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

Symptom profiles in patients receiving maintenance hemodialysis and their association with quality of life: a longitudinal study

PURPOSE

Many patients receiving maintenance hemodialysis experience one or multiple symptoms. Using a latent profile analysis to identify symptom profiles may provide insights for person-centered symptom management strategies.

METHODS

This is a longitudinal study based on data from patients receiving maintenance hemodialysis at three hospitals in Shanghai, China. Of the 448 patients who completed the surveys at baseline (T1), 309 completed the 12-month follow-up survey (T2). Symptoms and quality of life were measured by the Chinese version of Kidney Disease Quality of Life 36 Short Form. The optimal classification of symptoms was identified using latent profile analysis.

RESULTS

Five symptom profiles were identified: High (9.2%), Fatigue and Gastrointestinal (7.1%), Fatigue and Skin (10.7%), Skin (23.2%), and Low (49.8%). The high-symptom profile and the-fatigue-and-skin-symptom profile were associated with a lower level of physical functioning, a higher burden of kidney disease, and more negative effects of kidney disease than the low symptom profile at T1 and T2. Multivariate regression analysis showed that the high-symptom profile predicted a poorer physical functioning at T2, and the-fatigue-and-skin-symptom profile predicted a poorer physical functioning and higher burden of kidney disease at T2.

CONCLUSION

Patients receiving maintenance hemodialysis reported unique symptom experiences which could be classified into different profiles. Patients reporting an overall high level of symptoms or a high level of fatigue and skin symptoms were more likely to have a poorer quality of life.

The Heterogeneity of Symptom Burden and Fear of Progression Among Kidney Transplant Recipients: A Latent Class Analysis

Purpose

Kidney transplant recipients (KTRs) may experience symptoms that increase their fear of progression (FoP), but a dearth of research examines the issue from a patient-centered perspective. Our study aimed to first determine the category of symptom burden, then to explore the differences in characteristics of patients in different subgroups, and finally to analyze the impact of symptom subgroup on FoP.

Patients and Methods

Sociodemographic and Clinical Characteristics, Symptom Experience Scale, and Fear of Progression Questionnaire-Short Form were used. Latent class analysis was used to group KTRs according to the occurrence of symptoms. We used multivariate logistic regression to analyze the predictors of different subgroups. The differences in FoP among symptom burden subgroups were analyzed by hierarchical multiple regression.

Results

Three subgroups were identified, designated all-high (20.5%), moderate (39.9%), and all-low (39.6%) according to their symptom occurrence. Multivariate logistic regression showed that gender, post-transplant time, per capita monthly income, and hyperuricemia were the factors that distinguished and predicted the all-high subgroup (P < 0.05). Hierarchical multiple regression showed that symptom burden had a significant effect on FoP (class1 vs class3: β = 0.327, P < 0.001; class2 vs class3: β = 0.104, P = 0.046), explaining the 8.0% variance of FoP (ΔR2 = 0.080).

Conclusion

KTRs generally experience moderate or low symptom burden, and symptom burden is an influencing factor in FoP. Identifying the traits of KTRs with high symptom burden can help clinicians develop targeted management strategies and ease FoP of KTRs.

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 Experiences of Patients Operated for Oral Cancer: A Mixed Methods Study

OBJECTIVE

This convergent mixed methods study aimed to obtain a comprehensive understanding of symptom cluster experiences in patients with oral cancer. Survey and phenomenological interviews were conducted in parallel to identify distinct patient subgroups based on symptom cluster experiences along with their predictors and explore experiences of living with symptom clusters, respectively.

DATA SOURCES

A convenience sample of 300 patients with oral cancer who had completed surgery provided the quantitative data, and a maximum variation purposive subsample of 20 participants, drawn from the survey sample, provided the qualitative data. Agglomerative hierarchical cluster analysis was used to identify subgroups, multivariate analyses were done to identify predictors, and thematic analysis was used for patient narratives.

CONCLUSION

Almost 94% of the survey participants had two or more co-occurring symptoms. The four most severe and prevalent symptoms were dysphagia, problems with teeth or gums, speech difficulty, and dry mouth. A distinct subgroup consisting of 61% of patients reported severe dysphagia and teeth problems, which was associated with age, oral cancer stage and site. Interviews revealed the causes and the context influencing the perception and response to these symptoms. Thus, the quantitative data provided information on severity and patient subgroups based on symptom cluster experiences, while the qualitative data validated these conclusions and additionally provided in-depth details and meaningful insight on perceived causes and contextual influences of their experiences. This comprehensive picture of symptom cluster experiences can aid in the development of patient-centered interventions for people with oral cancer.

IMPLICATIONS FOR NURSING PRACTICE

An interdisciplinary approach to targeting concurrent symptoms incorporating psychological and physical interventions is necessary. Older patients treated for Stage IV cancers and for buccal mucosa tumors are at high-risk of having severe dysphagia postoperatively, and these patients should be targeted for dysphagia interventions. The contextual factors play an important role in developing patient-centered interventions.

