive at a common definition, especially that is theoretically derived, for symptom clusters, standardize the criteria for symptoms for inclusion in the clusters, and focus on patients' subjective experience to inform which clusters are clinically relevant.

Influence of physiological and psychological factors on cognitive dysfunction in heart failure patients

AIM

Our study aimed to examine factors that contribute to cognitive dysfunction in patients with heart failure (HF).

BACKGROUND

Although a majority of patients with HF have mild to moderate cognitive impairment, little is known about factors that influence progressive cognitive decline in this population.

METHODS

We examined the influence of physiological factors (NYHA functional class II - IV, ejection fraction, co-morbidity burden, polypharmacy), psychosocial factors (anxiety, depression, evaluation for advanced therapy), and associated toxicities (anticholinergic drug burden), on cognitive dysfunction. Data were analyzed using mean (SE) for continuous variables and frequency and percent for categorical variables. Differences between NYHA functional classification (Class II vs. Class III/IV) were examined using Chi Square. Linear regression models were used to assess associations among model variables.

RESULTS

Of the 113 participants with HF, Class III-IV HF were more cognitively impaired than those with NYHA Class II (p < 0.0001), had higher anxiety (p = 0.002), and depression (p = 0.003), and lower EF (p = 0.041). A majority of participants had a moderate anticholinergic drug burden, and NYHA Class III/IV participants had significantly higher medication counts than Class II participants (p = 0.034). Regression analysis found that NYHA Class III/IV, anxiety, depression and evaluation for advanced therapy significantly influenced cognitive dysfunction.

CONCLUSIONS

Findings support a high prevalence of cognitive dysfunction, anxiety, and depression in NYHA class II-IV with a greater level of cognitive dysfunction in class III/IV patients.

The Contribution of Living Arrangements, Social Support, and Self-efficacy to Self-management Behaviors Among Individuals With Heart Failure: A Path Analysis

BACKGROUND

Living arrangements, social support, and self-efficacy have significant implications for self-management science. Despite the theoretical linkages among the 3 concepts, there is limited empirical evidence about their interplay and the subsequent influence on heart failure (HF) self-management.

OBJECTIVE

The aim of this study was to validate components of the Individual and Family Self-management Theory among individuals with HF.

METHODS

This is a secondary analysis of cross-sectional data generated from a sample of 370 individuals with HF. A path analysis was conducted to examine the indirect and direct associations among social environment (living arrangements), social facilitation (social support) and belief (self-efficacy) processes, and self-management behaviors (HF self-care maintenance) while accounting for individual and condition-specific factors (age, sex, race, and HF disease severity).

RESULTS

Three contextual factors (living arrangements, age, and HF disease severity) had direct associations with perceived social support and self-efficacy, which in turn were positively associated with HF self-management behaviors. Living alone (β = -.164, P = .001) was associated with lower perceived social support, whereas being an older person (β = .145, P = .004) was associated with better support. Moderate to severe HF status (β = -.145, P = .004) or higher levels of perceived social support (β = .153, P = .003) were associated with self-efficacy.

CONCLUSIONS

Our results support the Individual and Family Self-management Theory, highlighting the importance of social support and self-efficacy to foster self-management behaviors for individuals with HF. Future research is needed to further explore relationships among living arrangements, perceived and received social support, self-efficacy, and HF self-management.

Functional status mediates the association of nutritional status with depressive symptoms in patients with heart failure

AIMS

The decline of nutritional status and depressive symptoms are pandemic in heart failure patients and functional status may play a pivotal role between these. This study aimed to determine whether nutritional status is associated with depressive symptoms and whether functional status mediates this relationship in heart failure patients.

DESIGN

This was a secondary analysis of a cross-sectional study.

METHODS

The data were collected from November 2015-April 2016. Heart failure patients (N = 254) being hospitalized were included in this secondary analysis. The Depression Sub-Scale of the Hospital Anxiety and Depression Scale and the Duke Activity Status Index were used to assess patients' depressive symptoms and functional status. The nutritional status of patients was calculated using the Geriatric Nutritional Risk Index.

