Symptom clusters predict event-free survival in patients with heart failure

Identifying palliative care needs in patients with heart failure using patient reported outcomes

CONTEXT

Heart failure (HF) is considered a multi-faceted 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 yrs (range 35-94 yrs). 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 ahigh 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.

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.

Psychosomatic mechanisms of heart failure symptoms on quality of life in patients with chronic heart failure: A multi-centre cross-sectional study

AIMS

To determine the contributions of different kinds of symptoms to the quality of life and mediating effect of psychological and physical symptoms between heart failure symptoms and quality of life.

DESIGN

A multi-centre cross-sectional study.

METHODS

2006 chronic heart failure patients from four cities were recruited in China from January 2021 to December 2022. Patients' symptoms and quality of life were self-reported, and data were analysed using correlation analysis, dominance analysis and mediating effects analysis.

RESULTS

The dominance analysis revealed that the overall mean contributions of heart failure, psychological and physical symptoms were .083, .085 and .111; 29.5%, 30.2% and 39.5% of the known variance. And heart failure symptoms could negatively affect quality of life through psychological and physical symptoms, accounting for 28.39% and 22.95% of the total effect. Heart failure symptoms could also affect quality of life through the chain-mediated effect of physical and psychological symptoms, accounting for 16.74%.

CONCLUSIONS

Physiological symptoms had the strongest effect on quality of life and heart failure symptoms had the weakest. Most of the effect for heart failure symptoms on quality of life in chronic heart failure patients was mediated by psychological and physiological symptoms.

RELEVANCE TO CLINICAL PRACTICE

It is important to design non-pharmacological intervention plans for the enhancement of physical and psychological symptoms' management skills, to reduce the adverse impact of heart failure symptoms on quality of life.

REPORTING METHOD

Study methods and results reported in adherence to the STROBE checklist.

NO PATIENT OR PUBLIC CONTRIBUTION

No patients or members of the public were involved in the study.

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.

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.

Physical Symptoms, Depressive Symptoms, and Quality of Life in Patients With Heart Failure: Cluster Analysis

BACKGROUND

Physical and psychological symptoms are prevalent in patients with heart failure (HF) and are associated with poor quality of life (QOL) and high hospitalization rates. Thus, it is critical to identify symptom clusters to better manage patients with high-risk symptom cluster(s) and to reduce adverse effects.

OBJECTIVE

The aims of this study were to identify clusters of physical HF symptoms (ie, dyspnea during daytime, dyspnea when lying down, fatigue, chest pain, edema, sleeping difficulty, and dizziness) and depressive symptoms and to examine their association with QOL in patients with HF.

METHODS

In this secondary analysis of a cross-sectional study, data on physical HF symptoms (Symptom Status Questionnaire), depressive symptoms (Patient Health Questionnaire-9), and general QOL (European Quality of Scale-Visual Analog Scale) were collected. We identified clusters based on the physical HF symptoms and depressive symptoms using 2-step and k -means cluster analysis methods.

RESULTS

Chest pain was removed from the model because of the low importance value. Two clusters were revealed (cluster 1, severe symptom cluster, vs cluster 2, less severe symptom cluster) based on the 7 symptoms. In cluster 1, all of the 7 symptoms were more severe, and QOL was poorer than those in cluster 2 (all P s < .001). All the mean and median scores of the 7 symptoms in cluster 1 were higher than those in cluster 2.

CONCLUSIONS

Patients with HF were clearly divided into 2 clusters based on physical HF symptoms and depressive symptoms, which were associated with QOL. Clinicians should assess these symptoms to improve patient outcomes.

Symptom Cluster Profiles Among Adults with Insomnia and Heart Failure

OBJECTIVE/BACKGROUND

Both heart failure (HF) and insomnia are associated with high symptom burden that may be manifested in clustered symptoms. To date, studies of insomnia have focused only on its association with single symptoms. The purposes of this study were to: (1) describe daytime symptom cluster profiles in adults with insomnia and chronic HF; and (2) determine the associations between demographic and clinical characteristics, insomnia and sleep characteristics and membership in symptom cluster profiles.

PARTICIPANTS

One hundred and ninety-five participants [M age 63.0 (SD12.8); 84 (43.1%) male; 148 (75.9%) New York Heart Association Class I/II] from the HeartSleep study (NCT0266038), a randomized controlled trial of the sustained effects of cognitive behavioral therapy for insomnia (CBT-I).

METHODS

We analyzed baseline data, including daytime symptoms (fatigue, pain, anxiety, depression, dyspnea, sleepiness) and insomnia (Insomnia Severity Index), and sleep characteristics (Pittsburgh Sleep Quality Index, wrist actigraphy). We conducted latent class analysis to identify symptom cluster profiles, bivariate associations, and multinomial regression.

