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.

Nonpharmacological Interventions for Managing Symptom Clusters in Adults: A Systematic Review

Objectives: The complex effects of multiple co-occurring symptoms are a major cause of reduced quality of life; thus, it is necessary to identify symptom clusters experienced by patients and explore interventions. This study aimed to provide an overview of non-pharmacological interventions based on symptom clusters in adults to identify effective intervention strategies and methods. Methods. This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines. For the search databases, PubMed, Embase, Cochrane Library, CINAHL, RISS, KISS, and KISTI were used. It includes English and Korean experimental studies published up to May 2023. The literature quality was evaluated using the Joanna Briggs Institute Quality Assessment Tool. Results. Of the 18 studies selected, 15 were randomized controlled trials and three were quasi-experimental studies, all of which were conducted on patients with cancer. The symptom clusters-based interventions in the literature are classified as movement-based, relaxation-based, integrated, and miscellaneous interventions. Integrated interventions, which were effective in all studies, might prove to be very effective for managing symptom clusters. Movement-based intervention studies, which include dance, Qigong, and Tai Chi, might be very effective in improving health-related quality of life (HRQoL). Conclusions. This review demonstrates that non-pharmacological interventions reduce the occurrence and severity of symptom clusters, thereby improving HRQoL. Further studies are required to evaluate the effects of these interventions in patients with various chronic conditions other than cancer.

Symptom clusters and unplanned hospital readmission in Chinese patients with acute myocardial infarction on admission

Backgroud

Acute myocardial infarction (AMI) has a high morbidity rate, high mortality rate, high readmission rate, high health care costs, and a high symptomatic, psychological, and economic burden on patients. Patients with AMI usually present with multiple symptoms simultaneously, which are manifested as symptom clusters. Symptom clusters have a profound impact on the quality of survival and clinical outcomes of AMI patients.

Objective

The purpose of this study was to analyze unplanned hospital readmissions among cluster groups within a 1-year follow-up period, as well as to identify clusters of acute symptoms and the characteristics associated with them that appeared in patients with AMI.

Methods

Between October 2021 and October 2022, 261 AMI patients in China were individually questioned for symptoms using a structured questionnaire. Mplus 8.3 software was used to conduct latent class analysis in order to find symptom clusters. Univariate analysis is used to examine characteristics associated with each cluster, and multinomial logistic regression is used to analyze a cluster membership as an independent predictor of hospital readmission after 1-year.

Results

Three unique clusters were found among the 11 acute symptoms: the typical chest symptom cluster (64.4%), the multiple symptom cluster (29.5%), and the atypical symptom cluster (6.1%). The cluster of atypical symptoms was more likely to have anemia and the worse values of Killip class compared with other clusters. The results of multiple logistic regression indicated that, in comparison to the typical chest cluster, the atypical symptom cluster substantially predicted a greater probability of 1-year hospital readmission (odd ratio 8.303, 95% confidence interval 2.550-27.031, P < 0.001).

Conclusion

Out of the 11 acute symptoms, we have found three clusters: the typical chest symptom, multiple symptom, and atypical symptom clusters. Compared to patients in the other two clusters, those in the atypical symptom cluster-which included anemia and a large percentage of Killip class patients-had worse clinical indicators at hospital readmission during the duration of the 1-year follow-up. Both anemia and high Killip classification suggest that the patient's clinical presentation is poor and therefore the prognosis is worse. Intensive treatment should be considered for anemia and high level of Killip class patients with atypical presentation. Clinicians should focus on patients with atypical symptom clusters, enhance early recognition of symptoms, and develop targeted symptom management strategies to alleviate their discomfort in order to improve symptomatic outcomes.

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.

Exploring Traditional Medicine Diagnostic Classification for Parkinson's Disease Using Hierarchical Clustering

INTRODUCTION

Personalized diagnosis and therapy for Parkinson's disease (PD) are needed due to the clinical heterogeneity of PD. Syndrome differentiation (SD) in traditional medicine (TM) is a diagnostic method for customized therapy that comprehensively analyzes various symptoms and systemic syndromes. However, research identifying PD classification based on SD is limited.

METHODS

Ten electronic databases were systematically searched from inception to August 10, 2021. Clinical indicators, including 380 symptoms, 98 TM signs, and herbal medicine for PD diagnosed with SD, were extracted from 197 articles; frequency statistics on clinical indicators were conducted to classify several subtypes using hierarchical clustering.

RESULTS

Four distinct cluster groups were identified, each characterized by significant cluster-specific clinical indicators with 95% confidence intervals of distribution. Subtype 2 had the most severe progression, longest progressive duration, and highest association with greater late-stage PD-associated motor symptoms, including postural instability and gait disturbance. The action properties of the herbal formula and original SD presented in the data sources for subtype 2 were associated with Yin deficiency syndrome.

DISCUSSION/CONCLUSION

Hierarchical clustering analysis distinguished various symptoms and TM signs among patients with PD. These newly identified PD subtypes may optimize the diagnosis and treatment with TM and facilitate prognosis prediction. Our findings serve as a cornerstone for evidence-based guidelines for TM diagnosis and treatment.

Einleitung

Eine personalisierte Diagnose und Therapie des Morbus Parkinson (MP) ist angesichts der ausgeprägten klinischen Heterogenität des MP unerlässlich. Die Syndromdifferenzierung (SD) ist in der traditionellen Medizin (TM) eine diagnostische Methode für eine maßgeschneiderte Therapie, bei der verschiedene Symptome und systemische Syndrome umfassend analysiert werden. Es liegen jedoch nur begrenzt Forschungsergebnisse in Bezug auf eine SD-basierte Klassifikation des MP vor.

