84 resultados para PTSD, bombing, cognitive models, community, survey


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Résumé Contexte: Bon nombre d'études épidémiologiques concernant les premières crises comitiales ont été effectuées principalement sur des populations générales. Cependant, les patients admis dans un hôpital peuvent présenter des éléments cliniques différents. Nous avons donc mené une étude prospective auprès de sujets dans une population hospitalière ayant subi une première crise d'épilepsie, afin d'étudier leur pronostic et le rôle des examens complémentaires (examen neurologique, imagerie cérébrale, examens sanguins, EEG) dans le choix de l'administration d'une médication antiépileptique. Méthodes : Sur une période d'une année, nous avons suivi 177 patients adultes, admis consécutivement, ayant présenté une crise d'épilepsie dont l'évaluation aiguë a été effectuée dans notre hôpital. Pendant 6 mois, nous avons pratiqué pour chaque patient un suivi du traitement antiépileptique, des récidives de crises et d'un éventuel décès. Résultats : L'examen neurologique était anormal dans 72.3% des cas, l'imagerie cérébrale dans 54.8% et les examens sanguins dans 57.1%. L'EEG a montré des éléments épileptiformes dans 33.9% des cas. L'étiologie la plus fréquemment représentée était constituée par des intoxications. Un traitement antiépileptique a été prescrit chez 51% des patients. 31.6% des sujets suivis à six mois ont subi une récidive ; la mortalité s'est élevée à 17.8%. Statistiquement, l'imagerie cérébrale, l'EEG et l'examen neurologique étaient des facteurs prédictifs indépendants pour l'administration d'antiépileptiques, et l'imagerie cérébrale le seul facteur associé au pronostic. Conclusions : Les patients évalués en aigu dans un hôpital pour une première crise comitiale présentent un profil médical sous-jacent, qui explique probablement leur mauvais pronostic. L'imagerie cérébrale s'est avérée être le test paraclinique le plus important dans la prévention du traitement et du pronostic. Mots-clés : première crise d'épilepsie, étiologie, pronostic, récidive, médication antiépileptique, population hospitalière Summary Background: Epidemiological studies focusing on first-ever seizures have been carried out mainly on community based populations. However, since hospital populations may display varying clinical features, we prospectively analysed patients with first-ever seizure in a hospital based community to evaluate prognosis and the role of complementary investigations in the decision to administer antiepileptic drugs (AED). Methods: Over one year, we recruited 177 consecutive adult patients with a first seizure acutely evaluated in our hospital. During six months' follow-up data relating to AED treatment, recurrence of seizures and death were collected for each patient. Results:. Neurological examination was abnormal in 72.3%, neuroimaging in 54.8% and biochemical tests in 57.1%. Electroencephalogram (EEG) showed epileptiform features in 33.9%. Toxicity represented the most common aetiology. AED was prescribed in 51% of patients. Seizure recurrence at six months involved 31.6% of patients completing the follow-up; mortality was 17.8%. Statistical analysis showed that brain CT, EEG and neurological examination are independent predictive factors for AED administration, but only CT scan is associated with outcome. Conclusions: Patients evaluated acutely for first- ever seizure in a hospital setting have severe underlying clinical conditions apparently related to their relatively poor prognosis. Neuroimaging represents the most important paraclinical test in predicting both treatment administration and outcome.

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ACCESSIBLE SUMMARY: Patients' satisfaction is scarcely studied within the context of community treatment for adolescents. Thus, this study adopts a multiple perspective on patients' satisfaction (including service users as well as staff members). The results highlighted that all informants (patients, foster carers in foster homes and professional caregivers from community treatment teams) perceived the patients to be satisfied, with foster carers reporting the highest patient satisfaction rate. Considering the patient satisfaction rate from multiple perspectives provides complementary understandings. Clinical outcomes and, specifically, a reduction in emotional difficulties were related to patient's satisfaction, but only from the patients' perspective. ABSTRACT: Community treatment (CT) teams in Switzerland provide care to patients who are unable to use regular child and adolescent mental health services (i.e. inpatient and outpatients facilities). No study has considered patients' self-rated satisfaction alongside with staff members' perspectives on patient satisfaction. Thus, adopting a cross-sectional survey design, we collected patients' satisfaction using the Client Satisfaction Questionnaire (CSQ-8), rated by multiple informants (patients, foster carers in foster homes and professional caregivers from CT teams). Professional caregivers assessed clinical outcomes using the Health of the Nation Outcome Scale for Children and Adolescents. The results indicated that all informants were satisfied with the community treatment teams. The satisfaction scores were not correlated across informants; however, the alleviation of emotional symptoms was correlated with patients' satisfaction. This study indicated that the use of a combined approach including the views of service users and professionals gives important complementary information. Finally, in our sample, lower emotional symptoms were linked to enhanced patient satisfaction. This study demonstrated the importance of considering multiple perspectives to obtain the most accurate picture of patients' satisfaction. Second, focusing on the reduction of emotional symptoms might lead to a higher degree of patients' satisfaction.