RESULTS

In this study, the average scores of depressive symptoms, nutritional status and functional status were 4.91 (SD 3.12), 102.38 (SD 6.57) and 20.58 (SD 8.96) respectively. Out of the 254 patients, 46 patients (18.1%) had significant depressive symptoms (the score of Depression Sub-Scale of the Hospital Anxiety and Depression Scale ≥ 8) and 55 (21.7%) suffered from malnutrition (the score of Geriatric Nutritional Risk Index ≤ 98). In the multiple regression analyses, nutritional status was negatively associated with depressive symptoms (β = -0.142, p = .02) and functional status mediated the relationship between nutritional status and depressive symptoms.

CONCLUSIONS

Many patients with heart failure have malnutrition and depressive symptoms. Functional status plays a mediating role in the relationship between nutritional status and depressive symptoms.

IMPACT

To relieve depressive symptoms in patients with heart failure, it is of importance to improve the functional status, especially for those with poor nutritional status.

Symptom clusters and quality of life among patients with chronic heart failure: A cross-sectional study

AIM

This study aimed to identify symptom clusters among patients with chronic heart failure (HF) and examine their independent relationships with quality of life (QoL).

METHODS

A descriptive cross-sectional design was adopted, and 201 Chinese participants were recruited. Their symptom profiles and QoL were assessed using the Memorial Symptom Assessment Scale-Heart Failure and Minnesota Living with Heart Failure Questionnaire. Exploratory factor analysis was used to identify the symptom clusters. Pearson's correlation analysis and multiple regression analysis were conducted to examine their independent relationships with QoL.

RESULTS

Six distinct symptom clusters were identified: the fatigue, dyspneic, discomfort, congestive, ischemic, and emotional symptom clusters. These six symptom clusters accounted for 57.508% of the variance in patient symptom experiences and were positively related to their overall QoL. Moreover, the fatigue (β = .317, p < .001), dyspneic (β = .228, p < .001), congestive (β = .363, p < .001), and emotional (β = .200, p < .001) symptom clusters independently predicted QoL.

CONCLUSION

The six symptom clusters that were identified in this study and the relationships that they shared with QoL are expected to inform future approaches to symptom management. Interventions that target these symptom clusters will improve the QoL of patients with HF.

Multisymptom Profile Predicts Increased Risk of Poor Outcomes After Initial Placement of Implantable Cardioverter Defibrillator

CONTEXT

Patients with implantable cardioverter defibrillators (ICDs) are at risk for multiple physical and psychological symptoms. Identification of specific symptom profiles associated with poor outcomes may elucidate novel strategies to enhance symptom management.

OBJECTIVES

The objectives were to determine common symptoms after initial ICD implantation, identify classes of individuals with similar symptom profiles, describe patient characteristics associated with different symptom profiles, and determine if symptom profiles at hospital discharge predicted outcomes three and 12 months after implantation.

METHODS

This was a secondary data analysis of a randomized controlled trial that compared patient + partner versus patient-only interventions designed to help patients manage symptoms, prepare for ICD shocks, and resume daily activities. Symptoms were measured with the Patient Concerns Assessment. Latent class regression analysis was used to identify symptom classes at baseline, three-month, and 12-month follow-up. Associations between patient characteristics, class membership, and outcomes were examined using chi-square, analysis of variance, and Poisson regression.

RESULTS

The study included 301 patients (74% male, mean age 64 ± 11.9 years). Three classes were identified: Multi-Symptom (N = 119, 40%), Tired-Rundown (N = 130, 43%), and Mostly Asymptomatic (N = 52, 17%). Patients in the Multi-Symptom class were younger (59.9 years, P < 0.001) and reported more anxiety (P < 0.001) and depression (P < 0.01) than the other classes. Membership in the Multi-Symptom class predicted lower quality of life and resulted in nearly double the rate of hospitalizations after 12 months (P = 0.02, IRR 1.9).

CONCLUSION

Evaluation of symptom profiles after ICD implantation offers a promising strategy for identifying patients at risk for poor health outcomes.