Methoden

Zehn elektronische Datenbanken wurden systematisch durchsucht, von der Einrichtung bis zum 10. August 2021. Klinische Indikatoren einschließlich von 380 Symptomen, 98 TM-Zeichen sowie pflanzlichen Heilmitteln für mittels SD diagnostiziertem MP wurden aus 197 Artikeln extrahiert, und Häufigkeitsstatistiken der klinischen Indikatoren wurden erstellt, um mittels hierarchischem Clustering eine Reihe von Subtypen zu klassifizieren.

Ergebnisse

Vier verschiedene Cluster-Gruppen wurden identifiziert, die jeweils durch signifikante, Cluster-spezifische klinische Indikatoren mit 95% Konfidenzintervall der Verteilung gekennzeichnet waren. Subtyp 2 hatte den schwersten Verlauf, die längste Progressionsdauer und die stärkste Assoziation mit einem höheren Ausmaß von motorischen Symptomen des MP im Spätstadium, darunter Haltungsinstabilität und Gangstörungen. Die Wirkungseigenschaften der pflanzlichen Formulierung sowie die ursprüngliche SD, die in den Datenquellen für Subtyp 2 genannt wurden, waren mit Yin-Mangel-Syndrom assoziiert.

Diskussion/Schlussfolgerung

Die hierarchische Clustering-Analyse hob verschiedene Symptome und TM-Zeichen bei Patienten mit MP hervor. Die neu identifizierten MP-Subtypen könnten die Diagnose und Behandlung mittels TM optimieren und zur Prognoseerstellung beitragen. Unsere Ergebnisse sind ein Fundament für eine evidenzbasierte Leitlinie für die TM-Diagnostik und -Therapie.

Symptom Presentation among Women with Suspected Ischemia and No Obstructive Coronary Artery Disease (INOCA)

Identifying ischemic heart disease (IHD) in women based on symptoms is challenging. Women are more likely to endorse non-cardiac symptoms. More than 50% of women with suspected ischemia have no obstructive coronary disease (and thus, INOCA) and impaired outcomes during follow-up. We aimed to identify symptoms having predictive capacity for INOCA in women with clinical evidence of coronary ischemia. We included 916 women from the original WISE cohort (NCT00000554) who had coronary angiography performed for suspected ischemia and completed a 65-item WISE symptom questionnaire. Sixty-two percent (n = 567) had suspected INOCA. Logistic regression models using a best subsets approach were examined to identify the best predictive model for INOCA based on Score χ2 and AICc. A 10-variable, best-fit model accurately predicted INOCA (AUC 0.72, 95% CI 0.68, 0.75). The model indicated that age ≤ 55 years, left side chest pain, chest discomfort, neck pain, and palpitations had independent, positive relationship (OR > 1) to INOCA (p < 0.001 to 0.008). An inverse relationship (OR < 1) was observed for impending doom, and pain in the jaw, left or bilateral arm, and right hand, interpreted as INOCA associated with the absence of these symptoms (p ≤ 0.001 to 0.023). Our best-fit model accurately predicted INOCA based on age and symptom presentation ~72% of the time. While the heterogeneity of symptom presentation limits the utility of this unvalidated 10-variable model, it has promise for consideration of symptom inclusion in future INOCA prediction risk modeling for women with evidence of symptomatic ischemia.

Symptoms and symptom clusters in patients newly diagnosed with inflammatory bowel disease: results from the IBSEN III Study

BACKGROUND

Patients with inflammatory bowel disease report multiple symptoms, but the relationships among co-occurring symptoms are poorly understood. This study aimed to examine the prevalence of symptoms and explore symptom clusters and possible associations between symptom clusters and socio-demographic and clinical variables in patients newly diagnosed with inflammatory bowel disease.

METHODS

The IBSEN III study is a prospective population-based inception cohort of patients with inflammatory bowel disease. This study used patient data from the three largest hospitals in the study catchment area. The Memorial Symptom Assessment Scale was used to assess the prevalence of symptoms. Symptom clusters were identified using principal component analysis. Possible associations between socio-demographic and clinical variables and symptom cluster membership were estimated using regression analysis.

RESULTS

Of the 573 patients (age, ≥18 years) diagnosed with inflammatory bowel disease, 350 (61.1%) completed the questionnaire (responders). Eleven symptoms were reported by >50% of the responders. The three most prevalent symptoms were bloating (84%), drowsiness (81%), and lack of energy (81%). Three symptom clusters were identified: psychological (56% of the patients), impaired energy (28%), and physical (16%) clusters. Multinomial regression analysis revealed that vitamin D deficiency was significantly associated with the impaired energy cluster (odds ratio=2.49, 95% confidence interval [1.00-6.2], p=0.05).

CONCLUSIONS

We found high symptom prevalence in patients newly diagnosed with inflammatory bowel disease. Three distinct symptom clusters were identified, and the psychological cluster includes >50% of the patients. Vitamin D deficiency is the only factor associated with cluster membership, namely the impaired energy cluster.

The Association Between Vitamin D Level and Chest Pain, Anxiety, and Fatigue in Patients With Coronary Artery Disease

This study sought to assess the association between vitamin D deficiency (VDD) and chest pain, anxiety, and fatigue in patients with coronary artery disease (CAD). A cross-sectional study was conducted to collect data from a sample of 90 participants with CAD. Serum 25OHD3 was measured using a radioimmunoassay procedure. Chest pain was assessed using the Numeric Pain Rating Scale, anxiety using the Anxiety Subscale, and fatigue by the General Fatigue subscale. The majority of participants (80%) had VDD. Results showed that the level of vitamin D was significantly negatively associated with chest pain (r = -.43, p = .00); anxiety (r = -.466, p = .00); and fatigue (r = -.25, p = .018). Findings suggest the role of VDD in heightened central sensitivity in cardiac-related symptoms such as chest pain, anxiety, and fatigue. Patients with CAD should be monitored for VDD so that the condition can be corrected.

