957 resultados para Symptom Clusters


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Examined whether discrete working memory deficits underlie positive, negative and disorganised symptoms of schizophrenia. 52 outpatients (mean age 37.5 yrs) with schizophrenia were studied using items drawn from the Positive and Negative Syndrome Scale (PANSS). Linear regression and correlational analyses were conducted to examine whether symptom dimension scores were related to performance on several tests of working memory function. Severity of negative symptoms correlated with reduced production of words during a verbal fluency task, impaired ability to hold letter and number sequences on-line and manipulate them simultaneously, reduced performance during a dual task, and compromised visuospatial working memory under distraction-free conditions. Severity of disorganisation symptoms correlated with impaired visuospatial working memory under conditions of distraction, failure of inhibition during a verbal fluency task, perseverative responding on a test of set-shifting ability, and impaired ability to judge the veracity of simple declarative statements. The present study provides evidence that the positive, negative and disorganised symptom dimensions of the PANSS constitute independent clusters, associated with unique patterns of working memory impairment.

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Multivariate methods are required to assess the interrelationships among multiple, concurrent symptoms. We examined the conceptual and contextual appropriateness of commonly used multivariate methods for cancer symptom cluster identification. From 178 publications identified in an online database search of Medline, CINAHL, and PsycINFO, limited to articles published in English, 10 years prior to March 2007, 13 cross-sectional studies met the inclusion criteria. Conceptually, common factor analysis (FA) and hierarchical cluster analysis (HCA) are appropriate for symptom cluster identification, not principal component analysis. As a basis for new directions in symptom management, FA methods are more appropriate than HCA. Principal axis factoring or maximum likelihood factoring, the scree plot, oblique rotation, and clinical interpretation are recommended approaches to symptom cluster identification.

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Advances in symptom management strategies through a better understanding of cancer symptom clusters depend on the identification of symptom clusters that are valid and reliable. The purpose of this exploratory research was to investigate alternative analytical approaches to identify symptom clusters for patients with cancer, using readily accessible statistical methods, and to justify which methods of identification may be appropriate for this context. Three studies were undertaken: (1) a systematic review of the literature, to identify analytical methods commonly used for symptom cluster identification for cancer patients; (2) a secondary data analysis to identify symptom clusters and compare alternative methods, as a guide to best practice approaches in cross-sectional studies; and (3) a secondary data analysis to investigate the stability of symptom clusters over time. The systematic literature review identified, in 10 years prior to March 2007, 13 cross-sectional studies implementing multivariate methods to identify cancer related symptom clusters. The methods commonly used to group symptoms were exploratory factor analysis, hierarchical cluster analysis and principal components analysis. Common factor analysis methods were recommended as the best practice cross-sectional methods for cancer symptom cluster identification. A comparison of alternative common factor analysis methods was conducted, in a secondary analysis of a sample of 219 ambulatory cancer patients with mixed diagnoses, assessed within one month of commencing chemotherapy treatment. Principal axis factoring, unweighted least squares and image factor analysis identified five consistent symptom clusters, based on patient self-reported distress ratings of 42 physical symptoms. Extraction of an additional cluster was necessary when using alpha factor analysis to determine clinically relevant symptom clusters. The recommended approaches for symptom cluster identification using nonmultivariate normal data were: principal axis factoring or unweighted least squares for factor extraction, followed by oblique rotation; and use of the scree plot and Minimum Average Partial procedure to determine the number of factors. In contrast to other studies which typically interpret pattern coefficients alone, in these studies symptom clusters were determined on the basis of structure coefficients. This approach was adopted for the stability of the results as structure coefficients are correlations between factors and symptoms unaffected by the correlations between factors. Symptoms could be associated with multiple clusters as a foundation for investigating potential interventions. The stability of these five symptom clusters was investigated in separate common factor analyses, 6 and 12 months after chemotherapy commenced. Five qualitatively consistent symptom clusters were identified over time (Musculoskeletal-discomforts/lethargy, Oral-discomforts, Gastrointestinaldiscomforts, Vasomotor-symptoms, Gastrointestinal-toxicities), but at 12 months two additional clusters were determined (Lethargy and Gastrointestinal/digestive symptoms). Future studies should include physical, psychological, and cognitive symptoms. Further investigation of the identified symptom clusters is required for validation, to examine causality, and potentially to suggest interventions for symptom management. Future studies should use longitudinal analyses to investigate change in symptom clusters, the influence of patient related factors, and the impact on outcomes (e.g., daily functioning) over time.

