Symptom Clusters Research Articles

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.

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.

Initial Symptom Severity and Recovery of Sport-Related Concussion in Team Versus Individual Sport Athletes.

Recovery after sport-related concussion is variable, and potential differences between team vs individual sport athletes are not fully understood. In a cohort of athletes with concussions, we sought to compare these groups across (1) symptom severity score, (2) individual symptom cluster scores, and (3) recovery metrics. A retrospective, cohort study of 13 to 23-year-old athletes treated at a regional sport concussion center between November 2017 and April 2022 was conducted. Athletes were categorized into team vs individual sport athletes, with additional classification of individual sports based on strong vs minimal team elements (ie, the degree of interdependence displayed by athletes). The primary outcomes were symptom severity score, measured by either the Sport Concussion Assessment Tool-5th Edition or the Immediate Post-Concussion Assessment and Cognitive Testing, and physical, cognitive, emotional, and sleep symptom cluster scores. Secondary outcomes were recovery metrics, including time to return-to-learn, symptom resolution, and return-to-play. Of the 1051 athletes, 954 (90.8%) were in team sports and 97 (9.2%) in individual sports. In multivariable linear regression, individual sport athletes had higher emotional symptom severity compared with team sport athletes (β = 0.09 [0.01, 0.17], P = .034) when adjusting for sex, attention-deficit/hyperactivity disorder, psychological disorders, time to clinic, on-field evaluation, and Immediate Post-Concussion Assessment and Cognitive Testing vs Sport Concussion Assessment Tool-5th Edition scale. There were no significant differences in return-to-learn (P = .104), symptom resolution (P = .941), or return-to-play (P = .279) on univariate regressions. In the current single-center, pilot study of athletes with a sport-related concussion, individual sport athletes exhibited more emotional symptoms than team sport athletes. These preliminary data lend early support that individual sport athletes may be more at risk of emotional symptoms than team sport athletes after a sport-related concussion. Clinicians may use these findings to identify athletes who may be particularly vulnerable to emotional symptoms.

Symptom Network and Clusters of the Multidimensional Symptom Experience in Patients With Atrial Fibrillation

Background The symptom network can provide a visual insight into the symptom mechanisms. However, few study authors have explored the multidimensional symptom network of patients with atrial fibrillation (AF). Objectives We aimed to identify the core symptom and symptom clusters of patients with AF by generating a symptom network. Furthermore, we wanted to identify multiple characteristics related to symptom clusters. Methods This is a cross-sectional study. A total of 384 patients with AF at Tianjin Medical University General Hospital were enrolled. The University of Toronto Atrial Fibrillation Severity Scale was used to assess AF symptoms. Network analysis was used to explore the core symptom and symptom cluster. Results Shortness of breath at rest (r s = 1.189, r c = 0.024), exercise intolerance (r s = 1.116), shortness of breath during physical activity (r s = 1.055, r c = 0.022), and fatigue at rest (r c = 0.020) have the top centrality for strength and closeness. The top 3 symptoms of bridge strength were shortness of breath at rest (r s = 0.264), dizziness (r s = 0.208), and palpitations (r s = 0.207). Atrial fibrillation symptoms could be clustered into the breathless cluster and the cardiac cluster. We have identified multiple factors such as mental health status, left ventricular ejection fraction, heart failure, sex, B-type natriuretic peptide, and chronic obstructive pulmonary disease as significant contributors within the breathless cluster, whereas sex, mental health status, and history of radiofrequency ablation were strongly associated with the cardiac cluster, holding promise in elucidating the underlying mechanisms of these symptoms. Conclusion Special attention should be given to shortness of breath at rest as its core and bridging role in patients' symptoms. Furthermore, both the breathless and cardiac clusters are common among patients. Network analysis reveals direct connections between symptoms, symptom clusters, and their influencing factors, providing a foundation for clinicians to effectively manage patients' symptoms.

Exploring the Interactions Between Psychotic Symptoms, Cognition, and Environmental Risk Factors: A Bayesian Analysis of Networks.