RESULTS

We identified three daytime symptom cluster profiles, physical (N = 73 participants; 37.4%), emotional (N = 12; 5.6%), and all-high symptoms (N = 111; 56.4%). Body mass index, beta blockers, and insomnia severity were independently associated with membership in the all-high symptom profile, compared with the other symptom profile groups.

CONCLUSIONS

Higher symptom burden is associated with more severe insomnia in people with stable HF. There is a need to understand whether treatment of insomnia improves symptom burden as reflected in transition from symptom cluster profiles reflecting higher to lower symptom burden.

Acupuncture as a post-stroke treatment option: A narrative review of clinical guideline recommendations

BACKGROUND

Acupuncture may be useful to treat the various clusters of symptoms occurring after a stroke. The use of evidence to underpin clinical practice and treatment guidelines (CPGs and TGs respectively) varies from country to country and may affect what recommendations are made by guideline developers.

PURPOSE

To examine the extent to which international clinical and treatment guidelines on post-stroke treatment mention the role of acupuncture and to identify what symptoms they recommend for its use.

METHOD

Scoping of national and international websites of CPGs and TGs r on the after care and rehabilitation of stroke patients provided by professional and government organisations was conducted. The presence/absence of recommendations and the underpinning evidence was appraised for the use of acupuncture for symptoms following stroke.

RESULTS

Of 84 CPGs and TGs on post stroke after-care identified from 27 countries between 2001 and 2021, 49 made statements about acupuncture. Positive recommendations on the use of acupuncture were identified for 15 symptom areas from 11 countries for: stroke rehabilitation, dysphagia, shoulder pain, motor recovery, walking, balance, spasticity, upper limb extremity impairment, post-stroke pain, central post stroke pain, cognitive disorder, depression, and sleep problems. Thirty-five CPGs (2001-2018) from 18 countries published over the same period were identified that made no mention of acupuncture and therefore no recommendations were made on its use.

CONCLUSIONS

Currently, evidence used by international guideline developers varies and this influences whether a positive or negative recommendation is made. Recommendations to use acupuncture should be based on the best available evidence which has been quality appraised.

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.

Classical Massage and Relaxation Exercise on Symptom Status and Quality of Life in Advanced Stage Patients With Heart Failure: A Randomized Controlled Trial

This randomized controlled study aimed to investigate the effects of classical massage (CM) and Benson relaxation exercise (BRE) on symptom status and quality of life (QoL) in patients with heart failure (HF). Seventy-two patients with HF were recruited from 4 hospitals in Ankara, Turkey. The study sample was allocated to a CM (n = 24), BRE (n = 26), or control group (n = 22) based on the New York Heart Association classification of HF (stages III and IV) through stratified randomization. The intervention groups received either CM or BRE twice daily for 7 days (total of 14 sessions). The control group received only routine care. The scores of symptom status decreased in the CM and BRE groups at the end of the intervention (first week) as compared with the control group (P < .05). Nevertheless, at the end of the monitoring period, no significant differences were detected between the 3 study groups at baseline (P = .474), week 1 (P = .936), and week 3 (P = .668) in terms of QoL scores. The CM and BRE showed beneficial effects in the management of HF symptoms in advanced stage HF patients who were hospitalized and received intensive treatment.

Diversity and molecular network patterns of symptom phenotypes

Symptom phenotypes have continuously been an important clinical entity for clinical diagnosis and management. However, non-specificity of symptom phenotypes for clinical diagnosis is one of the major challenges that need be addressed to advance symptom science and precision health. Network medicine has delivered a successful approach for understanding the underlying mechanisms of complex disease phenotypes, which will also be a useful tool for symptom science. Here, we extracted symptom co-occurrences from clinical textbooks to construct phenotype network of symptoms with clinical co-occurrence and incorporated high-quality symptom-gene associations and protein-protein interactions to explore the molecular network patterns of symptom phenotypes. Furthermore, we adopted established network diversity measure in network medicine to quantify both the phenotypic diversity (i.e., non-specificity) and molecular diversity of symptom phenotypes. The results showed that the clinical diversity of symptom phenotypes could partially be explained by their underlying molecular network diversity (PCC = 0.49, P-value = 2.14E-08). For example, non-specific symptoms, such as chill, vomiting, and amnesia, have both high phenotypic and molecular network diversities. Moreover, we further validated and confirmed the approach of symptom clusters to reduce the non-specificity of symptom phenotypes. Network diversity proposes a useful approach to evaluate the non-specificity of symptom phenotypes and would help elucidate the underlying molecular network mechanisms of symptom phenotypes and thus promotes the advance of symptom science for precision health.

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.

