Symptom Clusters Research Articles

Psychological and Biological Stress Pathways as Common Mechanisms Underlying a Psycho-Neurological Symptom Cluster in Cancer Patients: Perceived Stress, Cortisol, and ACTH

ObjectiveThis study aimed to examine (a) whether psychological stress is associated with experiencing multiple psycho-neurological symptoms (depression, cognitive impairment, fatigue, sleep disturbance, and pain) as a cluster and (b) whether stress hormones (adrenocorticotropic hormone [ACTH] and cortisol) are associated with psychological stress and symptom cluster experience. MethodsThis cross-sectional study analyzed data from 133 patients with hematologic cancer awaiting chemotherapy. Enzyme-linked immunosorbent assays analyzed the morning stress hormone levels (ACTH and cortisol). Latent profile analyses identified the group experiencing a psycho-neurological symptom cluster. Factors influencing the experience of the psycho-neurological symptom cluster were included as covariates and analyzed using multinomial logistic regression. ResultsThirty-three percent (n=44) experienced all five psycho-neurological symptoms as a cluster and experienced each symptom in a higher severity than those who did not experience the symptom cluster (ps <.05). Thereby, this group legitimately experienced the psycho-neurological symptom cluster. The major determinant of this group was the perceived psychological stress (OR = 8.05, 95% CI = 3.08; 20.99). Further, each symptom demonstrated a positive association with stress levels (correlation r ranged from 0.22 to 0. 56, all ps < 0.05). Participants with higher stress were more likely to experience the symptom cluster. Stress hormones levels (ACTH and cortisol) were neither associated with the symptom cluster experience nor with psychological stress levels. ConclusionsPsychological stress, rather than biological stress response, is involved in experiencing the psycho-neurological symptom cluster. Managing stress levels would help alleviate this symptom cluster.

Features and Differences in Core Symptom Clusters in Home-Based Hospice Patients With Advanced Cancer: A Network Analysis.

Patients with terminal-stage cancer frequently experience multiple symptoms simultaneously. Little is known about how core symptom clusters differ in advanced-cancer patients with different survival expectancies receiving hospice care. To identify the core symptom clusters of hospice-care cancer patients with different survival expectancies and compare the features of their symptom networks. In this retrospective study, secondary data analysis was conducted. Records of 6946 patients with advanced cancer who received home-based hospice care service in a hospice center from April 2001 to December 2020 were collected and analyzed using network analysis. This analysis included 6946 patients with advanced cancer receiving hospice care. In patients with survival expectancies of 0-6 months, loss of appetite was identified as the core symptom (rs = 4.03, rb = 5.21, rc = 2.63), and five symptom clusters were identified. Malnutrition was the core symptom in patients with survival expectancies of 6-12 months (rs = 2.83, rb = 2.43, rc = 0.93), and nine symptom clusters were identified. Wasting syndrome was the core symptom cluster in two groups. The network density of symptoms in patients with < 6 months of survival expectancy (91.99) was higher than in patients with 6-12 months (28.39). Nutrition impact symptoms are the core symptoms for home-hospice care cancer patients with a survival period of 1 year or below. Moreover, hospice cancer patients with short survival expectancies have greater inter-symptom impact.

Gender differences in the relationship between depressive symptoms and diabetes associated with cognitive-affective symptoms.

Despite the frequent co-occurrence of depression and diabetes, gender differences in their relationship remain unclear. This exploratory study examined if gender modifies the association between depressive symptoms, prediabetes and diabetes with cognitive-affective and somatic depressive symptom clusters. Cross-sectional analyses were conducted on 29 619 participants from the 2007-2018 National Health and Nutrition Examination Survey. Depressive symptoms were measured by the nine-item Patient Health Questionnaire. Multiple logistic regression was used to analyse the relationship between depressive symptoms and diabetes. Multiple linear regression was used to analyse the relationship between depressive symptom clusters and diabetes. The odds of having depressive symptoms were greater in those with diabetes compared to those without. Similarly, total symptom cluster scores were higher in participants with diabetes. Statistically significant diabetes-gender interactions were found in the cognitive-affective symptom cluster model. Mean cognitive-affective symptom scores were higher for females with diabetes (coefficient = 0.23, CI: 0.10, 0.36, P = 0.001) than males with diabetes (coefficient = -0.05, CI: -0.16, 0.07, P = 0.434) when compared to the non-diabetic groups. Diabetes was associated with higher cognitive-affective symptom scores in females than in males. Future studies should examine gender differences in causal pathways and how diabetic states interact with gender and influence symptom profiles.