Characterizing fatigue phenotypes with other symptoms and clinically relevant outcomes among people with multiple sclerosis

PURPOSE

Fatigue is a common symptom of multiple sclerosis (MS) and can adversely affect all aspect of quality of life. The etiology of fatigue remains unclear, and its treatments are suboptimal. Characterizing the phenotypes of fatigued persons with MS may help advance research on fatigue's etiology and identify ways to personalize fatigue interventions to improve quality of life. The purpose of this study was to identify fatigue phenotypes; examine phenotype stability overtime; and characterize phenotypes by health and function, social and environmental determinants, psychosocial factors, and engagement in healthy behaviors.

METHODS

We conducted a longitudinal study over a 3-month period with 289 fatigued participants with MS. To identify fatigue phenotypes and determine transition probabilities, we used latent profile and transition analyses with valid self-report measures of mental and physical fatigue severity, the mental and physical impact of fatigue, depression, anxiety, and sleep quality. We used ANOVAs and effect sizes to characterize differences among phenotypes.

RESULTS

The best fitting model included six subgroups of participants: Mild Phenotype, Mild-to-Moderate Phenotype, Moderate-to-Severe Phenotype, Severe Phenotype, Fatigue-dominant Phenotype, and Mental Health-dominant Phenotype. The transition analysis indicated that phenotypic membership was highly stable. Variables with a large eta squared effect size included environmental barriers, self-efficacy, and fatigue catastrophizing.

CONCLUSION

These results indicate that the magnitude of fatigue experienced may be more important to consider than the type of fatigue when characterizing fatigue phenotypes. Future research should explore whether tailoring interventions to environmental barriers, self-efficacy, and fatigue catastrophizing reduce the likelihood of transitioning to a more severe phenotype.

A Bibliometric Analysis of High-Intensity Interval Training in Cardiac Rehabilitation

As global quality of life has improved, the risk factors for cardiovascular diseases have gradually increased in prevalence. People have consequently sought to improve their health through physical exercise. High-intensity interval training (HIIT) is a cardiac rehabilitation (CR) tool that has been of great interest for several years. However, its feasibility and safety remain controversial. This study aimed to explore hot research topics and new directions regarding the role of HIIT in CR and to describe the dynamic development of the field. We used the Web of Science Core Collection database to develop visualizations using CiteSpace software (v.6.1.R2). The number of articles published, institutional collaboration networks, author partnerships, and keyword co-occurrence and clustering were used to analyze the impact of HIIT on CR. Our results showed that Norway, Canada, and the United States were the most prominent contributors to this field. Articles by Nigam, A and Juneau, M had the highest number of citations. The Norwegian University of Science and Technology had performed the most in-depth research in this area. The European Journal of Preventive Cardiology had published the most articles. The United States had the highest number of publishing journals. Relevant issues focused on coronary artery disease, exercise capacity, heart failure, cardiorespiratory fitness, and physical activity. HIIT in heart transplantation may be at the forefront of research in this field and future studies should focus on this topic. HIIT-based CR can therefore improve the exercise capacity and quality of life of cardiovascular patients and improve patient compliance in a safe manner.

Advances in Conceptual and Methodological Issues in Symptom Cluster Research: A 20-Year Perspective

Two conceptual approaches are used to evaluate symptom clusters: "clustering" symptoms (ie, variable-centered analytic approach) and "clustering" patients (ie, person-centered analytic approach). However, these methods are not used consistently and conceptual clarity is needed. Given the emergence of novel methods to evaluate symptom clusters, a review of the conceptual basis for older and newer analytic methods is warranted. Therefore, this article will review the conceptual basis for symptom cluster research; compare and contrast the conceptual basis for using variable-centered versus patient-centered analytic approaches in symptom cluster research; review their strengths and weaknesses; and compare their applications in symptom cluster research.

Predictors of health-related quality of life after coronary artery bypass graft surgery

Health-related quality of life (HRQOL) is a multifactorial concept in assessing physical and mental health. This study was performed to evaluate the HRQOL of patients undergoing coronary artery bypass graft (CABG) surgery and the predictors of HRQOL in patients until 1 year after surgery. This cross-sectional study included 110 consecutive patients who underwent elective CABG in a medical center in South Korea. The Short-Form Health Survey, cardiac symptom survey, cardiac self-efficacy, and the Interpersonal Support Evaluation List-12 were used to measure the HRQOL, symptom experience, self-efficacy, and social support, respectively. The regression model explained 42% of the variance in the participants' physical HRQOL. The predictors of the physical HRQOL include the presence of a spouse, post-CABG duration, symptom experience, and self-efficacy. The regression model explained 36% of the variance in the participants' mental HRQOL. The predictors of the mental HRQOL included perceived health status, self-efficacy, and social support. The predictive factors for HRQOL after CABG were the presence of a spouse, post-CABG duration, symptom experience, self-efficacy, and social support. Furthermore, a suitable program and nursing interventions could be implemented to improve the HRQOL of post-CABG patients.