Appetite and Nutritional Status as Potential Management Targets in Patients with Heart Failure with Reduced Ejection Fraction-The Relationship between Echocardiographic and Biochemical Parameters and Appetite

This study aimed to investigate the role of appetite loss and malnutrition in patients with heart failure with reduced ejection fraction (HFrEF). In this prospective, observational, single-center study, we enrolled 120 consecutive adults with HFrEF. We analyzed the selected clinical, echocardiographic, and biochemical parameters. Appetite loss and malnutrition were assessed by CNAQ (Council on Nutrition Appetite Questionnaire) and MNA (Mini Nutritional Assessment)/GNRI (Geriatric Nutritional Risk Index) questionnaires, respectively.Most patients were men (81.7%), mean age was 55.1 ± 11.3 years, and mean left ventricular ejection fraction was 23.9 ± 8.0%. The mean CNAQ score was 28.8 ± 3.9, mean MNA-23.1 ± 2.6, and mean GNRI-113.0 ± 12.3. Based on ROC curves, we showed that a sodium concentration <138 mmol/L had the greatest discriminating power for diagnosing impaired nutritional status (MNA ≤ 23.5) with a sensitivity of 54.5% and specificity of 77.8%. The threshold of HDL <0.97 mmol/L characterized 40.7% sensitivity and 86% specificity, B-type natriuretic peptide >738.6 pg/dL had 48.5% sensitivity and 80.8% specificity, high-sensitivity C-reactive protein >1.8 mg/L had 94.9% sensitivity and 42.9% specificity, and bilirubin >15 µmol/L had 78.2% sensitivity and 56.9% specificity. Nutritional status and appetite assessed by MNA/GNRI and CNAQ questionnaires showed poor correlations with other findings in HFrEF patients.

The Prevalence of Complementary and Integrative Health Approach Use and Quality of Life Among Patients With Heart Failure: A Cross-sectional, Descriptive, and Comparative Study

This study aimed to determine the prevalence of complementary and integrative health approach (CIHA) use in patients with heart failure (HF) and compare quality of life (QoL) between CIHA users and nonusers. This was a cross-sectional, descriptive, and comparative study including 130 patients with HF in Turkey. The data were collected using the sociodemographic and CIHA information form and the Kansas City Cardiomyopathy Questionnaire (KCCQ). The mean age was 64.51 ± 10.40 years. Furthermore, 26.1% of the participants had used at least one form of CIHA in the previous year. The most used CIHA was herbal therapies (94.2%). The total scores of the KCCQ were 47.70 ± 9.50 in the study, and a statistically significant difference was found in the total scores of the KCCQ between CIHA users and nonusers. The findings of this study revealed that more than a quartile of patients with HF used at least one form of CIHA. Further prospective studies are warranted to follow up with patients having HF who use any form of CIHA for a longer period and determine other parameters that directly influence QoL.

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.

Symptom clusters in hospitalized older adults: Characteristics and outcomes

Hospital care in medical patients relies mostly on objective measures with limited assessment of subjective symptoms. We subgrouped 331 hospitalized older adults with medical diagnosis (age 75.5 ± 7.1) according to the severity of multiple symptoms to explore if these subgroups differed in health-related characteristics on admission and functional outcomes one month post-discharge. Cluster analysis identified three subgroups based on experiences with five highly distressing symptoms (fatigue, dyspnea, dizziness, sleep disturbance, pain): low levels of all symptoms, high levels of all symptoms; moderate levels of four symptoms with high dyspnea. Belonging in different subgroups was accompanied by different levels of cognitive and mental, but not physical or health status. Patients in the subgroup "Moderate Levels with High Dyspnea" had significantly lower risk of decline in post-discharge instrumental activities of daily living than other subgroups. Better understanding of older hospitalized adults' symptom profiles may yield important information on health condition and recovery.

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.

Integrating Symptoms Into the Middle-Range Theory of Self-Care of Chronic Illness

The Middle-Range Theory of Self-Care of Chronic Illness has been used widely since it was first published in 2012. With the goal of theoretical refinement in mind, we evaluated the theory to identify areas where the theory lacked clarity and could be improved. The concept of self-care monitoring was determined to be underdeveloped. We do not yet know how the process of symptom monitoring influences the symptom appraisal process. Also, the manner in which self-care monitoring and self-care management are associated was thought to need refinement. As both of these issues relate to symptoms, we decided to enrich the Middle-Range Theory with knowledge from theories about symptoms. Here, we propose a revision to the Middle-Range Theory of Self-Care of Chronic Illness where symptoms are clearly integrated with the self-care behaviors of self-care maintenance, monitoring, and management.

Perceived Control Predicts Symptom Status in Patients With Heart Failure

BACKGROUND

Symptom status is an important indicator of disease progression in patients with heart failure (HF). Perceived control is a target of most self-care interventions and is associated with better outcomes in HF; however, little is known about the relationship between perceived control and symptom status in patients with HF.

OBJECTIVE

The aims of this study were to (1) determine the relationship of perceived control to HF symptom status and (2) examine the associations of perceived control to self-care and of self-care to symptom status.