Psychotic disorders (PDs) have huge personal and societal impact, and efforts to improve outcomes in patients are continuously needed. Environmental risk factors (ERFs), especially modifiable risk factors, are important to study because they pose a target for intervention and prevention. No studies have investigated ERFs, cognition, and psychotic symptoms together in a network approach. We explored interactions between 3 important ERFs (tobacco smoking, cannabis use, and childhood trauma), 6 cognitive domains, and 3 dimensions of symptoms in psychosis. From the Genetic Risk and Outcome of Psychosis (GROUP) cohort, we used data from patients, siblings, and healthy controls to construct networks using Bayesian analyses of all 12 variables. We constructed networks of the combined sample and of patients and siblings separately. We found that tobacco smoking was directly associated with cognition and psychotic symptoms. The cognitive variable processing speed was the most central node, connecting clusters of psychotic symptoms and substance use through the variables of positive symptoms and tobacco smoking. Comparing the networks of patients and siblings, we found that networks were relatively similar between patients and siblings. Our results support a potential central role of processing speed deficits in PDs. Findings highlight the importance of integrating tobacco smoking as potential ERFs in the context of PDs and to broaden the perspective from cannabis discontinuation to smoking cessation programs in patients or people at risk of PDs.

Developing a Sitting Simple Baduanjin program for advanced cancer patients with the fatigue-sleep disturbance symptom cluster: A feasibility study.

We describe a development and feasibility study of a Sitting Simple Baduanjin program for advanced cancer patients suffering from the fatigue-sleep disturbance symptom cluster. This study was to evaluate the practicality and safety of the Sitting Simple Baduanjin intervention and determine its preliminary efficacy. This work employed a single-arm mixed-methods approach. The primary outcome measures were feasibility (i.e., recruitment, adherence, and satisfaction) and safety. Validated self-report questionnaires were used to evaluate the preliminary effects of the program, including fatigue, sleep quality, and quality of life at the 4th, 8th, and 12th weeks of the intervention. Qualitative interviews were also conducted after the program. A total of 30 participants were enrolled, of which 23 (77%) completed the 12-week Sitting Simple Baduanjin program. The mean adherence rate was 88% and no adverse events were reported. Statistically significant improvements were observed in terms of fatigue, sleep quality, and quality of life after program completion. Four themes emerged from the qualitative interview data: (a) acceptability of the Sitting Simple Baduanjin technique, (b) perceived benefits of exercise, (c) barriers, and (d) facilitators. The findings support the feasibility of the Sitting Simple Baduanjin program for advanced cancer patients and show promise in improving patients' levels of the fatigue-sleep disturbance symptom cluster and quality of life.

Symptom Clusters in Breast Cancer Patients Receiving Adjuvant Chemotherapy: A Systematic Review.

Breast cancer patients experience various adverse symptoms during adjuvant chemotherapy. These adverse symptoms often form symptom clusters and have a negative impact on patients. To summarise common symptom clusters in different dimensions and their longitudinal changes among breast cancer patients receiving adjuvant chemotherapy. A systematic review. Ten electronic databases were searched from 2001 to January 2024, and the search was last updated on 16 August 2024. Two reviewers independently assessed the eligibility of each study and extracted data. The Standard Quality Assessment Criteria for Evaluating Primary Research Papers was used to evaluate the quality of included studies. The findings were synthesised narratively. This systematic review has been registered (CRD42022370210). Nine studies with a total of 1454 participants were included. The common symptom clusters in breast cancer patients receiving adjuvant chemotherapy were the gastrointestinal symptom cluster (nausea-lack of appetite), the fatigue-pain-sleep disturbance symptom cluster and the psychological symptom cluster (worry-sadness-nervousness-distress-feeling irritable-difficult concentrating). The severity dimension was the most frequently utilised in identifying symptom clusters, with the number and concurrence of symptom clusters showing variation over time. This study summarised common symptom clusters in breast cancer patients receiving adjuvant chemotherapy and revealed their changes from symptom dimensions and the chemotherapy process. These findings support further exploration of symptom cluster changes and underlying mechanisms, facilitating the design of targeted management strategies, including appropriate interventions and measurement dimensions in clinical nursing, to ultimately reduce patients' symptom burden. Common symptom clusters have been identified in breast cancer patients receiving adjuvant chemotherapy. Clinical nursing in oncology can prioritise these symptom clusters and provide patients with targeted management strategies. PRISMA guidelines and SWiM guidelines. No patient or public contribution.