Decision-tables for choosing commonly applied inferential statistical tests in comparative and correlation studies

BACKGROUND

Nurse researchers are increasingly using a wide variety of inferential statistical tests. However, novice researchers might find choosing tests for their studies difficult, as a result of this variety.

AIM

To present structured decision-tables to help choose which statistical tests to use in comparative and correlation studies.

DISCUSSION

The wide spectrum of statistical techniques the authors identified in nursing research helped them to construct overview tables that researchers could use as a simple tool to help choose appropriate statistical tests for their studies.

CONCLUSION

The decision-tables provided in this paper are unique in that they are composed of commonly applied statistical techniques identified in nursing studies and structured to simplify the pathway to statistical test decision-making for a broad spectrum of study designs.

IMPLICATIONS FOR PRACTICE

Novice nurse researchers can use the decision-tables presented in this paper as a starting point to explore with research colleagues or supervisors the appropriate choice of statistical techniques.

Patterns of multimorbid health conditions: a systematic review of analytical methods and comparison analysis

Background

The latest review of studies on multimorbidity patterns showed high heterogeneity in the methodology for identifying groups of multimorbid conditions. However, it is unclear how analytical methods used influence the identified multimorbidity patterns.

Methods

We undertook a systematic review of analytical methods used to identify multimorbidity patterns in PubMed and EMBASE from their inception to January 2017. We conducted a comparison analysis to assess the effect the analytical methods had on the multimorbidity patterns identified, using the Australian National Health Survey (NHS) 2007-08 data.

Results

We identified 13 194 studies and excluded 13 091 based on titles/abstracts. From the full-text reviews of the 103 remaining publications, we identified 41 studies that used five different analytical methods to identify multimorbid conditions in the studies. Thirty-seven studies (90%) adopted either the factor-analysis or hierarchical-clustering methods, but heterogeneity arises for the use of different proximity measures within each method to form clusters. Our comparison analysis showed the variation in identified groups of multimorbid conditions when applying the methods to the same NHS data. We extracted main similarities among the groupings obtained by the five methods: (i) cardiovascular and metabolic diseases, (ii) mental health problems and (iii) allergic diseases.

Conclusion

We showed the extent of effects for heterogeneous analytical methods on identification of multimorbidity patterns. However, more work is needed to guide investigators for choosing the best analytical method to improve the validity and generalizability of findings. Investigators should also attempt to compare results obtained by various methods for a consensus grouping of multimorbid conditions.

Influence of depression and gender on symptom burden among patients with advanced heart failure: Insight from the pain assessment, incidence and nature in heart failure study

INTRODUCTION

Patients with advanced heart failure (HF) experience many burdensome symptoms that increase patient suffering.

METHODS

Comparative secondary analysis of 347 patients with advanced HF. Symptom burden was measured with the Memorial Symptom Assessment Scale-HF. Depression was measured using the Patient Health Questionnaire-9.

RESULTS

Mean number of symptoms was 13.6. The three most frequent symptoms were non-cardiac pain, shortness of breath, and lack of energy. Patients with depression reported higher symptom burden. Symptom burden differed when compared by gender. Women reported higher symptom burden for other pain, dry mouth, swelling of the arms and legs, sweats, feeling nervous, nausea, and vomiting. Men reported higher symptom burden with sexual problems.

CONCLUSIONS

Given the high rates of symptoms and distress, interventions are needed to alleviate the symptom burden of patients with advanced HF. Reported symptom burden in patients with advanced heart failure was higher when depressive symptoms were present. Women reported varied number and severity of symptoms than men.

Symptom cluster among patients with advanced heart failure: a review of its manifestations and impacts on health outcomes

PURPOSE OF REVIEW

Assessment of symptom clustering is effective in enhancing care planning for symptom palliation in life-limiting disease. This review was aimed at identifying symptom cluster manifestation among advanced heart failure patients and to investigate the prognostic impact of the identified symptom clusters.

