Diabetes Changes Symptoms Cluster Patterns in Persons Living With HIV

Health-related quality of life and associated factors among people living with HIV/AIDS in Sichuan, China: A cross-sectional study

Purpose

This study aimed to explore health-related quality of life (HRQoL) and its associated factors among people living with HIV/AIDS (PLWH) in Sichuan, China.

Methods

A total of 401 PLWH were recruited from the city of Panzhihua between August 2018 and January 2019. Demographic characteristics and disease-related data were collected by self-administered questionnaires and medical system records. Health-related quality of life (HRQoL) was measured by the medical outcome study HIV health survey (MOS-HIV), which measured ten subdimensions and two summarized dimensions, the physical health summary score (PHS) and the mental health summary score (MHS). Logistic regression models were used to explore the variables independently associated with quality of life.

Results

The PHS and MHS measured by MOS-HIV were 53.66 ± 6.80 and 51.31 ± 7.66, respectively. Younger age, higher educational level, no methadone use, higher CD4 lymphocyte counts, less symptom counts and heathy BMI significantly were associated with higher HRQOL in the univariate χ2-test analysis. Education level was found to have a significant influence on patients' quality of life, both in physical health (P = 0.022) and mental health (P = 0.002) dimensions. Younger age (P = 0.032), higher CD4 lymphocyte counts (P = 0.007), less symptom counts (P < 0.001) and health BMI level (P < 0.001) were positively related to the PHS of quality of life in the multivariable logistic regression model.

Conclusion

The HRQoL of PLWH in Sinchuan Province was relatively low. Age, educational level, methadone use, CD4 lymphocyte counts, symptom counts and BMI were positively related to quality of life. This study indicates that health caregivers should pay more attention to comorbidity issues and mental health in PLWH, especially for those with lower education levels, unhealthy body mass index, more symptomatic presentation and older age.

HIV Symptom Clusters are Similar Using the Dimensions of Symptom Occurrence and Distress

CONTEXT

People living with HIV infection (PLWH) in the United States continue to experience a high symptom burden despite improvements in antiretroviral therapy.

OBJECTIVES

The purpose of this study was to determine if the number and types of symptom clusters differed based on whether symptom occurrence rates or distress ratings were used to create the clusters.

METHODS

Data from 2,000 patients with complete symptom occurrence rates and distress scores on the 20-item HIV Symptom Index from their first ambulatory clinic visit at one of six national HIV centers of excellence in the Center for AIDS Research Network of Integrated Clinical Systems were used in these analyses. Exploratory factor analysis was used to create the symptom clusters.

RESULTS

The same four symptom clusters (i.e., gastrointestinal, psychological, pain, body image) were identified using occurrence rates and distress ratings. For both dimensions of the symptom experience, the psychological, pain, and body image clusters each had the same symptoms. For the gastrointestinal cluster, four symptoms loaded on the occurrence dimension and six symptoms loaded on the distress dimension.

CONCLUSION

The number and types of symptom clusters were relatively similar across the occurrence and distress dimensions of the symptom experience. Symptom clusters in PLWH may provide insights into the development of targeted interventions for multiple co-occurring symptoms.

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.

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.

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.

Differences in Health-Related Quality of Life Predictors in People Living With HIV With and Without Diabetes

Diabetes is one of the most common comorbid conditions in people living with HIV (PLWH). Diabetes may affect health-related quality of life (HRQoL) for PLWH because they experience more symptoms, are prescribed more medications, and are required to do self-care activities. The purpose of our study was to compare predictors of the HRQoL for PLWH with and without diabetes. The study was a secondary analysis of data from the Center for AIDS Research Network of Integrated Clinical Systems cohort using multiple regression. Significant differences were found between PLWH with and without diabetes. The significant predictors of HRQoL for PLWH-alone were depression, anxiety, medication adherence, physical activity, smoking, and age. For PLWH with diabetes, the only significant predictors of HRQoL were anxiety and depression.

The Patient-Provider Continuum of Care: Narratives of People Living With Comorbid HIV and Diabetes in Northern Thailand

Background:

Among South-East Asia Region countries, Thailand has a high prevalence of HIV with an increasing significant comorbidity of diabetes mellitus (DM).

Objective:

Guided by syndemics, the purpose of this qualitative study is to develop insight into the experience of patients living with comorbid HIV and DM in Northern Thailand for quality improvement.

Methods:

Interviews were conducted in 2 groups for content analysis: (1) people living with comorbid HIV and DM and (2) health-care staff providing care to patients living with the comorbidity.

Results:

Participants’ (N = 12) ages ranged from 42 to 56 (mean = 49). Health staff (N = 12) generated complementary narratives. All participants reported onset of diabetes after discovering they were HIV infected. Content analysis revealed emergent themes regarding (1) knowledge and perceptions and (2) management framed by syndemics and chronicity.

Conclusion:

Findings suggest routine training for patient education and provider integration of care. Macrosocial factors such as limited access and resources and biological factor such as drug interactions are noted as key considerations for future interventions and alterations in the care for patients with comorbid HIV and DM.