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Goals of work: The aim of this secondary data analysis was to investigate symptom clusters over time for symptom management of a patient group after commencing adjuvant chemotherapy. Materials and methods: A prospective longitudinal study of 219 cancer outpatients conducted within 1 month of commencing chemotherapy (T1), 6 months (T2), and 12 months (T3) later. Patients' distress levels were assessed for 42 physical symptoms on a clinician-modified Rotterdam Symptom Checklist. Symptom clusters were identified in exploratory factor analyses at each time. Symptom inclusion in clusters was determined from structure coefficients. Symptoms could be associated with multiple clusters. Stability over time was determined from symptom cluster composition and the proportion of symptoms in the initial symptom clusters replicated at later times. Main results Fatigue and daytime sleepiness were the most prevalent distressing symptoms over time. The median number of concurrent distressing symptoms approximated 7, over time. Five consistent clusters were identified at T1, 2, and T3. An additional two clusters were identified at 12 months, possibly due to less variation in distress levels. Weakness and fatigue were each associated with two, four, and five symptom clusters at T1, T2, and T3, respectively, potentially suggesting different causal mechanisms. Conclusion: Stability is a necessary attribute of symptom clusters, but definitional clarification is required. We propose that a core set of concurrent symptoms identifies each symptom cluster, signifying a common cause. Additional related symptoms may be included over time. Further longitudinal investigation is required to identify symptom clusters and the underlying causes.

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Context Patients with venous leg ulcers experience multiple symptoms, including pain, depression, and discomfort from lower leg inflammation and wound exudate. Some of these symptoms impair wound healing and decrease quality of life (QOL). The presence of co-occurring symptoms may have a negative effect on these outcomes. The identification of symptom clusters could potentially lead to improvements in symptom management and QOL. Objectives To identify the prevalence and severity of common symptoms and the occurrence of symptom clusters in patients with venous leg ulcers. Methods For this secondary analysis, data on sociodemographic characteristics, medical history, venous history, ulcer and lower limb clinical characteristics, symptoms, treatments, healing, and QOL were analyzed from a sample of 318 patients with venous leg ulcers who were recruited from hospital outpatient and community nursing clinics for leg ulcers. Exploratory factor analysis was used to identify symptom clusters. Results Almost two-thirds (64%) of the patients experienced four or more concurrent symptoms. The most frequent symptoms were sleep disturbance (80%), pain (74%), and lower limb swelling (67%). Sixty percent of patients reported three or more symptoms at a moderate-to-severe level of intensity (e.g., 78% reported disturbed sleep frequently or always; the mean pain severity score was 49 of 100, SD 26.5). Exploratory factor analysis identified two symptom clusters: pain, depression, sleep disturbance, and fatigue; and swelling, inflammation, exudate, and fatigue. Conclusion Two symptom clusters were identified in this sample of patients with venous leg ulcers. Further research is needed to verify these symptom clusters and to evaluate their effect on patient outcomes.