Identification of Potential Diagnostic Markers for Depressive Disorders using Urinary Biomarkers of N-Methylnicotinamide and Hippuric Acid

Introduction: The diagnostic methodology for depressive disorders, relying on symptom clusters, has inherent limitations in ensuring heterogeneity levels. Consequently, this presents a notable risk of inevitable diagnostic errors in mental health assessments. Therefore, advocating for objective diagnostic approaches through empirical testing in clinical settings becomes crucial for individuals dealing with depressive disorders. This study aims to identify the effectiveness of urine as a diagnostic support for depressive disorders using the N-Methylnicotinamide and Hippuric Acid biomarkers. Methods: This study used 13 urine samples from patients with depressive disorders and 13 normal urine samples. It used ELISA methods with observational analytic and cross-sectional designs. Results: The results showed that the N-methylnicotinamide biomarker had a relationship with depressive disorders with a correlation value of 0.867, while hippuric acid obtained a correlation value of 0.692. Besides, the N-Methylnicotinamide and Hippuric Acid biomarkers showed differences in the urine of depressive disorder and normal patients with significance values of 0.000 and 0.001 for the N-Methylnicotinamide and Hippuric Acid biomarkers, respectively. In addition, the Relative Operating Characteristics curve analysis showed that these two biomarkers had good sensitivity and specificity values in assisting the diagnosis of depressive disorders. N-methylnicotinamide has a sensitivity of 92.3% and a specificity of 100%, while hippuric acid has a sensitivity of 76.9% and a specificity of 84.6%. Conclusions: Significant differences in the biomarkers of N-methylnicotinamide and hippuric acid in the urine of depressed patients compared to normal patients. Therefore, these biomarkers can be the empirical laboratory methods to support the diagnosis of depressive.

Bayesian additive regression trees for predicting childhood asthma in the CHILD cohort study

BackgroundAsthma is a heterogeneous disease that affects millions of children and adults. There is a lack of objective gold standard diagnosis that spans the ages; instead, diagnoses are made by clinician assessment based on a cluster of signs, symptoms and objective tests dependent on age. Yet, there is a clear morbidity associated with chronic asthma symptoms. Machine learning has become a popular tool to improve asthma diagnosis and classification. There is a paucity of literature on the use of Bayesian machine learning algorithms to predict asthma diagnosis in children. This paper develops a prediction model using the Bayesian additive regression trees (BART) and compares its performance to various machine learning algorithms in predicting the diagnosis of childhood asthma.MethodsClinically relevant variables collected at or before 3 years of age from 2794 participants in the CHILD Cohort Study were used to predict physician-diagnosed asthma at age 5. BART and six other commonly used machine learning algorithms, namely adaptive boosting, logistic regression, decision tree, neural network, random forest, and support vector machine were trained. Measures of performance including sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve were calculated. The confidence intervals were calculated using Bootstrapping samples. Important predictors and interaction effects associated with asthma were also identified using BART.ResultsBART, logistic regression and random forest showed the highest area under the ROC curve compared to other machine learning algorithms. Based on BART, recurrent wheeze, respiratory infection and food sensitization at 3 years of age were the most important predictors. The three most important interaction effects were found to be interaction terms of respiratory infection at 3 years and recurrent wheezing at 3 years, maternal asthma and paternal asthma, and maternal wheezing and inhalant sensitization of child at 3 years.ConclusionsBART demonstrated promising prediction performance when compared to other machine learning algorithms. Future research could validate the BART in an external cohort to evaluate its reliability and generalizability.

Assessing a Training Program for Integrative Medicine Practitioners in the Treatment of Acute Stress Disorder

ABSTRACTStudy ObjectiveThe study examined a training program for integrative medicine (IM) providers, teaching clinical skills for treating acute stress disorder (ASD).MethodsA 10‐h online training program, designed by IM and mental health professionals, was attended by a group of 32 IM providers working in supportive and palliative oncology care. Pre‐ and post‐course questionnaires assessed self‐perceived levels of IM and mental health ASD‐related skills (from 1, very low; to 7, very high).ResultsMost participants (25; 78%) completed pre‐ and post‐study questionnaires, which showed an increase in post‐course scores for the expectation that IM could reduce ASD‐related pain (p = 0.004). Scores for self‐assessed skill levels increased for treating gastro‐intestinal symptoms and appetite (p = 0.039) and for dyspnea (p = 0.048). A borderline increase for arousal was observed (p = 0.063), with no increase with other arousal symptom cluster symptoms.ConclusionsThe ASD‐focused training program for IM practitioners was associated with an increase in self‐perceived levels for related clinical skills quality of life‐related concerns, primarily pain, appetite and dyspnea. Further research is needed to better understand the implications of the findings, and to explore the implementation of the learned skills in clinical practice.