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

BACKGROUND

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

STUDY DESIGN AND METHODS

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

CONCLUSIONS

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

BRIEF LAY SUMMARY

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

Patient-centred approaches for the management of unpleasant symptoms in kidney disease

Patients with chronic kidney disease (CKD) frequently experience unpleasant symptoms. These can be gastrointestinal (constipation, nausea, vomiting and diarrhoea), psychological (anxiety and sadness), neurological (lightheadedness, headache and numbness), cardiopulmonary (shortness of breath and oedema), dermatological (pruritus and dry skin), painful (muscle cramps, chest pain and abdominal pain) or involve sexual dysfunction, sleep disorders and fatigue. These symptoms often occur in clusters, with one of them as the lead symptom and others as secondary symptoms. Uraemic toxins (also called uremic toxins) are often considered to be the main cause of CKD-associated symptom burden, but treatment of uraemia by dialysis often fails to resolve them and can engender additional symptoms. Indeed, symptoms can be exacerbated by comorbid conditions, pharmacotherapies, lifestyle and dietary regimens, kidney replacement therapy and ageing. Patients with kidney disease, including those who depend on dialysis or transplantation, should feel actively supported in their symptom management through the identification and targeting of unpleasant symptoms via a tailored palliative care approach. Such an approach may help minimize the burden and consequences of kidney disease, and lead to improved patient outcomes including health-related quality of life and better life participation.

Characterizing Pain Leading to Emergency Medical Services Activation in Heart Failure

BACKGROUND

Pain is a common but understudied symptom among patients with heart failure (HF) transported by emergency medical services (EMS). The aims were to determine explanatory factors of a primary complaint of pain and pain severity, and characterize pain among patients with HF transported by EMS.

METHODS

Data from electronic health records of patients with HF transported by EMS within a midwestern United States county from 2009 to 2017 were analyzed. Descriptive statistics, χ 2 , analysis of variance, and logistic and multiple linear regression analyses were used.

RESULTS

The sample (N = 4663) was predominantly women (58.1%) with self-reported race as Black (57.7%). The mean age was 64.2 ± 14.3 years. Pain was the primary complaint in 22.2% of the sample, with an average pain score of 6.8 ± 3.1 out of 10. The most common pain complaint was chest pain (68.1%). Factors associated with a primary pain complaint were younger age (odds ratio [OR], 0.97; 95% confidence interval [CI], 0.96-0.97), history of myocardial infarction (OR, 1.96; 95% CI, 1.55-2.49), and absence of shortness of breath (OR, 0.67; 95% CI, 0.58-0.77). Factors associated with higher pain severity were younger age ( b = -0.05, SE = 0.013), being a woman ( b = 1.17, SE = 0.357), and White race ( b = -1.11, SE = 0.349).

CONCLUSIONS

Clinical and demographic factors need consideration in understanding pain in HF during EMS transport. Additional research is needed to examine these factors to improve pain management and reduce transports due to pain.

Prevalence of chronic kidney disease in Asia: a systematic review and analysis

INTRODUCTION

The burden of chronic kidney disease (CKD) is growing rapidly around the world. However, there is limited information on the overall regional prevalence of CKD, as well as the variations in national prevalence within Asia. We aimed to consolidate available data and quantify estimates of the CKD burden in this region.

METHODS

We systematically searched MEDLINE, Embase and Google Scholar for observational studies and contacted national experts to estimate CKD prevalence in countries of Asia (Eastern, Southern and South Eastern Asia). CKD was defined as estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 or the presence of proteinuria. For countries without reported data, we estimated CKD prevalence using agglomerative average-linkage hierarchical clustering, based on country-level risk factors and random effects meta-analysis within clusters. Published CKD prevalence data were obtained for 16 countries (of the 26 countries in the region) and estimates were made for 10 countries.

RESULTS

There was substantial variation in overall and advanced (eGFR <30 mL/min/1.73 m2) CKD prevalence (range: 7.0%-34.3% and 0.1%-17.0%, respectively). Up to an estimated 434.3 million (95% CI 350.2 to 519.7) adults have CKD in Asia, including up to 65.6 million (95% CI 42.2 to 94.9) who have advanced CKD. The greatest number of adults living with CKD were in China (up to 159.8 million, 95% CI 146.6 to 174.1) and India (up to 140.2 million, 95% CI 110.7 to 169.7), collectively having 69.1% of the total number of adults with CKD in the region.

CONCLUSION

The large number of people with CKD, and the substantial number with advanced CKD, show the need for urgent collaborative action in Asia to prevent and manage CKD and its complications.

Characterization of Symptoms and Symptom Clusters for Type 2 Diabetes Using a Large Nationwide Electronic Health Record Database

OBJECTIVE

A variety of symptoms may be associated with type 2 diabetes and its complications. Symptoms in chronic diseases may be described in terms of prevalence, severity, and trajectory and often co-occur in groups, known as symptom clusters, which may be representative of a common etiology. The purpose of this study was to characterize type 2 diabetes-related symptoms using a large nationwide electronic health record (EHR) database.

METHODS

We acquired the Cerner Health Facts, a nationwide EHR database. The type 2 diabetes cohort (n = 1,136,301 patients) was identified using a rule-based phenotype method. A multistep procedure was then used to identify type 2 diabetes-related symptoms based on International Classification of Diseases, 9th and 10th revisions, diagnosis codes. Type 2 diabetes-related symptoms and co-occurring symptom clusters, including their temporal patterns, were characterized based the longitudinal EHR data.