Depression symptoms are associated with demographic characteristics, nutritional status, and social support among young adults in Chile: a latent class analysis

BackgroundDepressive disorders are a critical public health concern in Chile. Nonetheless, there is a lack of evidence regarding the identification of depressive symptom clusters. The objective was to identify depressive symptom clusters among Chilean young adults and examine how demographic, and lifestyle factors as well as social support can influence and predict them.MethodsCross-sectional study conducted among 1,000 participants from the Limache cohort 2. A latent class analysis (LCA) was performed to identify depressive symptom clusters, using the Patient Health Questionnaire (PHQ-9). Multinomial logistic regression was then applied to explore the associations between identified classes and potential predictors. The models were adjusted by age and sex.ResultsThree latent classes of depressive symptoms were identified: minimal (25.7%); somatic (50.7%) and severe (23.6%). In the severe class for eight out nine depressive symptoms the probabilities were above 50%, and the probability of suicidal ideation was almost a third in this class. Being female (Adjusted Odds ratio [AOR], 2.49; 95% confidence interval [CI] [1.63–3.81]), current smoker (AOR, 1.74; 95% CI [1.15–2.65]), having basic education (AOR, 3.12; 95% CI [1.30–7.53]) and obesity (AOR, 2.72; 95% CI [1.61–4.59]) significantly increased the likelihood of belonging to severe class. Higher social support decreased the odds of being in the somatic (OR, 0.96; 95% CI [0.93–0.98]) and severe (OR, 0.92; 95% CI [0.90–0.94]) classes.ConclusionsThese findings highlight the importance of individualized intervention strategies for depression management. Also, the study suggests that nutritional status and social support should be considered when addressing depression in this population.

Refining Research Diagnostic Criteria for Catatonia Among Delirium, Medical, Affective, and Psychosis Patient Groups.

The authors proposed catatonia diagnostic criteria that require the presence of three neuropsychiatric symptom clusters, rated over 24 hours; this system differs from other symptom clustering proposals and is intended to increase diagnostic rigor over Bush-Francis Catatonia Rating Scale (BFCRS) or DSM-5 criteria. By applying new BFCRS item score thresholds, symptoms were clustered into three categories to comprise the Research Diagnostic Criteria for Catatonia (RDCC): akinesia (criterion A), unusual motor signs (criterion B), and behavioral signs (criterion C). RDCC symptom clusters were analyzed in four prospectively evaluated patient groups (delirium, medical, affective, and psychosis) (N=341). Use of the RDCC, compared with the DSM-5-TR and BFCRS, resulted in far fewer diagnoses of catatonia in the four patient groups: medical, N=1 out of 42 (2%); affective, N=1 out of 45 (2%); psychosis, N=3 out of 53 (6%); and delirium, N=0 out of 201. Permutations of the RDCC with more relaxed criteria were assessed, requiring either symptom thresholds or numbers of symptoms to meet criteria, resulting in catatonia rate gradations between those obtained with the RDCC and those obtained with current systems. The Cochrane Q test found that the DSM-5-TR was not dissimilar to the RDCC, if fulfilling numerical thresholds for criteria A-C, although any level of symptom severity was allowed. Confirmatory factor analysis with three goodness-of-fit indexes validated the RDCC. The RDCC requires akinetic symptoms on the basis of literature demonstrating their high BFCRS prevalence and exploratory factor analysis co-loadings, plus symptoms from unusual motor and behavioral signs. Compared with current lenient diagnostic approaches, having the symptoms required by the RDCC produced lower catatonia rates in the psychosis, affective, and medical groups and revealed no patients with catatonia in the delirium group. Subdividing DSM-5-TR symptoms into several different criteria may improve diagnosis. RDCC symptom clusters are both research data-based and amenable to further research for validation.