Agreement for posttraumatic stress symptoms among unaccompanied young refugees and professional caregivers

ABSTRACT Background: Prevalence rates for posttraumatic stress symptoms (PTSS) in unaccompanied young refugees (UYRs) are high. Research with biological parents indicates low agreement rates between self and caregiver reports for PTSS, although caregivers play an important role as gatekeepers to ensure appropriate treatment. Objective: This study examines youth and caregiver agreement on the endorsement of different trauma types, the PTSS severity score and symptom clusters, as well as the potential association between youth factors (age, comorbidity, and duration in facility) and disagreement. Method: The sample consisted of N = 610 UYRs, aged M = 16.75 (SD = 1.33, range: 12–20) years. Of these, 91.0% were male, and 43.4% were from Afghanistan, currently residing in German children and youth welfare facilities. Results: Agreement rates across trauma types were poor (accidental trauma: Cohen’s k = .13; community violence: Cohen’s k = .07; domestic violence: Cohen’s k = .19; sexual abuse: Cohen’s k = .38). Agreement rates for the PTSS severity score (ICC = .22) and symptom clusters were poor (re-experiencing: ICC = .27; avoidance: ICC = .02; negative alterations in cognitions and mood ICC = .12; hyperarousal: ICC = .25), with youth reporting significantly higher scores. Regression models showed that having comorbid symptoms and a shorter duration in the facility were associated with higher disagreement at the PTSS severity score (Adjusted ­R 2 = .21) and across symptom clusters (re-experiencing: Adjusted ­R 2 = .13; avoidance: Adjusted ­R 2 = .07; negative alterations in cognitions and mood: Adjusted ­R 2 = .16; hyperarousal: Adjusted­ R 2 = .16). Age was not significantly associated with disagreement rates. Conclusion: It is important to enhance the awareness and comprehension of caregivers regarding recognition of mental illnesses and their symptoms as well as assessing mental health among UYRs.

A Systematic Review of Comparative Effectiveness of Interventions for Low Anterior Resection Syndrome: Impacts on Bowel Function and Quality of Life.

Low anterior resection syndrome (LARS) is a common complication following sphincter-preserving surgical resection for rectal cancer, characterized by symptoms such as fecal incontinence, urgency, and altered bowel habits, which significantly affect patients' quality of life. This cluster of symptoms not only limits their day-to-day physical activity but also has a debilitating effect on their emotional and mental well-being, undermining their integration and overall psychological health. This systematic review aimed to evaluate the effectiveness of invasive and non-invasive interventions for LARS, including pelvic floor rehabilitation, transanal irrigation, and various surgical options such as sacral neuromodulation and stoma formation, either as part of primary surgery or as a definitive treatment option for refractory cases. We systematically searched relevant databases for studies published in the last decade, focusing on adult patients diagnosed with LARS post-low anterior resection (LAR), with outcomes assessed through bowel function and quality of life metrics. The review identified six studies that met our eligibility criteria; a pooled cohort of 794 patients was identified, with sample sizes ranging from 37 to 430 participants. Our analysis revealed that pelvic floor rehabilitation significantly improves bowel function and quality of life in patients with LARS; yet, the optimal management approach remains unclear due to variability in patient responses. These findings highlight the inherent complexity and heterogeneity of LARS management, underscoring the necessity for multifaceted and individualized treatment strategies. Although pelvic floor rehabilitation shows promise, especially among motivated patients, its long-term sustainability remains uncertain. Surgical options are typically reserved for severe cases and carry significant risks and psychological impacts. For patients identified as being at high risk for LARS, treatment options must be considered and discussed at an earlier phase of their care. Our review concludes with the need for a tailored, patient-centered approach to managing LARS, highlighting the importance of ongoing research to fill existing evidence gaps. There is a need for translational research across various treatment modalities, comparing their effects, cost-effectiveness, implementation strategies, and the consequent effects on patients' quality of life and mental health.