METHODS

A total of 115 patients with HF were included. Data on symptom status (Memorial Symptom Assessment Scale-HF), perceived control (Control Attitudes Scale-Revised), and self-care (Self-Care of Heart Failure Index) were collected. Other covariates included were age, gender, New York Heart Association class, comorbidity burden, and depressive symptoms. Multiple regression analyses were performed to analyze the data.

RESULTS

Lower perceived control predicted worse symptom status after controlling for covariates (P = .009). Other covariates predictive of worse symptom status were younger age, New York Heart Association class III/IV, and higher levels of depressive symptoms. Higher levels of perceived control were associated with better self-care (P = .044). Better self-care was associated with better symptom status (P = .038).

CONCLUSIONS

Lower levels of perceived control were independently associated with worse symptom status in patients with HF. Intervention strategies targeting perceived control should be tested to determine whether they could improve symptom status.

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

BACKGROUND

The relationship between physical and affective symptom clusters in heart failure (HF) is unclear.

OBJECTIVES

To identify associations between physical and affective symptom clusters in HF and to quantify outcomes and determinants of symptom subgroups.

METHODS

This was a secondary analysis of data from two cohort studies among adults with HF. Physical and affective symptom clusters were compared using cross-classification modeling. Cox proportional hazards modeling and multinomial logistic regression were used to identify outcomes and determinants of symptom subgroups, respectively.

RESULTS

In this young, mostly male sample (n = 274), physical and affective symptom clusters were cross-classified in a model with acceptable fit. Three symptom subgroups were identified: congruent-mild (69.3%), incongruent (13.9%), and congruent-severe (16.8%). Compared to the congruent-mild symptom group, the incongruent symptom group had significantly worse 180-day event-free survival.

CONCLUSION

Congruence between physical and affective symptom clusters should be considered when identifying patients at higher risk for poor outcomes.

Implant Strategy-Specific Changes in Symptoms in Response to Left Ventricular Assist Devices

BACKGROUND

Although we know that the quality of life generally improves after left ventricular assist device (LVAD) implantation, we know little about how symptoms change in response to LVAD.

METHODS

The purpose of this study was to compare the changes in symptoms between bridge and destination therapy patients as part of a prospective cohort study. Physical (dyspnea and wake disturbances) and affective symptoms (depression and anxiety) were measured before LVAD and at 1, 3, and 6 months after LVAD. Multiphase growth modeling was used to capture the 2 major phases of change: initial improvements between preimplant and 1 month after LVAD and subsequent improvements between 1 and 6 months after LVAD.

RESULTS

The sample included 64 bridge and 22 destination therapy patients as the preimplant strategy. Destination patients had worse preimplant dyspnea and wake disturbances, and they experienced greater initial improvements in these symptoms compared with bridge patients (all P < .05); subsequent change in both symptoms were similar between groups (both P > .05). Destination patients had worse preimplant depression (P = .042) but experienced similar initial and subsequent improvements in depression in response to LVAD compared with bridge patients (both P > .05). Destination patients had similar preimplant anxiety (P = .279) but experienced less initial and greater subsequent improvements in anxiety after LVAD compared with bridge patients (both P < .05).

CONCLUSION

There are many differences in the magnitude and timing of change in symptom responses to LVAD between bridge and destination therapy patients. Detailed information on changes in specific symptoms may better inform shared decision-making regarding LVAD.

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.

Patients’ Beliefs About Causes and Consequences of Heart Failure Symptoms

Patients’ perceptions of the causes and consequences of heart failure (HF) symptoms may impact effective self-management. The purpose of this study was to describe and explore patients’ perceptions of HF symptom status and the causes and consequences on their daily lives in patients with HF. Descriptive and qualitative data were obtained from 20 patients using a semistructured interview guide. Data were analyzed using content analysis and descriptive statistics. Participants reported 15 symptoms (median = 4). Five themes were (a) multiple causes and multiple symptoms; (b) knowing some causes, but still unclear; (c) not being able to live life as previously did; (d) facing emotional distress due to HF symptoms; and (e) development of new priorities and lifestyles. The findings demonstrate that all participants perceived considerable difficulties living with HF symptoms. More comprehensive interventions need to be delivered to patients to manage multiple causes and symptoms effectively.

Atrial fibrillation symptom clusters and associated clinical characteristics and outcomes: A cross-sectional secondary data analysis

BACKGROUND

Symptom clusters among adults with atrial fibrillation have previously been identified but no study has examined the relationship between symptom clusters and outcomes.

AIMS

The purpose of this study was to identify atrial fibrillation-specific symptom clusters, characterize individuals with each cluster, and determine whether symptom cluster membership is associated with healthcare utilization.