RECENT FINDINGS

A systematic search of the literature identified 10 relevant articles. Two approaches were undertaken based on: correlations between symptoms and shared characteristics of patients' symptom profiles, to identify the symptom clusters. By comparing the findings for heart failure patients at an advanced disease stage and those who were not, the symptom clusters of advanced heart failure were found to have unique characteristics. In particular, the typical symptoms associated with cardiac decompensation are not clustered together. Instead, dyspnoea is clustered with emotional symptoms indicating that a distressing dyspnoeic attack may reinforce awareness of the life-limiting nature of the disease and arouse negative emotions. In addition, the debilitating heart failure-specific symptoms share the cause of the life-limiting aspects in compromising patient vitality. The strong positive association between symptom burden and cardiac event prompts the need for effective intervention to palliate not only typical but also atypical and emotional symptoms of advanced heart failure.

SUMMARY

This review provides insight on potentially effective interventions for symptom palliation in advanced heart failure.

Acute Coronary Syndrome Symptom Clusters: Illustration of Results Using Multiple Statistical Methods

Researchers have employed various methods to identify symptom clusters in cardiovascular conditions, without identifying rationale. Here, we test clustering techniques and outcomes using a data set from patients with acute coronary syndrome. A total of 474 patients who presented to emergency departments in five United States regions were enrolled. Symptoms were assessed within 15 min of presentation using the validated 13-item ACS Symptom Checklist. Three variable-centered approaches resulted in four-factor solutions. Two of three person-centered approaches resulted in three-cluster solutions. K-means cluster analysis revealed a six-cluster solution but was reduced to three clusters following cluster plot analysis. The number of symptoms and patient characteristics varied within clusters. Based on our findings, we recommend using (a) a variable-centered approach if the research is exploratory, (b) a confirmatory factor analysis if there is a hypothesis about symptom clusters, and (c) a person-centered approach if the aim is to cluster symptoms by individual groups.

An integrative review of the theory of unpleasant symptoms

AIMS

The aim of this study was to explore how the theory of unpleasant symptoms (TOUS) has been used in the methodological design and analysis of symptom research.

DESIGN

An integrative review, using Whittemore and Knafl's approach.

DATA SOURCES

Searches were conducted between 26 January-10 February 2018. Databases included CINAHL Complete, PubMed, Proquest Nursing and Allied Health Source, Health Source: Nursing/Academic Edition, Academic Search Complete and Google Scholar.

REVIEW METHODS

A systematic approach to searching, screening and analysing the literature was applied. The matrix method, content analysis, constant comparison, counting and clustering were used.

RESULTS

Sixty-four records were included. Most studies were quantitative, cross-sectional, instrument-based and conducted in the USA. Various symptoms and patient populations were represented and each of the TOUS concepts were explored.

CONCLUSION

Although the theory has a role to play in furthering symptom science, attention should be paid to the areas of the model and of symptom research that have received less attention. More complex statistical approaches and big data will help to illuminate symptom experiences. Additional focus on intervention studies and all symptom dimensions will help to advance symptom science research.

IMPACT

This review is the first to provide a comprehensive, systematic summary of the uses of the TOUS across the research literature to date. This theory is a diverse, holistic middle-range theory capable of being applied to multiple symptoms and populations. Researchers should consider using the theory as a conceptual framework for studies to advance symptom science and explore symptoms holistically.

What's the Risk? Older Women Report Fewer Symptoms for Suspected Acute Coronary Syndrome than Younger Women

The purpose of the study was to determine whether older (≥65 years) and younger (<65 years) women presenting to the emergency department (ED) with symptoms suggestive of acute coronary syndrome (ACS) varied on risk factors, comorbid conditions, functional status, and symptoms that have implications for emergent cardiac care. Women admitted to five EDs were enrolled. The ACS Symptom Checklist was used to measure symptoms. Comorbid conditions and functional status were measured with the Charlson Comorbidity Index and Duke Activity Status Index. Logistic regression models were used to evaluate symptom differences in older and younger women adjusting for ACS diagnosis, functional status, body mass index (BMI), and comorbid conditions. Analyses were stratified by age, and interaction of symptom by age was tested. Four hundred women were enrolled. Mean age was 61.3 years (range 21–98). Older women (n = 163) were more likely to have hypertension, hypercholesterolemia, never smoked, lower BMI, more comorbid conditions, and lower functional status. Younger women (n = 237) were more likely to be members of minority groups, be college-educated, and have a non-ACS discharge diagnosis. Younger women had higher odds of experiencing chest discomfort, chest pain, chest pressure, shortness of breath, nausea, sweating, and palpitations. Lack of chest symptoms and shortness of breath (key symptoms triggering a decision to seek emergency care) may cause older women to delay seeking treatment, placing them at risk for poorer outcomes. Younger African American women may require more comprehensive risk reduction strategies and symptom management.