Unveiling Post-COVID-19 syndrome: incidence, biomarkers, and clinical phenotypes in a Thai population

BackgroundPost-COVID- 19 syndrome (PCS) significantly impacts the quality of life of survivors. There is, however, a lack of a standardized approach to PCS diagnosis and management. Our bidirectional cohort study aimed to estimate PCS incidence, identify risk factors and biomarkers, and classify clinical phenotypes for enhanced management to improve patient outcomes.MethodsA bidirectional prospective cohort study was conducted at five medical sites in Hatyai district in Songkhla Province, Thailand. Participants were randomly selected from among the survivors of COVID-19 aged≥18 years between May 15, 2022, and January 31, 2023. The selected participants underwent a scheduled outpatient visit for symptom and health assessments 12 to 16 weeks after the acute onset of infection, during which PCS was diagnosed and blood samples were collected for hematological, inflammatory, and serological tests. PCS was defined according to the World Health Organization criteria. Univariate and multiple logistic regression analyses were used to identify biomarkers associated with PCS. Moreover, three clustering methods (agglomerative hierarchical, divisive hierarchical, and K-means clustering) were applied, and internal validation metrics were used to determine clustering and similarities in phenotypes.FindingsA total of 300 survivors were enrolled in the study, 47% of whom developed PCS according to the World Health Organization (WHO) definition. In the sampled cohort, 66.3% were females, and 79.4% of them developed PCS (as compared to 54.7% of males, p-value <0.001). Comorbidities were present in 19% (57/300) of all patients, with 11% (18/159) in the group without PCS and 27.7% (39/141) in the group with PCS. The incidence of PCS varied depending on the criteria used and reached 13% when a quality of life indicator was added to the WHO definition. Common PCS symptoms were hair loss (22%) and fatigue (21%), while mental health symptoms were less frequent (insomnia 3%, depression 3%, anxiety 2%). According to our univariate analysis, we found significantly lower hematocrit and IgG levels and greater ALP levels in PCS patients than in patients who did not develop PCS (p-value< 0.05). According to our multivariable analysis, adjusted ALP levels remained a significant predictor of PCS (OR 1.02, p-value= 0.005). Clustering analysis revealed four groups characterized by severe clinical symptoms and mental health concerns (Cluster 1, 4%), moderate physical symptoms with predominant mental health issues (Cluster 2, 9%), moderate mental health issues with predominant physical symptoms (Cluster 3, 14%), and mild to no PCS (Cluster 4, 77%). The quality of life and ALP levels varied across the clusters.InterpretationThis study challenges the prevailing diagnostic criteria for PCS, emphasizing the need for a holistic approach that considers quality of life. The identification of ALP as a biomarker associated with PCS suggests that its monitoring could be used for early detection of the onset of PCS. Cluster analysis revealed four distinct clinical phenotypes characterized by different clinical symptoms and mental health concerns that 'exhibited varying impacts on quality of life. This finding suggested that accounting for the reduced quality of life in the definition of PCS could enhance its diagnosis and management and that moving toward personalized interventions could both improve patient outcomes and help reduce medicalization and optimally target the available resources.FundingThe research publication received funding support from Medical Council of Thailand (Police General Dr. Jongjate Aojanepong Foundation), Hatyai Hospital Charity and Wellcome Trust.

Symptom clusters and symptom network analysis during immunotherapy in lung cancer patients.

This study analyzes symptoms in lung cancer patients undergoing immunotherapy to identify core symptom clusters through network analysis and lay a foundation for effective symptom management programs. The sample comprised 240 lung cancer patients receiving immunotherapy. Participants were assessed using the Memorial Symptom Assessment Scale. Exploratory factor analysis was used to extract symptom clusters, and network analysis using JASP 0.17.3 was performed to explore the centrality indices and density of the symptom network. Five symptom clusters were identified, i.e., emotion-related, lung cancer-related, physical, skin, and neural symptom clusters, with a cumulative variance contribution rate of 55.819%. Network analysis revealed that sadness was the most intense symptom (rs = 2.189), dizziness was the most central symptom (rc = 1.388), and fatigue was the most significant bridging symptom (rb = 2.575). This study identified five symptom clusters and a symptom network among lung cancer patients during immunotherapy. The network analysis's centrality indices and network density results can assist healthcare professionals in devising more precise symptom management strategies.

Phenotyping Men With Lower Urinary Tract Symptoms: Results From the Symptoms of Lower Urinary Tract Dysfunction Research Network.