METHODS

This was a cross-sectional secondary data analysis of 1501 adults from the Vanderbilt Atrial Fibrillation Registry with verified atrial fibrillation. Self-reported symptoms were measured with the University of Toronto Atrial Fibrillation Severity Scale. We used hierarchical cluster analysis (Ward's method) to identify clusters and dendrograms, pseudo F, and pseudo T-squared to determine the ideal number of clusters. Next, we used regression analysis to examine the association between cluster membership and healthcare utilization.

RESULTS

Males predominated (67%) and the average age was 58.4 years. Two symptom clusters were identified, a Weary cluster (3.7%, n=56, fatigue at rest, shortness of breath at rest, chest pain, and dizziness) and an Exertional cluster (32.7%, n=491, shortness of breath with activity and exercise intolerance). Several sociodemographic and clinical characteristics varied by symptom cluster group membership, including age, gender, atrial fibrillation type, body mass index, comorbidity status, and treatment strategy. Women were more likely to experience either cluster ( p<0.001). The Weary cluster was associated with nearly triple the rate of emergency department utilization (incident rate ratio [IRR] 2.8, p<0.001) and twice the rate of hospitalizations (IRR 1.9, p<0.001).

CONCLUSION

We identified two symptom clusters. The Weary cluster was associated with a significantly increased rate of healthcare utilization.

Uncertainty and depressive symptoms as mediators of quality of life in patients with heart failure

Uncertainty in illness is regarded as a source of stress in many chronic diseases and is negatively related to health-related quality of life (HRQoL). However, studies on the relationship between uncertainty and HRQoL in patients with heart failure are limited. This study used Mishel's theory of uncertainty in illness to investigate the mediating role of uncertainty in illness and depressive symptoms between symptom distress and HRQoL in patients with heart failure. This study used a cross-sectional correlation design. Participants were recruited by convenience sampling from outpatient services and medical wards of cardiology departments of a medical center in northern Taiwan. Data were collected for uncertainty, depressive symptoms, symptoms distress of heart failure, and HRQoL using self-report questionnaires. Demographics and clinical characteristics were analyzed with descriptive statistics. The mutual effects of disease characteristics, symptom distress, uncertainty in illness, depressive symptoms and HRQoL, as well as the overall model fitness, were analyzed by with structural equation modeling. We collected 147 qualified questionnaires. The mean score for the Mishel Uncertainty in Illness Scale for patients with heart failure was 73.5 (SD = 18.55); 65.3% of participants had a score of ≧13 on the Beck Depressive Inventory-II, indicating mild depression. Uncertainty, depressive symptoms, and HRQoL were directly related to symptom distress. Symptom distress and depressive symptoms were both mediators between uncertainty and depressive symptoms. Depressive symptoms also mediated emotional support and HRQoL. Uncertainty and depressive symptoms were important factors in the pathway between symptom distress and HRQoL for heart failure patients. We suggest providing heart failure patients with tailored interventions for effective self-management of symptoms based on Mishel's theory of uncertainty in illness, which could help control disease symptoms, alleviate uncertainty and depression as well as improve HRQoL.

Micronutrient Deficiency Independently Predicts Time to Event in Patients With Heart Failure

Background Dietary micronutrient deficiencies have been shown to predict event-free survival in other countries but have not been examined in patients with heart failure living in the United States. The purpose of this study was to determine whether number of dietary micronutrient deficiencies in patients with heart failure was associated with shorter event-free survival, defined as a combined end point of all-cause hospitalization and death. Methods and Results Four-day food diaries were collected from 246 patients with heart failure (age: 61.5±12 years; 67% male; 73% white; 45% New York Heart Association [NYHA] class III / IV ) and analyzed using Nutrition Data Systems for Research. Micronutrient deficiencies were determined according to methods recommended by the Institute of Medicine. Patients were followed for 1 year to collect data on all-cause hospitalization or death. Patients were divided according to number of dietary micronutrient deficiencies at a cut point of ≥7 for the high deficiency category versus <7 for the no to moderate deficiency category. In the full sample, 29.8% of patients experienced hospitalization or death during the year, including 44.3% in the high-deficiency group and 25.1% in the no/moderate group. The difference in survival distribution was significant (log rank, P=0.0065). In a Cox regression, micronutrient deficiency category predicted time to event with depression, NYHA classification, comorbidity burden, body mass index, calorie and sodium intake, and prescribed angiotensin-converting enzyme inhibitors, diuretics, or β-blockers included as covariates. Conclusions This study provides additional convincing evidence that diet quality of patients with heart failure plays an important role in heart failure outcomes.

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.

Emotion Regulation and Perceptions of Illness Coherence and Controllability on Regimen Adherence and Negative Cardiac Health Events in African American Women With Heart Failure

BACKGROUND

African American women with heart failure (HF) have stressors that negatively impact HF self-management adherence and heighten the occurrence of negative cardiac health events. Perceptions of illness coherence and controllability and emotion regulation are known to facilitate self-management in the face of stressors.