Specific symptom change associated with ecological momentary assessments of intrusive trauma memories

As the global prevalence of exposure to traumatic events rises, there is a growing need for accessible and scalable treatments for trauma-related disorders like posttraumatic stress disorder (PTSD). Intrusive reexperiencing symptoms, such as trauma-related intrusive memories (TR-IMs), are central to PTSD and a target of gold-standard treatments that are effective but resource-intensive. This study examined whether completing a brief ecological momentary assessment (EMA) protocol assessing the occurrence and phenomenology of TR-IMs was associated with decreases in intrusion symptom severity. Trauma-exposed adults (N = 139) experiencing at least 2 TR-IMs per week related to a DSM-5 criterion A traumatic event completed a 2-week EMA protocol. During this period, they reported on 18 sensory-perceptual and affective qualities of their TR-IMs three times per day and on posttraumatic stress symptom severity at day’s end. Longitudinal symptom measurements were entered into linear mixed-effects models to test the effect of Time on symptom severity. Over the 2-week protocol, intrusion symptom severity decreased, while other symptom cluster scores did not change. Within the intrusion symptoms, this effect was specific to TR-IMs and emotional reactivity to trauma reminders, and was not moderated by survey completion rate, total PTSD symptom severity, ongoing treatment, or time since trauma. This study was quasi-experimental and lacked a control group, therefore no definitive conclusions about clinical utility can be made. Nonetheless, these findings provide preliminary proof-of-principle and warrant future clinical trials assessing the clinical efficacy of EMAs of intrusive trauma memories as a scalable treatment option targeting intrusive memory symptoms.

Revisiting PD: Unraveling the brain-first and body-first perspectives

Parkinson’s disease (PD) has undergone significant advancements in diagnosis and treatment over the past century, with apparent dopaminergic cell degeneration on dopamine transporter scans and a strong response to medication being key features. However, the etiology remains complex, involving various pathogenic mechanisms beyond alpha-synuclein accumulation. The recent brain-first versus body-first hypothesis, emerging from advances in functional imaging and clinical symptom clustering, suggests distinct starting points of alpha-synuclein pathology-either in the brain or the body, with subsequent spread via neural connections. This theory, exemplified by the alpha-synuclein origin site and connectome (SOC) model, proposes that body-first PD may originate in the enteric nervous system and spread to the brain, while brain-first PD starts within the central nervous system, such as the olfactory bulb or amygdala. While the SOC model offers valuable insights into the progression of PD, it raises several controversies. Critics argue that the model may oversimplify the disease’s complexity, failing to account for overlapping symptoms and the varying progression rates observed in different subtypes. Furthermore, there are concerns about the lack of longitudinal data and the potential for reclassification of PD subtypes over time. Despite these challenges, the ongoing development of imaging techniques that reflect in-vivo pathology holds promise for resolving these controversies and advancing the selection of patients for disease-modifying therapies.

Body Mass Index and Postacute Sequelae of SARS-CoV-2 Infection in Children and Young Adults

Obesity is associated with increased severity of COVID-19. Whether obesity is associated with an increased risk of post-acute sequelae of SARS-CoV-2 infection (PASC) among pediatric populations, independent of its association with acute infection severity, is unclear. To quantify the association of body mass index (BMI) status before SARS-CoV-2 infection with pediatric PASC risk, controlling for acute infection severity. This retrospective cohort study occurred at 26 US children's hospitals from March 2020 to May 2023 with a minimum follow-up of 179 days. Eligible participants included children and young adults aged 5 to 20 years with SARS-CoV-2 infection. Data analysis was conducted from October 2023 to January 2024. BMI status assessed within 18 months before infection; the measure closest to the index date was selected. The BMI categories included healthy weight (≥5th to <85th percentile for those aged 5-19 years or ≥18.5 to <25 for those aged >19 years), overweight (≥85th to <95th percentile for those aged 5-19 years or ≥25 to <30 for for those aged >19 years), obesity (≥95th percentile to <120% of the 95th percentile for for those aged 5-19 years or ≥30 to <40 for those aged >19 years), and severe obesity (≥120% of the 95th percentile for those aged 5-19 years or ≥40 for those aged >19 years). To identify PASC, a diagnostic code specific for post-COVID-19 conditions was used and a second approach used clusters of symptoms and conditions that constitute the PASC phenotype. Relative risk (RR) for the association of BMI with PASC was quantified by Poisson regression models, adjusting for sociodemographic, acute COVID severity, and other clinical factors. A total of 172 136 participants (mean [SD] age at BMI assessment 12.6 [4.4] years; mean [SD] age at cohort entry, 13.1 [4.4] years; 90 187 female [52.4%]) were included. Compared with participants with healthy weight, those with obesity had a 25.4% increased risk of PASC (RR, 1.25; 95% CI, 1.06-1.48) and those with severe obesity had a 42.1% increased risk of PASC (RR, 1.42; 95% CI, 1.25-1.61) when identified using the diagnostic code. Compared with those with healthy weight, there was an increased risk for any occurrences of PASC symptoms and conditions among those with obesity (RR, 1.11; 95% CI, 1.06-1.15) and severe obesity (RR, 1.17; 95% CI, 1.14-1.21), and the association held when assessing total incident occurrences among those with overweight (RR, 1.05; 95% CI, 1.00-1.11), obesity (RR, 1.13; 95% CI, 1.09-1.19), and severe obesity (RR, 1.18; 95% CI, 1.14-1.22). In this cohort study, elevated BMI was associated with a significantly increased PASC risk in a dose-dependent manner, highlighting the need for targeted care to prevent chronic conditions in at-risk children and young adults.