Symptom Clusters and Their Impacts on Hospital Readmission in Patients With Heart Failure: A Cross-Sectional Study

Background and Purpose:

Readmissions after hospitalization due to multiple symptoms in heart failure (HF) are common and costly. Patients have difficulty differentiating HF symptoms from comorbid illness or aging. Therefore, early identification of symptom clusters could improve symptom recognition and reduce hospital readmission. However, little is known about the relationship between symptom clusters and readmission in HF patients. This study aimed to identify symptom clusters among Korean patients with HF and the relationship between symptom clusters and hospital readmission.

Methods:

This cross-sectional study included 306 HF outpatients within 12 months after discharge. Exploratory factor analysis was used to identify the symptom clusters. Multiple logistic regression analysis was used to examine the effect of symptom clusters on readmission, after adjusting for sociodemographic and clinical characteristics.

Results:

Three symptom clusters were identified in HF patients: the “respiratory distress” cluster, “bodily pain and energy insufficiency” cluster, and “circulatory and gastrointestinal distress” cluster. Patients with class III or IV of HF functional class experienced three symptom clusters at a higher level. This study showed that the “bodily pain and energy insufficiency” cluster was the strongest predictor of hospital readmission in HF patients (adjusted odds ratio = 6.59, 95% confidence interval (CI) [1.29, 32.79]).

Implications for Practice:

A higher level of “bodily pain and energy insufficiency” cluster was associated with hospital readmission in Korean HF patients. Health-care providers should be encouraged to consider patients’ cultural backgrounds to recognize differences in symptom clusters. Further studies are needed to evaluate symptom clusters across international cohorts and their impacts on patients’ outcomes.

Heart Failure Symptoms Profile Associated With Depressive Symptoms

Heart failure (HF) symptoms are known to influence depressive symptoms, yet a symptom profile has not been identified. HF symptoms relative to symptom experience (frequency, severity, interference with physical activity and enjoyment of life) associated with depressive symptoms were examined. Data from three HF studies (N = 308) which used the Heart Failure Symptom Survey were included in this cross-sectional secondary analysis. Supervised classification for and identification of symptoms most associated with depressive symptoms were accomplished using random forest algorithms via conditional inference trees. The HF symptom profile associated with depressive symptoms across all four symptom experience domains included fatigue, dizziness, and forgetfulness/difficulty concentrating. Abdominal bloating, worsening cough, and difficulty sleeping were also important, but did not consistently rank in the top 5 for symptom importance relative to all symptom experience domains. Symptom profiling may enhance early identification of patients at risk for depressive symptoms and inform symptom management interventions.

The clinical epidemiology of fatigue in newly diagnosed heart failure

BACKGROUND

Fatigue is a common and distressing but poorly understood symptom among patients with heart failure (HF). This study sought to evaluate the prevalence, predictors, and prognostic value of clinically documented fatigue in newly diagnosed HF patients from the community.

METHODS

This retrospective cohort study consisted of 12,285 newly diagnosed HF patients receiving health care services through the Geisinger Health System, with passive data collection through electronic medical records (EMR). Incident HF, fatigue, and other study variables were derived from coded data within EMRs. A collection of 87 candidate predictors were evaluated to ascertain the strongest independent predictors of fatigue using logistic regression. Patients were followed for all-cause mortality for an average of 4.8 years. The associations between fatigue and 6-month, 12-month, and overall mortality were evaluated via Cox proportional hazards regression models.