RESULTS

Patients had a mean age of 61.4 years, 51.2% were female, and 70.0% were White. Among 1,136,301 patients, there were 8,008,276 occurrences of 59 symptoms. The most frequently reported symptoms included pain, heartburn, shortness of breath, fatigue, and swelling, which occurred in 21-60% of the patients. We also observed over-represented type 2 diabetes symptoms, including difficulty speaking, feeling confused, trouble remembering, weakness, and drowsiness/sleepiness. Some of these are rare and difficult to detect by traditional patient-reported outcomes studies.

CONCLUSION

To the best of our knowledge, this is the first study to use a nationwide EHR database to characterize type 2 diabetes-related symptoms and their temporal patterns. Fifty-nine symptoms, including both over-represented and rare diabetes-related symptoms, were identified.

Ferroptosis: New Dawn for Overcoming the Cardio-Cerebrovascular Diseases

The dynamic balance of cardiomyocytes and neurons is essential to maintain the normal physiological functions of heart and brain. If excessive cells die in tissues, serious Cardio-Cerebrovascular Diseases would occur, namely, hypertension, myocardial infarction, and ischemic stroke. The regulation of cell death plays a role in promoting or alleviating Cardio-Cerebrovascular Diseases. Ferroptosis is an iron-dependent new type of cell death that has been proved to occur in a variety of diseases. In our review, we focus on the critical role of ferroptosis and its regulatory mechanisms involved in Cardio-Cerebrovascular Diseases, and discuss the important function of ferroptosis-related inhibitors in order to propose potential implications for the prevention and treatment of Cardio-Cerebrovascular Diseases.

Characterizing shared and distinct symptom clusters in common chronic conditions through natural language processing of nursing notes

Data-driven characterization of symptom clusters in chronic conditions is essential for shared cluster detection and physiological mechanism discovery. This study aims to computationally describe symptom documentation from electronic nursing notes and compare symptom clusters among patients diagnosed with four chronic conditions-chronic obstructive pulmonary disease (COPD), heart failure, type 2 diabetes mellitus, and cancer. Nursing notes (N = 504,395; 133,977 patients) were obtained for the 2016 calendar year from a single medical center. We used NimbleMiner, a natural language processing application, to identify the presence of 56 symptoms. We calculated symptom documentation prevalence by note and patient for the corpus. Then, we visually compared documentation for a subset of patients (N = 22,657) diagnosed with COPD (n = 3339), heart failure (n = 6587), diabetes (n = 12,139), and cancer (n = 7269) and conducted multiple correspondence analysis and hierarchical clustering to discover underlying groups of patients who have similar symptom profiles (i.e., symptom clusters) for each condition. As expected, pain was the most frequently documented symptom. All conditions had a group of patients characterized by no symptoms. Shared clusters included cardiovascular symptoms for heart failure and diabetes; pain and other symptoms for COPD, diabetes, and cancer; and a newly-identified cognitive and neurological symptom cluster for heart failure, diabetes, and cancer. Cancer (gastrointestinal symptoms and fatigue) and COPD (mental health symptoms) each contained a unique cluster. In summary, we report both shared and distinct, as well as established and novel, symptom clusters across chronic conditions. Findings support the use of electronic health record-derived notes and NLP methods to study symptoms and symptom clusters to advance symptom science.

A Proposed Theory of Symptom Cluster Management

Background

Symptom cluster management is in its early stages in many chronic and debilitating illnesses. The development of a proposed theory should be an initial step in advancing this area of interest.

Objective

This article presents the development of a Proposed Theory of Symptom Cluster Management.

Methods

The concept analysis, statement synthesis, and theory synthesis by Walker and Avant were used in the development of this proposed theory. A search from July to September 2020 for published empirical and theoretical articles was conducted in scientific databases, expanded on the web, and secondary references from identified articles.

Results

The Proposed Theory of Symptom Cluster Management is both a descriptive and explanatory theory. The defining characteristics of symptom cluster management include the basic and effectiveness components. Antecedents for symptom cluster management include socio-demographic characteristics, symptom cluster characteristics, individual clinical characteristics, individual illness factors, and situational factors or symptom experience. The consequences are clustered as personal-related, health-related, social-related outcomes, and existential outcomes. Measurement tools for the antecedents and outcomes in symptom cluster management and the analytical and statistical strategies were considered. Relational statements were also identified. Theoretical assertions were advanced.

Conclusion

The Proposed Theory of Symptom Cluster Management may provide a holistic approach because it integrates both the symptom cluster and management strategies. The concepts, statements including the complete representation of the proposed theory identified in this article, may provide cues to policymakers and clinical researchers towards the development of tailored interventions and programs.

Symptom Status Questionnaire - Heart Failure - Brazilian Version: cross-cultural adaptation and content validation

BACKGROUND

In Brazil, there are no instruments available to measure the presence, frequency, severity and distress related to heart failure (HF) symptoms.

AIMS

To adapt the Symptom Status Questionnaire - HF (SSQ-HF) into Brazilian Portuguese and to examine the content validity of the adapted version.

METHODS

The instrument was translated, back-translated and evaluated by an expert committee for semantic, idiomatic, cultural, and conceptual equivalences. An agreement ≥80% was considered adequate. The adapted version was evaluated by both an expert committee (n = 9) for clarity, theoretical relevance and practical relevance (acceptable content validity coefficient (CVC): ≥0.70), and by a patient committee regarding understanding (n = 40).

RESULTS

The adapted version obtained 100% agreement regarding the equivalences. The total instrument CVC was 0.99. All patients understood the items.

CONCLUSION

The SSQ-HF-Brazilian version has satisfactory evidence of equivalence and content validity. Additional psychometric tests are deemed to confirm that the instrument can be used in Brazil.

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.