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.

Distinct Dysphagia Profiles in Patients With Oral Cancer After Surgery

OBJECTIVES

To determine distinct profiles based on symptom severity in patients undergoing surgery for oral cancer and examine whether these profiles differ by participant characteristics.

SAMPLE & SETTING

300 patients who underwent surgery for oral cancer at two outpatient clinics between June and December 2021.

METHODS & VARIABLES

Symptoms were assessed using the MD Anderson Symptom Inventory-Head and Neck Cancer Module. Sociodemographic and clinical characteristics were collected. Latent profile analysis was performed.

RESULTS

Five distinct dysphagia profiles were identified, which qualitatively differed regarding co-occurrence patterns of dysphagia, mucus-related symptoms, speech disturbances, and psychoneurologic symptoms. Significant differences were reported in interference to function, number of co-occurring symptoms, time since diagnosis and treatment completion, use of symptom management medications, oral cancer stage and site, and treatment completed.

IMPLICATIONS FOR NURSING

Identifying distinct dysphagia profiles can improve patient outcomes and help in planning specific nursing interventions to influence nutritional and functional status in oral cancer survivors. Dysphagia and dry mouth can persist beyond one year post-treatment, so follow-up dysphagia assessments are needed.

Symptom Clusters in Head and Neck Cancer: A Systematic Review and Conceptual Model

OBJECTIVE

The two approaches to symptom-cluster research include grouping symptoms and grouping patients. The objective of this systematic review was to examine the conceptual approaches and methodologies used in symptom-cluster research in patients with head and neck cancer.

DATA SOURCES

Articles were retrieved from electronic databases (CINAHL, MEDLINE via Ovid, APA PsycINFO, Scopus, Embase, and Cochrane Central Register of Controlled Trials-CENTRAL), five grey literature portals, and Google Scholar. Seventeen studies met the eligibility criteria. Eight studies grouped symptoms to identify symptom clusters, of which two used qualitative methods. The number of symptom clusters ranged from two to five, and the number of symptoms in a cluster ranged from 2 to 11. Nine studies grouped patients based on their experiences with multiple symptoms. Cluster analysis and factor analysis were most commonly used. Despite variable names and composition of symptom clusters, synthesis revealed three prominent symptom clusters: general, head and neck cancer-specific, and gastrointestinal. Being female and quality of life were significantly associated with high symptom group or cluster severity. Biological mechanisms were sparsely examined.

CONCLUSION

Symptom cluster research in head and neck cancer is emerging. Consensus on nomenclature of a symptom cluster will facilitate deduction of core clinically relevant symptom clusters in head and neck cancer. Further research is required on understanding patients' subjective experiences, identifying predictors and outcomes, and underlying mechanisms for symptom clusters.

IMPLICATIONS FOR NURSING PRACTICE

Identification of clinically relevant symptom clusters would enable targeted symptom assessment and management strategies, thus improving treatment efficiencies and patient outcomes.

Physical Symptom Cluster Subgroups in Chronic Kidney Disease

BACKGROUND

Symptom burden associated with chronic kidney disease can be debilitating, with a negative effect on patient health-related quality of life. Latent class clustering analysis is an innovative tool for classifying patient symptom experience.

OBJECTIVES

The aim of the study was to identify subgroups of patients at greatest risk for high symptom burden, which may facilitate development of patient-centered symptom management interventions.

METHODS

In this cross-sectional analysis, baseline data were analyzed from 3,921 adults enrolled in the Chronic Renal Insufficiency Cohort Study from 2003 to 2008. Latent class cluster modeling using 11 items on the Kidney Disease Quality of Life symptom profile was employed to identify patient subgroups based on similar observed physical symptom response patterns. Multinomial logistic regression models were estimated with demographic variables, lifestyle and clinical variables, and self-reported measures (Kidney Disease Quality of Life physical and mental component summaries and the Beck Depression Inventory).

RESULTS

Three symptom-based subgroups were identified, differing in severity (low symptom, moderate symptom, and high symptom). After adjusting for other variables in multinomial logistic regression, membership in the high-symptom subgroup was less likely for non-Hispanic Blacks and men. Other factors associated with membership in the high-symptom subgroup included lower estimated glomerular filtration rate, history of cardiac/cardiovascular disease, higher Beck Depression Inventory scores, and lower Kidney Disease Quality of Life physical and mental component summaries.

DISCUSSION

Three symptom subgroups of patients were identified among patients with mild-to-moderate chronic kidney disease. Several demographic and clinical variables predicted membership in subgroups. Further research is needed to determine if symptom subgroups are stable over time and can be used to predict healthcare utilization and clinical outcomes.