Integrated network analysis of symptom clusters across disease conditions

Identifying the symptom clusters (two or more related symptoms) with shared underlying molecular mechanisms has been a vital analysis task to promote the symptom science and precision health. Related studies have applied the clustering algorithms (e.g. k-means, latent class model) to detect the symptom clusters mostly from various kinds of clinical data. In addition, they focused on identifying the symptom clusters (SCs) for a specific disease, which also mainly concerned with the clinical regularities for symptom management. Here, we utilized a network-based clustering algorithm (i.e., BigCLAM) to obtain 208 typical SCs across disease conditions on a large-scale symptom network derived from integrated high-quality disease-symptom associations. Furthermore, we evaluated the underlying shared molecular mechanisms for SCs, i.e., shared genes, protein-protein interaction (PPI) and gene functional annotations using integrated networks and similarity measures. We found that the symptoms in the same SCs tend to share a higher degree of genes, PPIs and have higher functional homogeneities. In addition, we found that most SCs have related symptoms with shared underlying molecular mechanisms (e.g. enriched pathways) across different disease conditions. Our work demonstrated that the integrated network analysis method could be used for identifying robust SCs and investigate the molecular mechanisms of these SCs, which would be valuable for symptom science and precision health.

Assessment and Management of HIV Distal Sensory Peripheral Neuropathy: Understanding the Symptoms

Distal sensory peripheral neuropathy (HIV-DSP) affects upwards of 50% of people living with HIV. Causing often debilitating symptoms of tingling, numbness and burning, HIV-DSP can result in disability, unemployment and low quality of life. Comorbidities further complicate nursing care, heightening risk of polypharmacy and symptom exacerbation. Therefore, a neurological sensory assessment, combined with the patient's self-report of symptoms, can help nurse practitioners visualize, quantify and understand symptoms. Common pharmacological interventions include antiepileptics, antidepressants, analgesics and medical marijuana. The complexity of care for individuals with HIV-DSP merits a comprehensive approach. Implications for practice include interdisciplinary management with neurologists, podiatrists, mental health providers, and nurse-led counseling inclusive of patient safety teaching.

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.

The effect of increased physical activity on symptom burden in older persons living with HIV

Advancements in antiretroviral therapy have extended the longevity of people living with HIV (PLWH). However, they often experience symptoms that negatively impact their quality of life, including fatigue, weight change, depression, pain, and memory loss. Although there is a dearth of data on the effect of physical activity (PA) for HIV-associated symptom management, increased PA has generally been associated with improvements in strength and overall quality of life. In this study, we enrolled 40 participants (mean age = 51.5; 40% female; 17.4 mean years living with HIV) and used Omron pedometers to measure daily step counts over 12 weeks. The 20-item HIV Symptom Index was administered at baseline and week 12. Increased PA was not associated with improvement in overall HIV symptom burden. However, bothersome symptoms were reduced, and total symptom burden was highly correlated with PA level at week 12 (r = -.48, p = .01), such that participants with  higher step counts reported lower symptom burden. Significant gender differences in symptom burden were noted: males on average reported lower symptom burden. Further research is needed to examine associations between PA and HIV symptom burden and to further explore gender differences in HIV symptom burden to improve overall quality of life for all older PLWH.

A Framework for Using eHealth Interventions to Overcome Medical Mistrust Among Sexual Minority Men of Color Living with Chronic Conditions

The purpose of this paper is to present a stepwise, multi-construct, innovative framework that supports the use of eHealth technology to reach sexual minority populations of color to establish trustworthiness and build trust. The salience of eHealth interventions can be leveraged to minimize the existing paradigm of medical mistrust among sexual minority populations of color living with chronic illnesses. These interventions include virtual environments and avatar-led eHealth videos, which address psychosocial and structural-level challenges related to mistrust. Our proposed framework addresses how eHealth interventions enable technology adoption and usage, anonymity, co-presence, self-disclosure, and social support and establish trustworthiness and build trust.

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.

Mexican Americans' diabetes symptom prevalence, burden, and clusters

AIMS

Type 2 diabetes mellitus (T2DM), serious and increasingly prevalent among Mexican Americans, produces symptoms related to high and low glucose levels, medication side effects, and long-term complications. This secondary analysis explored symptom prevalence, differences among symptom burden levels, and how symptoms clustered.

METHODS

Clinical measurements and survey data (demographic, quality of life, and the symptom subscale of the Diabetes Symptom Self-Management Inventory) collected from Mexican American adults with T2DM (n = 71) were analyzed for symptom prevalence, differences across levels of symptom burden, and symptom clusters. Agglomerative hierarchical and k-means clustering analyses were performed on a Gower matrix. Internal validation methods and rank aggregation were used to identify the best clustering method of the two techniques and to identify symptoms that clustered together.

RESULTS

Participants reported mean = 14 symptoms; tiredness and trouble sleeping were most prevalent. People with high symptom burden had significantly lower quality of life and perceptions of worse diabetes severity. Hierarchical clustering produced three symptom clusters: cluster 1 = 9 symptoms (e.g. intense thirstiness, dry mouth); cluster 2 = 9 symptoms (e.g., itching skin, weight gain, noise or light sensitivity); cluster 3 = 13 symptoms (e.g., nervous, headache, trouble concentrating, and memory loss).

CONCLUSION

Mexican Americans with T2DM report several co-occurring symptoms. Quality of life is significantly worse for people with high symptom burden. Three distinct symptom clusters were identified. Studies with larger samples are needed to further diabetes symptom science. Clinicians should assess and address patients' co-occurring symptoms as a potential means of decreasing symptom burden and improving quality of life.