RESULTS

Clinically documented fatigue was found in 4827 (39%) newly diagnosed HF patients. Depression demonstrated the strongest association with fatigue. Fatigue was often part of a symptom cluster, as other HF symptoms including dyspnea, chest pain, edema, syncope, and palpitations were significant predictors of fatigue. Volume depletion, lower body mass index, and abnormal weight loss were also strong predictors of fatigue. Fatigue was not significantly associated with either 6-month (HR = 1.12, p = 0.16) or overall mortality (HR = 1.00, p = 0.89) in adjusted models.

CONCLUSIONS

Fatigue is a commonly documented symptom among newly diagnosed HF patients, and its origins may lie in both psychologic and physiologic factors. Though fatigue did provide a prognostic signal in the short-term, this was largely explained by physiologic confounders. Proper therapeutic remediation of fatigue in HF relies on identifying underlying factors.

An Analysis and Evaluation of the Theory of Unpleasant Symptoms

The Theory of Unpleasant Symptoms was developed to enhance understanding of relationships among multiple symptoms and symptom experiences. Although the theory has been used to guide research, no formal critique of the theory has been published since 2000. This article comprehensively analyzes and evaluates the theory using Fawcett and DeSanto-Madeya's framework. Although its semantic clarity, semantic and structural consistency, and parsimony could be improved, the theory demonstrates good social and theoretical significance, testability, and empirical and pragmatic adequacy. Understanding multiple patient symptoms is essential, and the theory demonstrates that nurses should focus on multiple rather than individual symptoms.

Translation and evaluation of Chinese version of the symptom experience index

Symptom assessment is crucial for patient care through the entire disease trajectory. Patients often experience multiple symptoms concurrently. The symptom experience index is reliable and valid as an instrument developed in the USA for assessing multiple symptoms and distress. The aim of the study was to translate and evaluate the Chinese version of the instrument in healthy adults and oncology patients. This is a psychometric study with a cross-sectional design. To ensure the semantic equivalence and content validity, an integrative translation method was employed to translate the English version into Chinese language. The participants were recruited during 2014 from a large university, two university-affiliated hospitals and a community in Changchun, China. The Chinese version demonstrated high internal consistency, test-retest reliability and content validity. Construct validity was supported by factor analysis and significant differences of symptom experience scores between healthy and oncology groups. Participants' acceptance of the Chinese version and its ability to collect adequate data among Chinese population provided evidence for using this version among Chinese population. This study provided initial evidence to support the psychometric properties of the Chinese version. The Chinese version demonstrated adequate reliability and validity to assess multiple symptom experience by Chinese populations.

Symptom clusters and quality of life among patients with advanced heart failure

Objectives

To identify symptom clusters among patients with advanced heart failure (HF) and the independent relationships with their quality of life (QoL).

Methods

This is the secondary data analysis of a cross-sectional study which interviewed 119 patients with advanced HF in the geriatric unit of a regional hospital in Hong Kong. The symptom profile and QoL were assessed by using the Edmonton Symptom Assessment Scale (ESAS) and the McGill QoL Questionnaire. Exploratory factor analysis was used to identify the symptom clusters. Hierarchical regression analysis was used to examine the independent relationships with their QoL, after adjusting the effects of age, gender, and comorbidities.

Results

The patients were at an advanced age (82.9 ± 6.5 years). Three distinct symptom clusters were identified: they were the distress cluster (including shortness of breath, anxiety, and depression), the decondition cluster (fatigue, drowsiness, nausea, and reduced appetite), and the discomfort cluster (pain, and sense of generalized discomfort). These three symptom clusters accounted for 63.25% of variance of the patients' symptom experience. The small to moderate correlations between these symptom clusters indicated that they were rather independent of one another. After adjusting the age, gender and comorbidities, the distress (β = −0.635, P < 0.001), the decondition (β = −0.148, P = 0.01), and the discomfort (β = −0.258, P < 0.001) symptom clusters independently predicted their QoL.

Conclusions

This study identified the distinctive symptom clusters among patients with advanced HF. The results shed light on the need to develop palliative care interventions for optimizing the symptom control for this life-limiting disease.