Theory-guided interventions for Chinese patients to adapt to heart failure: A quasi-experimental study

Objectives

To examine the effects of the Roy Adaptation Model-based interventions on adaptation in persons with heart failure.

Methods

A quasi-experimental study was conducted in Hangzhou, China, from March 2018 to November 2019. A convenience sample of 112 participants with heart failure from a multi-campus hospital was enrolled. Participants were allocated into an intervention group (n = 55) and a control group (n = 57) according to their hospitalized campus. A culturally-tailored care plan intervention based on the Roy Adaptation Model was performed in the intervention group. The control group received bedside patient education and a regular booklet for HF home care before discharge. Heart ultrasound, Minnesota Living with Heart Failure Questionnaire (MLHFQ), a knowledge survey, Self-care Heart failure Index (SCHFI), and Coping and Adaptation Processing Scale-Short Form (CAPS-SF) were used to measure patients’ levels of adaptation of physical function, self-concept, role function, and interdependence at baseline and six months after discharge.

Results

Ninety-one participants with complete data, 43 in the intervention group and 48 in the control group, were included in the analysis for the primary endpoints and showed adaptive improvement trends. Most patients in the intervention group completed 60% or more of the given interventions. At the sixth month after discharge, compared with the control group, the intervention group had improved adaptive behaviors showing higher scores of the MLHFQ (70.90 ± 22.45 vs. 54.78 ± 18.04), heart failure-related knowledge (13.79 ± 2.45 vs. 10.73 ± 4.28), SCHFI maintenance (57.67 ± 13.22 vs. 50.35 ± 10.88), and CAPS-SF (40.23 ± 4.36 vs. 38.27 ± 2.60) at the six-month follow-up (P ＜ 0.05). There were no significant differences between the two groups in the scores of left ventricular ejection fraction, scores of SCHFI management and SCHFI confidence subscales (P > 0.05).

Conclusions

The findings reported evidence of positive adaptation in patients with heart failure, indicating that the Roy Adaptation Model is an effective guide for developing an implemented framework for the nursing practice of the patients. The culturally-tailored care plan intervention is helpful to improve adaptation of patients with heart failure.

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.

Assessing the quality of life and depression among patients with heart failure and heart attack

Background

Health-related quality and of life and depression are major issues among patients with heart diseases. The aim of the current study was to assess the levels of quality of life and depression among patients with heart failure and heart attack as well as the correlation between these domains and the differences in both categories.

Participants and procedure

In this cross-sectional study the following tools were used: a) the Missoula-VITAS Quality of Life Index (MVQoLI-15), which examines 5 domains of quality of life, and b) the Center for Epidemiological Studies Depression Scale (CES-D), which measures depression among patients. Finally, a questionnaire about sociodemographic elements was completed by the patients. Data were analyzed through IBM Statistics SPSS 20.0. The statistical level was set at 0.05%.

Results

The mean value of CES-D Total and MVQoLI-15 were higher for the patients suffering from heart failure than those suffering from a heart attack. However, the dimensions of MVQoLI-15 Interpersonal Relationships, Well-Being and Transcendence were lower for heart failure patients compared to the levels of the patients suffering from a heart attack. According to the Pearson r test, there was a statistically significant negative correlation be-tween the quality of life and depression (p = .001) in the overall sample.

Conclusions

Patients with heart failure experience more depression and lower quality of life than heart attack patients.

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.

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.

Symptom Clusters in People Living With HIV: A Systematic Review

CONTEXT

An increasing number of studies regarding symptom management have begun to shift their focus from managing a single symptom to multiple symptom clusters. However, there is a lack of consistency of compositions among different studies and even in two different analyses reported in a single study within the same population.

OBJECTIVES

The aim of this systematic review was to summarize the compositions, measures, and data analysis techniques of symptom clusters in people living with HIV (PLWH).

METHODS

We conducted a comprehensive search to identify published studies about symptom clusters among PLWH. Databases including PubMed/MEDLINE, MEDLINE (Ovid), EMBASE (Ovid), CINAHL (EBSCO), Web of Science, and ProQuest Dissertations and Thesis were searched for studies published between January 2000 and December 2018.

RESULTS

Thirteen articles were eligible for inclusion. Five most commonly reported symptom clusters were found: 1) sad/depressed/loss of interest and nervous/anxious/worrying; 2) difficulty sleeping, problems with having sex, and fatigue/loss of energy; 3) fever/chills/sweat, nausea/vomiting, and loss of appetite; 4) numbness, muscle aches, and joint pain; and 5) dizziness and headache.

CONCLUSION

This systematic review summarized the compositions, measures, and analytical techniques of symptom clusters for PLWH. Although this review found unstable results on the compositions of symptom clusters and it was difficult to reach a definitive conclusion, the results still implicate the necessity of developing a threshold to decide what symptoms should be included in the clusters and the use of multiple data analysis techniques to obtain stable results.

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.

Identifying Symptom Clusters Among People Living With HIV on Antiretroviral Therapy in China: A Network Analysis

CONTEXT

There exists a research interest shift from separate symptoms to symptom clusters among people living with HIV (PLWH), which may provide a better understanding of symptom management in HIV/AIDS care. However, the symptom clusters among Chinese PLWH are still unknown.

OBJECTIVES

The aim of our study was to identify symptom clusters and to examine demographic and health-related factors associated with these symptom clusters among PLWH prescribing antiretroviral therapy (ART) in China.

METHODS

From April to September 2017, we recruited 1116 participants through a convenience sampling in five HIV/AIDS designated facilities in the eastern, middle, and southwest regions of China. The principal component analysis was used to identify the symptom clusters. Association network was adopted to describe the relationships among symptoms and clusters. A multiple linear model was used to investigate the associated factors for the severity of overall symptoms and the prevalence of each symptom clusters.