Cluster Analysis of Migraine-associated Symptoms (CAMS) in youth: A retrospective cross-sectional multicenter study.

To conduct a retrospective cross-sectional multicenter study to validate the relationships between migraine-associated symptoms. Symptoms associated with headache-photophobia and phonophobia, nausea, and/or vomiting-are required criteria for migraine diagnosis based on the International Classification of Headache Disorders-Third Edition (ICHD-3). However, individuals with migraine report high rates of other symptoms (e.g., lightheadedness, difficulty thinking). We recently completed a single-center study assessing the relationships between an expanded set of migraine-associated symptoms. A pre-registered cross-sectional multicenter retrospective analysis was conducted on standardized questionnaire data of youth ages 6-17 years from two headache registries at pediatric tertiary care centers. Cluster Analysis of Migraine-associated Symptoms (CAMS) was implemented to assess associations between 11 migraine-associated symptoms. We explored differences between the two centers, and how CAMS was associated with demographics, including sex and age, and headache burden. There were 10,721 participants who were 66.5% female and had a median (interquartile range) age of 13 (10-15) years. The first three CAMS dimensions accounted for 46.5% of the variance and were consistent across sites. The first dimension indicated those reporting any migraine-associated symptoms were likely to report multiple. The second dimension separated symptoms into those included in ICHD-3 migraine diagnostic criteria and non-ICHD symptoms (e.g., lightheadedness, difficulty thinking). The third dimension separated sensory hypersensitivity and vestibular symptoms. An abundance of migraine-associated symptoms correlated with greater headache severity (Spearman's ρ = 0.18, 95% confidence interval [CI] 0.17-0.20; small effect size) and disability (ρ = 0.26, 95% CI 0.25-0.28; small effect size). We also observed differences in associated symptoms across age and sex. Associations between an expanded set of migraine-associated symptoms are informative for headache burden and reveal intriguing changes across child development and sex. We were able to replicate findings across two centers, indicating that these symptom clusters are inherent to migraine.

The interplay among burnout, and symptoms of depression, anxiety, and stress in Chinese clinical therapists

Burnout, depression, anxiety, and stress negatively impact the well-being and retention of healthcare professionals. The interplay of these symptoms is understudied. Utilizing network analysis, this study examined the interrelationships among these symptom clusters in clinical therapists in China. An anonymous survey was conducted among clinical therapists from 41 tertiary psychiatric hospitals in China. Burnout was assessed using the Maslach Burnout Inventory-Human Service Survey (MBI-HSS), while symptoms of depression, anxiety, and stress were assessed via the Depression, Anxiety, and Stress Scale-21 (DASS-21). Analyses were performed to identify central symptoms and bridge symptoms of this network. A total of 419 participants were included in this survey. The prevalence rate for burnout, depression, anxiety, and stress was 19.8%, 22.2%, 17.9%, and 8.6%, respectively. Network analysis indicated that stress symptoms had the highest expected influence values, closely followed by emotional exhaustion from MBI-HSS. Notably, emotional exhaustion emerged as the strongest bridge of expected influence. The stability of the expected influence and bridge expected influence was robust, with coefficients at 0.75. The study’s findings underscore the importance of recognizing the central symptoms and bridge symptoms, which could lead to more effective early detection and intervention for burnout, depression, anxiety, and stress among clinical therapists.