Men with lower urinary tract symptoms (LUTS) represent a heterogeneous group, and treatment decisions are often based on severity of symptoms and physical examination findings. Identification of clinically meaningful subtypes could allow for more personalized care. This study advances phenotyping efforts from the Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN) by adding data domains to previous phenotyping using urologic symptoms alone. Two-hundred-seventeen LUTS, demographics, medical history, and physical examination datapoints from the LURN Observational Cohort study were assessed among 519 men with at least one bothersome LUTS, using weighted Tanimoto indices, semi-supervised learning, and resampling-based consensus clustering to identify distinct clusters of participants. Differentially abundant serum proteins of 220 men were compared across identified clusters. Five refined male clusters (RM1-RM5) were identified. Two clusters reported mild LUTS (RM1: n = 66; RM2: n = 84). RM1 was older than RM2 (70.3 vs. 56.1 years), had more comorbidities (functional comorbidity index 2.4 vs. 1.5) and erectile dysfunction. Two benign prostatic hyperplasia-like symptom clusters were identified (RM3: n = 64; RM4: n = 188). RM3 has the largest postvoid residual volume (275 mL); RM4 reported more urinary frequency, urgency, urinary incontinence, pain, and psychosocial symptoms. RM5 (n = 119) was characterized by urgency urinary incontinence, frequency, and significant comorbidities and psychosocial symptoms. Fifteen (RM2) to 87 (RM1) differentially abundant proteins were identified within each cluster. Minimal overlap was observed between affected proteins and pathways across clusters. Protein signatures across newly discovered subgroups suggest identified subtypes are biochemically distinct. Findings should be validated, but may represent populations with separate pathophysiology and therapeutic needs. The LURN ClinicalTrials.gov Identifier is NCT02485808.

Study protocol TransTAM: Transdiagnostic research into emotional disorders and cognitive-behavioral therapy of the adaptive mind

BackgroundEmotional disorders such as depression and anxiety disorders share substantial similarities in their etiology and treatment. In recent decades, these commonalities have been increasingly recognized in classification systems and treatment programs crossing diagnostic boundaries.MethodsTo examine the prospective effects of different transdiagnostic markers on relevant treatment outcomes, we plan to track a minimum of N = 200 patients with emotional disorders during their routine course of cognitive behavioral therapy at two German outpatient clinics. We will collect a wide range of transdiagnostic markers, ranging from basic perceptual processes and self-report measures to complex behavioral and neurobiological indicators, before entering therapy. Symptoms and psychopathological processes will be recorded before entering therapy, between the 20th and 24th therapy session, and at the end of therapy.DiscussionOur results could help to identify transdiagnostic markers with high predictive power, but also provide deeper insights into which patient groups with which symptom clusters are less likely to benefit from therapy, and for what reasons.Trial RegistrationThe trial was preregistered at the German Clinical Trial Register (DRKS-ID: DRKS00031206; 2023–05-09).

A pilot cross-sectional investigation of symptom clusters and associations with patient-reported outcomes in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and Post COVID-19 Condition.

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is associated with long-term disability and poor quality of life (QoL). Cardinal ME/CFS symptoms (including post-exertional malaise, cognitive dysfunction and sleep disturbances) have been observed in Post COVID-19 Condition (PCC). To gain further insight into the potential role of ME/CFS as a post-COVID-19 sequela, this study investigates associations between symptoms and patient-reported outcomes, as well as symptom clusters. Participants included Australian residents aged between 18 and 65 years formally diagnosed with ME/CFS fulfilling the Canadian or International Consensus Criteria or PCC meeting the World Health Organization case definition. Validated, self-administered questionnaires collected participants' sociodemographic and illness characteristics, symptoms, QoL and functional capacity. Associations between symptoms and patient-reported outcomes were investigated with multivariate linear regression models. Hierarchical cluster analysis was performed to identify symptom clusters. Most people with ME/CFS (pwME/CFS) and people with PCC (pwPCC) were female (n = 48/60, 80.0% and n = 19/30, 63.3%, respectively; p = 0.12). PwME/CFS were significantly younger (x̄=41.75, s = 12.91 years) than pwPCC (x̄=48.13, s =10.05 years; p =0.017). Autonomic symptoms (notably dyspnoea) were associated with poorer scores in most patient-reported outcome domains for both cohorts. None of the four symptom clusters identified were unique to ME/CFS or PCC. Clusters were largely delineated by the presence of gastrointestinal and neurosensory symptoms, illness duration, ME/CFS criteria met and total symptoms. Illness duration may explain differences in symptom burden between pwME/CFS and pwPCC. PCC diagnostic criteria must be refined to distinguish pwPCC at risk of long-term ME/CFS-like illness and subsequently deliver necessary care and support.