RESULTS

Five symptom clusters were identified, including cognitive dysfunction, mood disturbance, wasting syndrome, dizziness/headache, and skin-muscle-joint disorder. Cognitive dysfunction was the most central symptom cluster. Variables including primary caregiver during ART treatment, years of HIV diagnosis and ART use, having comorbidity, self-rated health, and quality of life were associated with the prevalence of these five symptom clusters.

CONCLUSION

Our study suggests that there is a need to evaluate symptom clusters for the improvement of symptom management among PLWH. It is particularly important to include assessment and treatment of cognitive symptoms as an essential component of the HIV care.

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.

Symptom Cluster Science in Chronic Kidney Disease: A Literature Review

The purpose of this review was to synthesize evidence on symptom clusters in patients with chronic kidney disease (CKD). The quality of studies was evaluated using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Twelve articles met inclusion criteria. Patients had CKD ranging from Stages 2 through 5. Most studies determined clusters using variable-centered approaches based on symptoms; however, one used a person-centered approach based on demographic and clinical characteristics. The number of clusters identified ranged from two to five. Several clusters were prominent across studies including symptom dimensions of fatigue/energy/sleep, neuromuscular/pain, gastrointestinal, skin, and uremia; however, individual symptoms assigned to clusters varied widely. Several clusters correlated with patient outcomes, including health-related quality of life and mortality. Identifying symptom clusters in CKD is a nascent field, and more research is needed on symptom measures and statistical methods for clustering. The clinical implications of symptom clusters remain unclear.

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.

Symptom clusters and treatment time delay in Korean patients with ST-elevation myocardial infarction on admission

Most patients with acute myocardial infarction (AMI) experience more than one symptom at onset. Although symptoms are an important early indicator, patients and physicians may have difficulty interpreting symptoms and detecting AMI at an early stage. This study aimed to identify symptom clusters among Korean patients with ST-elevation myocardial infarction (STEMI), to examine the relationship between symptom clusters and patient-related variables, and to investigate the influence of symptom clusters on treatment time delay (decision time [DT], onset-to-balloon time [OTB]). This was a prospective multicenter study with a descriptive design that used face-to-face interviews. A total of 342 patients with STEMI were included in this study. To identify symptom clusters, two-step cluster analysis was performed using SPSS software. Multinomial logistic regression to explore factors related to each cluster and multiple logistic regression to determine the effect of symptom clusters on treatment time delay were conducted. Three symptom clusters were identified: cluster 1 (classic MI; characterized by chest pain); cluster 2 (stress symptoms; sweating and chest pain); and cluster 3 (multiple symptoms; dizziness, sweating, chest pain, weakness, and dyspnea). Compared with patients in clusters 2 and 3, those in cluster 1 were more likely to have diabetes or prior MI. Patients in clusters 2 and 3, who predominantly showed other symptoms in addition to chest pain, had a significantly shorter DT and OTB than those in cluster 1. In conclusion, to decrease treatment time delay, it seems important that patients and clinicians recognize symptom clusters, rather than relying on chest pain alone. Further research is necessary to translate our findings into clinical practice and to improve patient education and public education campaigns.

A cluster and inferential analysis of myocardial infarction symptom presentation by age

BACKGROUND

Pre-hospital delay time in myocardial infarction is usually longer in older than in younger patients, with symptom presentation known to be a contributing factor.

AIM

The aim of this article is to examine symptom presentation differences, by age, in patients with myocardial infarction.

METHODS

This is a cross-sectional study using secondary analysis of a multi-site randomised controlled trial on pre-hospital delay time. Data were analysed using logistic regression and factor analysis.

RESULTS

Post-myocardial infarction patients were recruited prior to discharge ( n=1211), 54% were ≥65 years and 80% male. The average number of symptoms was three, with the ≥65 years age group reporting significantly less symptoms. Logistic regression controlling for gender, diabetes and diagnosis with 11 symptoms (χ²=52.09, p<0.001) was significant. Those ≥65 years had less chest symptoms, sweating, stomach upset and left arm pain, in addition to longer pre-hospital delay time. This group also had less symptom clustering and fewer symptoms within atypical clusters. Non-chest clusters occurred in 22% and 18% of the older and younger group respectively. Of note, two clusters 'atypical' (upset stomach/sweating) and 'typical arm' (right and left arm pain symptoms), accounted for 14% and 5% of myocardial infarction presentations in the ≥65 years group, within which 25% and 24% had no chest symptoms.

CONCLUSIONS

The results of this study indicate that myocardial infarction symptom presentation in older patients is likely to be less recognisable and more complex. Increased awareness of the presentation profile of older patients could expedite their triage, diagnosis and, consequently, their prognosis.

Sex differences in presenting symptoms of acute coronary syndrome: the EPIHeart cohort study

OBJECTIVES

Prompt diagnosis of acute coronary syndrome (ACS) remains a challenge, with presenting symptoms affecting the diagnosis algorithm and, consequently, management and outcomes. This study aimed to identify sex differences in presenting symptoms of ACS.

DESIGN

Data were collected within a prospective cohort study (EPIHeart).

SETTING

Patients with confirmed diagnosis of type 1 (primary spontaneous) ACS who were consecutively admitted to the Cardiology Department of two tertiary hospitals in Portugal between August 2013 and December 2014.

PARTICIPANTS

Presenting symptoms of 873 patients (227 women) were obtained through a face-to-face interview.