OBJECTIVE

The aim of this study was to determine whether difficulties with emotion regulation and negative perceptions of illness coherence and controllability are detrimental to adherence and increase negative cardiac health events in this patient population.

METHODS

African American women (n = 54) with HF, aged 49 to 84 years, participated in this longitudinal descriptive correlational study. Using convenience sampling, we recruited patients from hospitals and HF clinics. They completed interviews at intake and 30 days, and their medical records were reviewed at 90 days. Linear and logistic regression models were used to assess predictors of general adherence and negative cardiac health events.

RESULTS

Of 54 patients who participated in the study, 28 experienced a negative health event during 90 days, and 57% of these events were cardiac related. The only clear predictor of these events was greater New York Heart Association functional classification (β = 1.47, P = .027). No associations were found between predictors (emotion regulation, controllability, coherence, age, education) and general adherence.

CONCLUSIONS

Emotion regulation showed a possible greater impact on negative cardiac health events than on general adherence. Perceived illness coherence showed less impact on negative cardiac health events than on general adherence.

Change in symptom clusters in head and neck cancer patients undergoing postoperative radiotherapy: A longitudinal study

PURPOSE

Research on symptom clusters is a newly emerging field in oncology; however, little evidence regarding symptom clusters in head and neck cancer (HNC) is currently available. To clarify this under-researched area, we investigated symptom clusters among patients with HNC treated with surgery and postoperative radiotherapy. We also examined the pattern of symptom clusters throughout the treatment course.

METHOD

A convenience sample of 100 patients with HNC was recruited in the Ear, Nose, and Throat unit of a medical center in Taiwan. Before undergoing postoperative radiotherapy, patients were asked to complete the MD Anderson Symptom Inventory and a demographic sheet. Patients completed the same inventory questionnaire at week 1, 2, 3, 4, 5, and 6 of radiotherapy.

RESULT

Two symptom clusters were observed, and they were stable throughout the course of radiotherapy. Cluster 1, the HNC-specific cluster, comprised the symptoms of pain, dry mouth, lack of appetite, sleep disturbance, fatigue, drowsiness, distress, and sadness. Cluster 2, the gastrointestinal cluster, included nausea, vomiting, numbness, shortness of breath, and difficulty remembering.

CONCLUSION

This study advanced our knowledge of symptom clusters in patients with HNC. The results are expected to contribute to the development of appropriate assessment and nursing interventions targeting multiple symptoms that may coexist in postoperative radiotherapy.

The Prevalence and Associated Distress of Physical and Psychological Symptoms in Patients With Advanced Heart Failure Attending a South African Medical Center

BACKGROUND

Despite the high prevalence of heart failure in low- and middle-income countries, evidence concerning patient-reported burden of disease in advanced heart failure is lacking.

OBJECTIVE

The aim of this study is to measure patient-reported symptom prevalence and correlates of symptom burden in patients with advanced heart failure.

METHODS

Adult patients diagnosed with New York heart Association (NYHA) stage III or IV heart failure were recruited from the emergency unit, emergency ward, cardiology ward, general medicine wards, and outpatient cardiology clinic of a public hospital in South Africa. Patients were interviewed by researchers using the Memorial Symptom Assessment Scale-Short Form, a well-validated multidimensional instrument that assesses presence and distress of 32 symptoms.

RESULTS

A total of 230 patients (response, 99.1%), 90% NYHA III and 10% NYHA IV (12% newly diagnosed), with a mean age of 58 years, were included. Forty-five percent were women, 14% had completed high school, and 26% reported having no income. Mean Karnofsky Performance Status Score was 50%. Patients reported a mean of 19 symptoms. Physical symptoms with a high prevalence were shortness of breath (95.2%), feeling drowsy/tired (93.0%), and pain (91.3%). Psychological symptoms with a high prevalence were worrying (94.3%), feeling irritable (93.5%), and feeling sad (93.0%). Multivariate linear regression analyses, with total number of symptoms as dependent variable, showed no association between number of symptoms and gender, education, number of healthcare contacts in the last 3 months, years since diagnosis, or comorbidities. Increased number of symptoms was significantly associated with higher age (b = 0.054, P = .042), no income (b = -2.457, P = .013), and fewer hospitalizations in the last 12 months (b = -1.032, P = .017).

CONCLUSIONS

Patients with advanced heart failure attending a medical center in South Africa experience high prevalence of symptoms and report high levels of burden associated with these symptoms. Improved compliance with national and global treatment recommendations could contribute to reduced symptom burden. Healthcare professionals should consider incorporating palliative care into the care for these patients.