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

Although heart failure (HF) symptoms affect patients' quality of life (QoL), improving patients' QoL requires certain self-care behaviours. However, the specific role of self-care behaviours in the relationship between HF symptoms and QoL has not been clarified. To evaluate the status of symptom clusters, self-care behaviours and QoL in HF patients, and to analyse and test the moderating effect of self-care behaviours between symptom clusters and QoL. This study is a cross-sectional study. A total of 320 HF patients who treated in thethree hospitals in Chengdu, China, from December 2022 to July 2023 were selected as the research subjects. The patients were evaluated using The General Information Questionnaire, Memorial Symptom Assessment Scale Heart Failure, Self-Care of Heart Failure Index and Minnesota Living with Heart Failure Questionnaire. The statistical analysis methods were exploratory factor analysis, Pearson correlation analysis, hierarchical regression analysis and simple slope analysis. There were five symptom clusters in HF patients: emotional symptom cluster (sadness, anxiety, irritability, feeling nervous), digestive symptom cluster (lack of appetite, dry mouth, weight loss, nausea, abdominal distension), ischemic symptom cluster (dizziness, chest pain, palpitations, fatigue), dyspnoea symptom cluster (difficulty breathing when lying flat, waking up breathless at night, sleep difficulty) and congestion symptom cluster (cough, shortness of breath, oedema). There was a significant correlation between HF symptom group, self-care behaviours and QoL (p < 0.05). Both self-care maintenance (β = -0.262, p < 0.001) and self-care management (β = -0.258, p < 0.001) had a moderating effect between symptom clusters and QoL. There are a variety of symptom clusters in HF patients. Improving the self-care behaviours ability of HF patients is conducive to reducing the impact of HF symptom clusters on QoL. The study used the STROBE checklist for reporting. Medical staff should focus on the impact of HF symptom clusters and self-care behaviours on QoL, and formulate corresponding interventions for HF symptom clusters and self-care behaviours to improve the QoL of patients. The head nurse of the cardiovascular department actively assisted us in collecting questionnaires from HF patients, and all HF patients surveyed participated in this study seriously.

Examining the associations between posttraumatic stress disorder symptom clusters across cognitive processing therapy.

Cognitive processing therapy (CPT) is a well-known trauma-focused treatment that aims to generate more adaptive posttrauma cognitions and emotions. Changes in cognitions are theorized to be the mechanism by which CPT leads to improvement in posttraumatic stress disorder (PTSD) symptoms. The present study aimed to explore associations between changes in PTSD symptom clusters during CPT. We hypothesized that early changes in negative alterations in cognitions and mood (NACM) would correlate with later changes in other symptom clusters. Data were collected from 296 veterans participating a 7-week PTSD residential treatment program at a U.S. Veterans Affairs medical center. PTSD symptoms were assessed at pretreatment (Week 1), midtreatment (Week 4), and posttreatment (Week 7). Cross-lagged path analyses demonstrated that pretreatment-to-midtreatment improvement in NACM was correlated with midtreatment-to-posttreatment improvement in avoidance, β =.52, though this association was bidirectional, suggesting pretreatment-to-midtreatment improvements in either cluster may be correlated with midtreatment-to-posttreatment improvements. Similarly, pretreatment-to-midtreatment improvement in intrusions, β =.40, and arousal, β =.49, were correlated with later improvement in avoidance, suggesting avoidance may improve after improvement in other clusters. Interestingly, pretreatment-to-midtreatment arousal improvement was significantly correlated with midtreatment-to-posttreatment NACM improvement, β =.27, though the reverse was nonsignificant, whereas a bidirectional association between arousal and intrusions emerged, β =.34, β =.53. Early changes in arousal were correlated with later changes in several other symptom clusters, whereas other clusters demonstrated bidirectional associations. These results may inform understanding of symptom improvement timing across CPT, which may aid in treatment selection and planning.

Dissociable Default Mode Network Connectivity Patterns Underlie Distinct Symptoms in Psychosis Risk.

The Clinical High Risk (CHR) stage of psychosis is characterized by subthreshold symptoms of schizophrenia including negative symptoms, dysphoric mood, and functional deterioration. Hyperconnectivity of the default-mode network (DMN) has been observed in early schizophrenia, but the extent to which hyperconnectivity is present in CHR, and the extent to which such hyperconnectivity may underlie transdiagnostic symptoms, is not clear. As part of the Shanghai At-Risk for Psychosis (SHARP) program, resting-state fMRI data were collected from 251 young adults (158 CHR and 93 controls, M = 18.72, SD = 4.68, 129 male). We examined functional connectivity of the DMN by performing a whole-brain seed-to-voxel analysis with the MPFC as the seed. Symptom severity across a number of dimensions, including negative symptoms, positive symptoms, and affective symptoms were assessed. Compared to controls, CHRs exhibited significantly greater functional connectivity (p < 0.001 uncorrected) between the MPFC and 1) other DMN nodes including the posterior cingulate cortex (PCC), and 2) auditory cortices (superior and middle temporal gyri, STG/MTG). Furthermore, these two patterns of hyperconnectivity were differentially associated with distinct symptom clusters. Within CHR, MPFC-PCC connectivity was significantly correlated with anxiety (r= 0.23, p=0.006), while MPFC-STG/MTG connectivity was significantly correlated with negative symptom severity (r=0.26, p=0.001). Secondary analyses using item-level symptom scores confirmed a similar dissociation. These results demonstrate that two dissociable patterns of DMN hyperconnectivity found in the CHR stage may underlie distinct dimensions of symptomatology.