OUTCOME MEASURES

Typical pain was defined according to the definition of cardiology societies. Clusters of symptoms other than pain were identified by latent class analysis. Logistic regression was used to quantify differences in presentation of ACS symptoms by sex.

RESULTS

Chest pain was reported by 82% of patients, with no differences in frequency or location between sexes. Women were more likely to feel pain with an intensity higher than 8/10 and this association was stronger for patients aged under 65 years (interaction P=0.028). Referred pain was also more likely in women, particularly pain referred to typical and atypical locations simultaneously. The multiple symptoms cluster, which was characterised by a high probability of presenting with all symptoms, was almost fourfold more prevalent in women (3.92, 95% CI 2.21 to 6.98). Presentation with this cluster was associated with a higher 30-day mortality rate adjusted for the GRACE V.2.0 risk score (4.9% vs 0.9% for the two other clusters, P<0.001).

CONCLUSIONS

While there are no significant differences in the frequency or location of pain between sexes, women are more likely to feel pain of higher intensity and to present with referred pain and symptoms other than pain. Knowledge of these ACS presentation profiles is important for health policy decisions and clinical practice.

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.

It is not just menopause: symptom clustering in the Study of Women's Health Across the Nation

Background

Patterns of symptom clustering in midlife women may suggest common underlying mechanisms or may identify women at risk of adverse health outcomes or, conversely, likely to experience healthy aging. This paper assesses symptom clustering in the Study of Women’s Health Across the Nation (SWAN) longitudinally by stage of reproductive aging and estimates the probability of women experiencing specific symptom clusters. We also evaluate factors that influence the likelihood of specific symptom clusters and assess whether symptom clustering is associated with women’s self-reported health status.

Methods

This analysis includes 3289 participants in the multiethnic SWAN cohort who provided information on 58 symptoms reflecting a broad range of physical, psychological and menopausal symptoms at baseline and 7 follow-up visits over 16 years. We conducted latent transition analyses to assess symptom clustering and to model symptomatology across the menopausal transition (pre, early peri-, late peri- and post-menopausal). Joint multinomial logistic regression models were used to identify demographic characteristics associated with premenopausal latent class membership. A partial proportional odds regression model was used to assess the association between latent class membership and self-reported health status.

Results

We identified six latent classes that ranged from highly symptomatic (LC1) across most measured symptoms, to moderately symptomatic across most measured symptoms (LC2), to moderately symptomatic for a subset of symptoms (vasomotor symptoms, pain, fatigue, sleep disturbances and physical health symptoms) (LC3 and LC5) with one class (LC3) including interference in life activities because of physical health symptoms, to numerous milder symptoms, dominated by fatigue and psychological symptoms (LC4), to relatively asymptomatic (LC6). In pre-menopause, 10% of women were classified in LC1, 16% in LC2, 14% in LC3 and LC4, 26% in LC5, and 20% in LC6. Intensity of vasomotor and urogenital symptoms as well as sexual desire) differed minimally by latent class. Classification into the two most symptomatic classes was strongly associated with financial strain, White race/ethnicity, obesity and smoking status. Over time, women were most likely to remain within the same latent class as they transitioned through menopause stages (range 39–76%), although some women worsened or improved. The probability of moving between classes did not differ substantially by menopausal stage. Women in the highly symptomatic classes more frequently rated their health as fair to poor compared to women in the least symptomatic class.

Conclusion

Clear patterns of symptom clustering were present early in midlife, tended to be stable over time, and were strongly associated with self-perceived health. Notably, vasomotor symptoms tended to cluster with sleep disturbances and fatigue, were present in each of the moderate to highly symptomatic classes, but were not a defining characteristic of the symptom clusters. Clustering of midlife women by symptoms may suggest common underlying mechanisms amenable to interventions. Given that one-quarter of midlife women were highly or moderately symptomatic across all domains in the pre-menopause, addressing symptom burden in early midlife is likely critical to ameliorating risk in the most vulnerable populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s40695-017-0021-y) contains supplementary material, which is available to authorized users.

The Clinical Efficacy of Yindanxinnaotong Soft Capsule in the Treatment of Stroke and Angina Pectoris: A Meta-Analysis

Objective. To systematically evaluate the clinical efficacy of Yindanxinnaotong (YD) soft capsule in adult patients with cardiovascular diseases (stroke and angina pectoris). Methods. We electronically searched databases including Medline, PubMed, Chinese National Knowledge Infrastructure (CNKI), Cqvip Database (VIP), and Wanfang Database for published articles of randomized controlled trials (RCTs) of YD capsule in treating stroke and angina pectoris. The meta-analysis was performed using RevMan 5.3 software. Results. 49 RCTs involving 6195 subjects with cardiovascular diseases (angina pectoris and stroke) were included. Compared with western conventional medicine (WCM) and/or other Chinese medicines, YD plus WCM therapeutic regimen could significantly improve the efficacy rate (RR = 1.21, 95% CI (1.17, 1.25), P < 0.00001 for angina pectoris, RR = 1.24, 95% CI (1.18, 1.31), P < 0.00001 for stroke), showing the clinical value. In addition, the therapeutic efficiency of WCM plus YD capsule regimen is better than that of WCM alone in improving CRP (MD = −2.07, 95% CI (−3.97, −0.17), P = 0.03 <0.05) and TG (MD = −0.37, 95% CI (−0.52, −0.23), P < 0.0001). Conclusion. YD is effective in the treatment of cardiovascular diseases (angina pectoris and stroke) in adults, and WCM plus YD therapeutic regimen can significantly improve the effective rate in the clinic.