Symptom burden in heart failure: assessment, impact on outcomes, and management

Evidence-based management has improved long-term survival in patients with heart failure (HF). However, an unintended consequence of increased longevity is that patients with HF are exposed to a greater symptom burden over time. In addition to classic symptoms such as dyspnea and edema, patients with HF frequently suffer additional symptoms such as pain, depression, gastrointestinal distress, and fatigue. In addition to obvious effects on quality of life, untreated symptoms increase clinical events including emergency department visits, hospitalizations, and long-term mortality in a dose-dependent fashion. Symptom management in patients with HF consists of two key components: comprehensive symptom assessment and sufficient knowledge of available approaches to alleviate the symptoms. Successful treatment addresses not just the physical but also the emotional, social, and spiritual aspects of suffering. Despite a lack of formal experience during cardiovascular training, symptom management in HF can be learned and implemented effectively by cardiology providers. Co-management with palliative medicine specialists can add significant value across the spectrum and throughout the course of HF.

Psychometric Analysis of the Heart Failure Somatic Perception Scale as a Measure of Patient Symptom Perception

BACKGROUND

Symptoms are known to predict survival among patients with heart failure (HF), but discrepancies exist between patients' and health providers' perceptions of HF symptom burden.

OBJECTIVE

The purpose of this study is to quantify the internal consistency, validity, and prognostic value of patient perception of a broad range of HF symptoms using an HF-specific physical symptom measure, the 18-item HF Somatic Perception Scale v. 3.

METHODS

Factor analysis of the HF Somatic Perception Scale was conducted in a convenience sample of 378 patients with chronic HF. Convergent validity was examined using the Physical Limitation subscale of the Kansas City Cardiomyopathy Questionnaire. Divergent validity was examined using the Self-care of HF Index self-care management score. One-year survival based on HF Somatic Perception Scale scores was quantified using Cox regression controlling for Seattle HF Model scores to account for clinical status, therapeutics, and lab values.

RESULTS

The sample was 63% male, 85% white, 67% functionally compromised (New York Heart Association class III-IV) with a mean (SD) age of 63 (12.8) years. Internal consistency of the HF Somatic Perception Scale was α = .90. Convergent (r = -0.54, P < .0001) and divergent (r = 0.18, P > .05) validities were supported. Controlling for Seattle HF scores, HF Somatic Perception Scale was a significant predictor of 1-year survival, with those most symptomatic having worse survival (hazard ratio, 1.012; 95% confidence interval, 1.001-1.024; P = .038).

CONCLUSIONS

Perception of HF symptom burden as measured by the HF Somatic Perception Scale is a significant predictor of survival, contributing additional prognostic value over and above objective Seattle HF Risk Model scores. This analysis suggests that assessment of a broad range of HF symptoms, or those related to dyspnea or early and subtle symptoms, may be useful in evaluating therapeutic outcomes and predicting event-free survival.

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.

Klinische Studien zu neuen direkten oralen Antikoagulanzien

Um die Wirksamkeit und Verträglichkeit neuer direkter oraler Antikoagulanzien (DOAK) zu vergleichen, müssten idealerweise eine direkte Gegenüberstellung der Substanzen in klinischen Studien durchgeführt werden. Auf Grund des logistischen und finanziellen Aufwandes wird dies aber in absehbarer Zeit nicht geschehen. Indirekte Vergleiche, auch Netzwerkanalysen (NMA) genannt, lassen sich mit den vorliegenden Studien zwischen den DOAKs vornehmen. In der postoperativen Phase nach Knie- und Hüftgelenkersatz und bei Patienten mit Vorhofflimmern sind derzeit diese Vergleich möglich. Indirekte Vergleiche sind jedoch auch mit Einschränkungen behaftet.

Diese Arbeit gibt eine Übersicht der aktuell vorliegenden NMAs und versucht, deren Ergebnisse mit der Pharmakologie der DOAKs und den methodischen Problemen von NMAs zu beleuchten.

A review of the literature on symptom clusters in studies that included oncology patients receiving primary or adjuvant chemotherapy

AIMS AND OBJECTIVES

To summarise the current state of knowledge of symptom clusters research from studies that included, as part of their sample, patients who were receiving primary or adjuvant chemotherapy.

BACKGROUND

Since the concept of a symptom cluster was first introduced into the oncology literature in 2001, only four comprehensive reviews of symptom clusters research in oncology patients were identified that provide insights into this important concept in symptom management research.

DESIGN

A comprehensive review of the literature.

METHODS

A comprehensive literature search was conducted for the years 2000 to 2016. Only 19 studies met the inclusion criteria for this literature review. These studies were evaluated in terms of the symptom assessment instruments used; the statistical analysis methods used; the symptom dimension(s) used to create the symptom cluster(s); the number and types of symptom clusters identified; and whether the specific symptom clusters changed over time.