Correlation Between Symptom Clusters and Self-Management Among Maintenance Haemodialysis Patients: A Cross-Sectional Study.

The purpose of this study was to explore the relationship between symptom clusters and self-management among maintenance haemodialysis (MHD) patients. MHD patients experience disease progression and multiple symptom burdens that severely impact quality of life, and self-management of symptoms may significantly improve patient-reported outcomes. A cross-sectional study. This cross-sectional descriptive study included 194 patients undergoing MHD. The patients were assessed using the Dialysis Symptom Index (DSI) and the Haemodialysis Self-Management Instrument (HD-SMI). We used descriptive analysis, exploratory factor analysis, Pearson's correlation analysis and linear regression analysis to examine (1) the level of individual self-management, (2) the presence of symptom clusters by symptom severity and (3) the correlation between symptom clusters and self-management behaviours. This study was conducted in accordance with the STROBE checklist. The top five most severe symptoms among the patients were itching, feeling tired or lack of energy, difficulty sleeping, dry mouth and dry skin. We identified five groups of symptoms: (1) poor sleep, (2) neuromuscular, (3) gastrointestinal, (4) skin irritation and (5) psychological. In the present study, MHD patients reported low to moderate levels of self-management behaviours (50.84 ± 10.56), and low self-management ability was correlated with greater severity of the five symptom clusters (p < 0.01). Linear regression analysis revealed that all five symptom clusters were included in the regression equation, explaining 30% of the total variance in self-management skills among MHD patients. Enhanced awareness of symptom clusters and comprehensive symptom management are necessary to improve patients' quality of life. Nursing practices should incorporate comprehensive symptom assessments to help patients develop effective self-management strategies to improve quality of life.

Associations between symptom-based long COVID clusters and long-term quality of life, work and daily activities among individuals testing positive for SARS-CoV-2 at a national retail pharmacy

BackgroundEvidence on long COVID symptom clustering patterns among patients with COVID-19 is limited. We summarized long COVID symptoms in clusters defined by number of symptoms co-occurring together, and we assessed Health-Related Quality of Life (HQRoL), Work Productivity and Activity Impairment (WPAI) outcomes across these clusters over time. We assessed associations between the clusters and BNT162b2 vaccination status.MethodsA prospective longitudinal patient-reported outcomes (PRO) study recruited laboratory-confirmed symptomatic COVID-19 patients seeking testing from a national retail pharmacy. Long COVID-19 symptoms were self-reported by participants at 4-week, 3-month and 6-month surveys. Patient classes identified via latent class analysis (LCA) with long COVID-19 symptoms were simplified into clusters based on number of symptoms. HRQoL and WPAI outcomes were collected using EQ-ED-5L and WPAI: GH questionnaires. Mixed models for repeated measures analyses were conducted to examine associations between exposure groups and outcomes.ResultsThe study included 328 participants that were segmented into three groups of long COVID-19 symptoms based on LCA and then simplified by the number of symptoms (Cluster 1 low, <2; Cluster 2 moderate, 2–6; and Cluster 3 high, >6 symptoms). The number of long COVID-19 symptoms was negatively associated with HRQoL and WPAI, whereby participants with high symptom burden (>6 symptoms) had the lowest HRQoL and WPAI scores assessed by absenteeism, presenteeism, work productivity loss, activity impairment, and hours worked metrics. Compared with those unvaccinated and not up-to-date with COVID-19 vaccination, subjects boosted with BNT162b2 consistently reported less symptom burden during the follow-up, regardless of their symptom-based cluster.ConclusionThree distinct patient clusters based on frequency of long COVID symptoms experienced different HRQoL and WPAI outcomes over 6 months. The cluster with more concomitant symptoms experienced greater burden than the others. Participants up-to-date with BNT162b2 reported lower symptom burden across all clusters and timeframes.Clinical trial registrationClinicaltrials.gov NCT05160636.