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Context Older oncology patients have unique needs associated with the many physical, psychological,and social changes associated with the aging process. The mechanisms underpinning and the impact of these changes are not well understood. Identification of clusters of symptoms is one approach that has been used to elicit hypotheses about the biological and/or psychological basis for variations in symptom experiences. Objectives The purposes of this study were to identify and compare symptom clusters in younger (<60 years) and older ($60 years) patients undergoing cancer treatment. Methods. Symptom data from one Australian study and two U.S. studies were combined to conduct this analysis. A total of 593 patients receiving active treatment were dichotomized into younger (<60 years) and older ($60 years) groups. Separate exploratory factor analyses (EFAs) were undertaken within each group to identify symptom clusters from occurrence ratings of the 32 symptoms assessed by the Memorial Symptom Assessment Scale. Results In both groups, a seven-factor solution was selected. Four partially concordant symptom clusters emerged in both groups (i.e., mood/cognitive, malaise, body image, and genitourinary). In the older patients, the three unique clusters reflected physiological changes associated with aging, whereas in the younger group the three unique clusters reflected treatment-related effects. Conclusion The symptom clusters identified in older patients typically included a larger and more diverse range of physical and psychological symptoms. Differences also may be reflective of variations in treatment approaches between age groups. Findings highlight the need for better understanding of variation in treatment and symptom burden between younger and older adults with cancer.

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The objective of this study was to identify symptom clusters and their effect on quality of life (QOL) of adults with chronic leg ulcers of mixed venous and arterial aetiology. A secondary analysis of data from four existing prospective longitudinal studies conducted by a wound healing research group in Australia was undertaken. A total of 110 patients who met the inclusion criteria were selected for this study. Exploratory factor analysis (EFA) was used to identify symptom clusters and correlational analyses to examine relationships between the identified symptom clusters and QOL. The EFA identified two distinct symptom clusters: a 'systemic symptom cluster' consisting of pain, fatigue and depressive symptoms; and a 'localised-leg symptom cluster' including pain, fatigue, oedema, lower limb inflammation and exudate. Physical QOL correlated significantly with the systemic symptom cluster (r = -0·055, P < 0·0001) and the localised-leg symptom cluster (r = -0·054, P < 0·0001), whereas mental QOL was associated only with the systemic symptom cluster (r = -0·038, P = 0·01). The results suggest that appropriate intervention strategies targeting specific symptom clusters should be developed. Targeting patients with symptom clusters is particularly important because they are at high risk and the most vulnerable for reduced QOL.

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This study aimed to identify clusters of symptoms, to determine the patient characteristics associated with identified, and determine their strength of association with survival in patients with advanced cancer (ACPs). Consecutively eligible ACPs not receiving cancer-specific treatment, and referred to a Tertiary Palliative Care Clinic, were enrolled in a prospective cohort study. At first consultation, patients rated 9 symptoms through the Edmonton Symptom Assessment System (0-10 scale) and 10 others using a Likert scale (1-5). Principal component analysis was used in an exploratory factor analysis to identify. Of 318 ACPs, 301 met eligibility criteria with a median (range) age of 69 (37-94) years. Three SCs were identified: neuro-psycho-metabolic (NPM) (tiredness, lack of appetite, lack of well-being, dyspnea, depression, and anxiety); gastrointestinal (nausea, vomiting, constipation, hiccups, and dry mouth) and sleep impairment (insomnia and sleep disturbance). Exploratory factor analysis accounted for 40% of variance of observed variables in all SCs. Shorter survival was observed for patients with the NPM cluster (58 vs. 23, P < 0.001), as well as for patients with two or more SCs (45 vs. 21, P = 0.005). In a multivariable model for survival at 30-days, age (HR: 0.98; 95% CI: 0.97-0.99; P = 0.008), hospitalization at inclusion (HR: 2.27; 95% CI: 1.47-3.51; P < 0.001), poorer performance status (HR: 1.90, 95% CI: 1.24-2.89; P = 0.003), and NPM (HR: 1.64; 95% CI: 1.17-2.31; P = 0.005), were associated with worse survival. Three clinically meaningful SC in patients with advanced cancer were identifiable. The NPM cluster and the presence of two or more SCs, had prognostic value in relation to survival.