RESULTS

The number of symptom clusters identified ranged from one-seven. The majority of the studies used some type of factor analysis to create the symptom clusters. The most common symptom dimension used to create the clusters was symptom severity. A "gastrointestinal symptom cluster" was the most common symptom cluster identified. Across the eight longitudinal studies, for half of these studies the symptom clusters remained relatively stable over time.

CONCLUSIONS

Additional research is needed in oncology patients to address the assessment of symptom clusters, the specific nature of symptom clusters and whether symptom clusters change over time.

Exploring Symptom Clusters in People With Heart Failure

Patients with heart failure (HF) experience multiple symptoms or symptom clusters. The purposes of this study were to (a) determine if distinct latent classes of HF symptoms could be identified, and (b) explore whether sociodemographic and clinical characteristics influenced symptom cluster membership. A total of 4,011 HF patients recruited from outpatient setting completed the Minnesota Living With Heart Failure Questionnaire (MLHFQ), including five physical symptoms (edema, shortness of breath, fatigue-increased need to rest, fatigue-low energy, and sleep difficulties) and three psychological symptoms (worrying, feeling depressed, and cognitive problems). Four distinct classes using latent class profile analysis were identified: low distress (Class 1), physical distress (Class 2), psychological distress (Class 3), and high distress (Class 4). Significant differences among the four latent classes were found for age, education level, and comorbidities. Symptom clusters are useful for recognition of HF symptoms, allowing for the development of strategies that target symptom groups.

Sleep Disturbance, Daytime Symptoms, and Functional Performance in Patients With Stable Heart Failure: A Mediation Analysis

BACKGROUND

Sleep disturbance is common among patients with heart failure (HF) who also experience symptom burden and poor functional performance.

OBJECTIVE

We evaluated the extent to which sleep-related, daytime symptoms (fatigue, excessive daytime sleepiness, and depressive symptoms) mediate the relationship between sleep disturbance and functional performance among patients with stable HF.

METHODS

We recruited patients with stable HF for this secondary analysis of data from a cross-sectional, observational study. Participants completed unattended ambulatory polysomnography from which the Respiratory Disturbance Index was calculated, along with a Six-Minute Walk Test, questionnaires to elicit sleep disturbance (Pittsburgh Sleep Quality Index, Insomnia Symptoms from the Sleep Habits Questionnaire), daytime symptoms (Center for Epidemiologic Studies Depression Scale, Global Fatigue Index, Epworth Sleepiness Scale), and self-reported functional performance (Medical Outcomes Study SF36 V2 Physical Function Scale). We used structural equation modeling with latent variables for the key analysis. Follow-up, exploratory regression analysis with bootstrapped samples was used to examine the extent to which individual daytime symptoms mediated effects of sleep disturbance on functional performance after controlling for clinical and demographic covariates.

RESULTS

The sample included 173 New York Heart Association Class I-IV HF patients (n = 60/34.7% women; M = 60.7, SD = 16.07 years of age). Daytime symptoms mediated the relationship between sleep disturbance and functional performance. Fatigue and depression mediated the relationship between insomnia symptoms and self-reported functional performance, whereas fatigue and sleepiness mediated the relationship between sleep quality and functional performance. Sleepiness mediated the relationship between the respiratory index and self-reported functional performance only in people who did not report insomnia.

CONCLUSIONS

Daytime symptoms explain the relationships between sleep disturbance and functional performance in stable HF.

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.

Advancing Symptom Science Through Symptom Cluster Research: Expert Panel Proceedings and Recommendations

An overview of proceedings, findings, and recommendations from the workshop on "Advancing Symptom Science Through Symptom Cluster Research" sponsored by the National Institute of Nursing Research (NINR) and the Office of Rare Diseases Research, National Center for Advancing Translational Sciences, is presented. This workshop engaged an expert panel in an evidenced-based discussion regarding the state of the science of symptom clusters in chronic conditions including cancer and other rare diseases. An interdisciplinary working group from the extramural research community representing nursing, medicine, oncology, psychology, and bioinformatics was convened at the National Institutes of Health. Based on expertise, members were divided into teams to address key areas: defining characteristics of symptom clusters, priority symptom clusters and underlying mechanisms, measurement issues, targeted interventions, and new analytic strategies. For each area, the evidence was synthesized, limitations and gaps identified, and recommendations for future research delineated. The majority of findings in each area were from studies of oncology patients. However, increasing evidence suggests that symptom clusters occur in patients with other chronic conditions (eg, pulmonary, cardiac, and end-stage renal disease). Nonetheless, symptom cluster research is extremely limited and scientists are just beginning to understand how to investigate symptom clusters by developing frameworks and new methods and approaches. With a focus on personalized care, an understanding of individual susceptibility to symptoms and whether a "driving" symptom exists that triggers other symptoms in the cluster is needed. Also, research aimed at identifying the mechanisms that underlie symptom clusters is essential to developing targeted interventions.

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.