Interpersonal symptoms in adolescence depression across Asian and European regions: a network approach

BackgroundMajor Depressive Disorder (MDD) poses a significant global health challenge, with symptom presentation potentially varying between adolescents and adults. Adolescence is a critical period marked by heightened vulnerability to interpersonal stresses, yet the impact of these stresses on the structure of depressive symptoms is not well understood. Recognizing the cultural nuances in how depression manifests among adolescents is crucial. To this end, this paper employs a network analysis approach, utilizing a comprehensive symptom checklist from the Multidimensional Depression Assessment Scale (MDAS). Our study investigates the role of interpersonal symptoms within the broader cluster of emotional, cognitive, and somatic symptoms and explores variations in adolescent groups in four Asian and European regions.MethodsWe recruited a diverse sample of 6,348 adolescents aged 12 to 18 from Hong Kong, Taiwan, the UK, China, and the Netherlands using the Qualtrics platform. Employing the Gaussian Graphical Model, we established a network model of depressive symptoms as measured by the MDAS, segregating the sample into Asian and European regions to examine the interconnections between them. The study focused on identifying central symptom nodes and comparing the network structures between the two groups.ResultsThe analysis identified feeling worthless, low energy, being a burden to others, and low mood as central symptoms of depression. Notably, there were significant differences in the connections between depressive symptoms among Asian (Hong Kong, China and Taiwan) and European (UK and the Netherlands) adolescents, highlighting cultural variations in how interpersonal symptoms interact with emotional, cognitive, and somatic symptoms.ConclusionThis study is pioneering in applying network analysis to include interpersonal symptoms in examining depression among a diverse adolescent population. It demonstrates that interpersonal symptoms are integral to the central features of depressive symptoms. Furthermore, our findings suggest that, compared to their UK and Dutch peers, interpersonal symptoms in Asian adolescents are uniquely connected to other symptom clusters, reflecting distinct cultural patterns. Limitations: The study engaged a broad community sample; however, future research could benefit from including a larger sample size to allow for a more detailed analysis of a greater number of symptom nodes.

Frequency and Longitudinal Course of Behavioral and Neuropsychiatric Symptoms in Participants With Genetic Frontotemporal Dementia.

Behavioral and neuropsychiatric symptoms are frequent in patients with genetic frontotemporal dementia (FTD). We aimed to describe behavioral and neuropsychiatric phenotypes in genetic FTD, quantify their temporal association, and investigate their regional association with brain atrophy. We analyzed data of pathogenic variant carriers in the chromosome 9 open reading frame 72 (c9orf72), progranulin (GRN), or microtubule-associated protein tau (MAPT) gene from the Genetic Frontotemporal dementia Initiative cohort study that enrolls both symptomatic pathogenic variant carriers and first-degree relatives of known carriers. Principal component analysis was performed to identify behavioral and neuropsychiatric clusters that were compared with respect to frequency and severity between groups. Associations between neuropsychiatric clusters and MRI-assessed atrophy were determined using voxel-based morphometry. We applied linear mixed effects and generalized linear mixed effects models to assess the longitudinal course of symptoms. A total of 522 participants were included: 221 c9orf72 (138 presymptomatic), 213 GRN (157 presymptomatic), and 88 MAPT (62 presymptomatic) pathogenic variant carriers. Principal component analysis revealed 5 phenotypic clusters (67.6% of variance), labeled diverse behavioral, affective, psychotic, euphoric/hypersexual, and tactile hallucinations phenotype. In participants presenting behavioral or neuropsychiatric symptoms, affective symptoms were most frequent across groups (83.6%-88.1%), followed by diverse behavioral symptoms (68.4%-77.9%). In c9orf72 and GRN pathogenic variant carriers, psychotic symptoms (32.0% and 19.4%, respectively) were more frequent than euphoric/hypersexual symptoms (28.7% and 14.2%, respectively), which was the other way around in MAPT pathogenic variant carriers (28.6% and 23.8%). Although diverse behavioral symptoms were associated with gray and white matter frontotemporal atrophy, only a small atrophy cluster in the right thalamus was associated with psychotic symptoms. Euphoric/hypersexual symptoms were associated with atrophy in mesial temporal lobes, basal forebrain structures, and the striatum (p < 0.05). Estimated time to symptom onset, genetic group, education, and sex influenced behavioral and neuropsychiatric symptoms (p < 0.05). Particularly, in c9orf72 pathogenic variant carriers, psychotic symptoms may be starting decades before recognition of onset of illness. We identified multiple clusters of behavioral and neuropsychiatric symptoms in participants with genetic FTD that relate to distinct cerebral atrophy patterns. Their severity depends on time, affected gene, sex, and education. These clinical-genetic associations can guide diagnostic evaluations and the design of clinical trials for new disease-modifying and preventive treatments.