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Context Cancer patients experience a broad range of physical and psychological symptoms as a result of their disease and its treatment. On average, these patients report ten unrelieved and co-occurring symptoms. Objectives To determine if subgroups of oncology outpatients receiving active treatment (n=582) could be identified based on their distinct experience with thirteen commonly occurring symptoms; to determine whether these subgroups differed on select demographic, and clinical characteristics; and to determine if these subgroups differed on quality of life (QOL) outcomes. Methods Demographic, clinical, and symptom data from one Australian and two U.S. studies were combined. Latent class analysis (LCA) was used to identify patient subgroups with distinct symptom experiences based on self-report data on symptom occurrence using the Memorial Symptom Assessment Scale (MSAS). Results Four distinct latent classes were identified (i.e., All Low (28.0%), Moderate Physical and Lower Psych (26.3%), Moderate Physical and Higher Psych (25.4%), All High (20.3%)). Age, gender, education, cancer diagnosis, and presence of metastatic disease differentiated among the latent classes. Patients in the All High class had the worst QOL scores. Conclusion Findings from this study confirm the large amount of interindividual variability in the symptom experience of oncology patients. The identification of demographic and clinical characteristics that place patients are risk for a higher symptom burden can be used to guide more aggressive and individualized symptom management interventions.

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There is growing evidence for the development of posttraumatic stress symptoms as a consequence of acute cardiac events. Acute coronary syndrome (ACS) patients experience a range of acute cardiac symptoms, and these may cluster together in specific patterns. The objectives of this study were to establish distinct symptom clusters in ACS patients, and to investigate whether the experience of different types of symptom clusters are associated with posttraumatic symptom intensity at six months. ACS patients were interviewed in hospital within 48 h of admission, 294 patients provided information on symptoms before hospitalisation, and cluster analysis was used to identify patterns. Posttraumatic stress symptoms were assessed in 156 patients at six months. Three symptom clusters were identified; pain symptoms, diffuse symptoms and symptoms of dyspnea. In multiple regression analyses, adjusting for sociodemographic, clinical and psychological factors, the pain symptoms cluster (β = .153, P = .044) emerged as a significant predictor of posttraumatic symptom severity at six months. A marginally significant association was observed between symptoms of dyspnea and reduced intrusive symptoms at six months (β = -.156, P = .061). Findings suggest acute ACS symptoms occur in distinct clusters, which may have distinctive effects on intensity of subsequent posttraumatic symptoms. Since posttraumatic stress is associated with adverse outcomes, identifying patients at risk based on their symptom experience during ACS may be useful in targeting interventions.

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Quality of life has been shown to be poor among people living with chronic hepatitis C However, it is not clear how this relates to the presence of symptoms and their severity. The aim of this study was to describe the typology of a broad array of symptoms that were attributed to hepatitis C virus (HCV) infection. Phase I used qualitative methods to identify symptoms. In Phase 2, 188 treatment-naive people living with HCV participated in a quantitative survey. The most prevalent symptom was physical tiredness (86%) followed by irritability (75%), depression (70%), mental tiredness (70%), and abdominal pain (68%). Temporal clustering of symptoms was reported in 62% of participants. Principal components analysis identified four symptom clusters: neuropsychiatric (mental tiredness, poor concentration, forgetfulness, depression, irritability, physical tiredness, and sleep problems); gastrointestinal (day sweats, nausea, food intolerance, night sweats, abdominal pain, poor appetite, and diarrhea); algesic (joint pain, muscle pain, and general body pain); and dysesthetic (noise sensitivity, light sensitivity, skin. problems, and headaches). These data demonstrate that symptoms are prevalent in treatment-naive people with HCV and support the hypothesis that symptom clustering occurs.

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Purpose of review: The study provides a review of current evidence about the role of complex nonpharmacological strategies in managing the multidimensional components of the breathlessness experience for individuals with life-limiting conditions. Recent findings: Evidence continues to demonstrate the significant impact of breathlessness on patients’ quality of life, day-to-day activity, and physical and psychosocial functioning. Recent evidence also confirms that patients draw on a number of self-initiated actions to cope with breathlessness, although many do not use strategies that are supported by a growing body of evidence from randomized controlled trials. Current literature supports the use of multicomponent, nonpharmacological interventions comprising strategies to improve breathing efficiency and reducing psychological distress to manage breathlessness. However trials of these approaches have mostly been conducted among patients with chronic obstructive pulmonary disease (COPD) or lung cancer, and few studies have investigated the benefits of nonpharmacological for patients in later stages of disease. Further investigation of interventions is required across a broader range of chronic life-limiting conditions. Addressing breathlessness and its co-occurring symptoms (symptom clusters) is also an area for future enquiry. Summary: The experience of breathlessness and strategies adopted by patients to manage the experience highlight the importance of multidimensional approaches to improve outcomes for patients with life-limiting conditions. There is good evidence to support the role of multicomponent, nonpharmacological interventions in reducing breathlessness for patients with COPD and lung cancer, although further studies are required to understand the particular clinical contexts in which such interventions are appropriate.

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Impulsivity and hyperactivity share common ground with numerous mental disorders, including schizophrenia. Recently, a population-specific serotonin 2B (5-HT2B) receptor stop codon (ie, HTR2B Q20*) was reported to segregate with severely impulsive individuals, whereas 5-HT2B mutant (Htr2B−/−) mice also showed high impulsivity. Interestingly, in the same cohort, early-onset schizophrenia was more prevalent in HTR2B Q*20 carriers. However, the putative role of 5-HT2B receptor in the neurobiology of schizophrenia has never been investigated. We assessed the effects of the genetic and the pharmacological ablation of 5-HT2B receptors in mice subjected to a comprehensive series of behavioral test screenings for schizophrenic-like symptoms and investigated relevant dopaminergic and glutamatergic neurochemical alterations in the cortex and the striatum. Domains related to the positive, negative, and cognitive symptom clusters of schizophrenia were affected in Htr2B−/− mice, as shown by deficits in sensorimotor gating, in selective attention, in social interactions, and in learning and memory processes. In addition, Htr2B−/− mice presented with enhanced locomotor response to the psychostimulants dizocilpine and amphetamine, and with robust alterations in sleep architecture. Moreover, ablation of 5-HT2B receptors induced a region-selective decrease of dopamine and glutamate concentrations in the dorsal striatum. Importantly, selected schizophrenic-like phenotypes and endophenotypes were rescued by chronic haloperidol treatment. We report herein that 5-HT2B receptor deficiency confers a wide spectrum of antipsychotic-sensitive schizophrenic-like behavioral and psychopharmacological phenotypes in mice and provide first evidence for a role of 5-HT2B receptors in the neurobiology of psychotic disorders

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This work studies the effect of clozapine (CLO) on the electroencephalography (EEG) and reactive oxygen species (ROS) production by peripheral blood monocytes (MO) in patients with schizophrenia (SCH). The aim of the study was to investigate the mechanism of action of CLO, to clarify the effect of CLO on EEG absolute power spectrum and ROS production, and explore the relationship of these effects with clinical response. We also tried to clarify whether the EEG changes or ROS production would help to identify the patients who were most likely to respond to treatment with CLO. Our findings suggest that the amount of slow background activity, particularly the absolute power of the theta frequency band, in the EEG is markedly increased by CLO treatment and this finding correlates positively with clinical improvement in patients with SCH. CLO affected the production of ROS by blood MO with reduction or minimal increase of the ROS production being associated with clinical improvement, whereas marked increase of the ROS production did not. Also a positive correlation between theta absolute power increase in the EEG and suppression of the production of ROS by blood MO was found. The correlations between different symptom clusters of SCH and the EEG rhythms were investigated; the absolute power of beta activity in the EEG seemed to correlate positively to overall psychopathology in patients with SCH showing inadequate response. The results suggest that the EEG background activity and investigation of the production of ROS by MO seem to be an adjunctive method to objectively assess and possibly predict the therapeutic effect of CLO in patients with chronic SCH showing inadequate response to treatment with conventional antipsychotics.