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ACCESSIBLE SUMMARY: Patients' satisfaction is scarcely studied within the context of community treatment for adolescents. Thus, this study adopts a multiple perspective on patients' satisfaction (including service users as well as staff members). The results highlighted that all informants (patients, foster carers in foster homes and professional caregivers from community treatment teams) perceived the patients to be satisfied, with foster carers reporting the highest patient satisfaction rate. Considering the patient satisfaction rate from multiple perspectives provides complementary understandings. Clinical outcomes and, specifically, a reduction in emotional difficulties were related to patient's satisfaction, but only from the patients' perspective. ABSTRACT: Community treatment (CT) teams in Switzerland provide care to patients who are unable to use regular child and adolescent mental health services (i.e. inpatient and outpatients facilities). No study has considered patients' self-rated satisfaction alongside with staff members' perspectives on patient satisfaction. Thus, adopting a cross-sectional survey design, we collected patients' satisfaction using the Client Satisfaction Questionnaire (CSQ-8), rated by multiple informants (patients, foster carers in foster homes and professional caregivers from CT teams). Professional caregivers assessed clinical outcomes using the Health of the Nation Outcome Scale for Children and Adolescents. The results indicated that all informants were satisfied with the community treatment teams. The satisfaction scores were not correlated across informants; however, the alleviation of emotional symptoms was correlated with patients' satisfaction. This study indicated that the use of a combined approach including the views of service users and professionals gives important complementary information. Finally, in our sample, lower emotional symptoms were linked to enhanced patient satisfaction. This study demonstrated the importance of considering multiple perspectives to obtain the most accurate picture of patients' satisfaction. Second, focusing on the reduction of emotional symptoms might lead to a higher degree of patients' satisfaction.

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BACKGROUND: Healthy lifestyle including sufficient physical activity may mitigate or prevent adverse long-term effects of childhood cancer. We described daily physical activities and sports in childhood cancer survivors and controls, and assessed determinants of both activity patterns. METHODOLOGY/PRINCIPAL FINDINGS: The Swiss Childhood Cancer Survivor Study is a questionnaire survey including all children diagnosed with cancer 1976-2003 at age 0-15 years, registered in the Swiss Childhood Cancer Registry, who survived ≥5 years and reached adulthood (≥20 years). Controls came from the population-based Swiss Health Survey. We compared the two populations and determined risk factors for both outcomes in separate multivariable logistic regression models. The sample included 1058 survivors and 5593 controls (response rates 78% and 66%). Sufficient daily physical activities were reported by 52% (n = 521) of survivors and 37% (n = 2069) of controls (p<0.001). In contrast, 62% (n = 640) of survivors and 65% (n = 3635) of controls reported engaging in sports (p = 0.067). Risk factors for insufficient daily activities in both populations were: older age (OR for ≥35 years: 1.5, 95CI 1.2-2.0), female gender (OR 1.6, 95CI 1.3-1.9), French/Italian Speaking (OR 1.4, 95CI 1.1-1.7), and higher education (OR for university education: 2.0, 95CI 1.5-2.6). Risk factors for no sports were: being a survivor (OR 1.3, 95CI 1.1-1.6), older age (OR for ≥35 years: 1.4, 95CI 1.1-1.8), migration background (OR 1.5, 95CI 1.3-1.8), French/Italian speaking (OR 1.4, 95CI 1.2-1.7), lower education (OR for compulsory schooling only: 1.6, 95CI 1.2-2.2), being married (OR 1.7, 95CI 1.5-2.0), having children (OR 1.3, 95CI 1.4-1.9), obesity (OR 2.4, 95CI 1.7-3.3), and smoking (OR 1.7, 95CI 1.5-2.1). Type of diagnosis was only associated with sports. CONCLUSIONS/SIGNIFICANCE: Physical activity levels in survivors were lower than recommended, but comparable to controls and mainly determined by socio-demographic and cultural factors. Strategies to improve physical activity levels could be similar as for the general population.

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BACKGROUND: Even if a large proportion of physiotherapists work in the private sector worldwide, very little is known of the organizations within which they practice. Such knowledge is important to help understand contexts of practice and how they influence the quality of services and patient outcomes. The purpose of this study was to: 1) describe characteristics of organizations where physiotherapists practice in the private sector, and 2) explore the existence of a taxonomy of organizational models. METHODS: This was a cross-sectional quantitative survey of 236 randomly-selected physiotherapists. Participants completed a purpose-designed questionnaire online or by telephone, covering organizational vision, resources, structures and practices. Organizational characteristics were analyzed descriptively, while organizational models were identified by multiple correspondence analyses. RESULTS: Most organizations were for-profit (93.2%), located in urban areas (91.5%), and within buildings containing multiple businesses/organizations (76.7%). The majority included multiple providers (89.8%) from diverse professions, mainly physiotherapy assistants (68.7%), massage therapists (67.3%) and osteopaths (50.2%). Four organizational models were identified: 1) solo practice, 2) middle-scale multiprovider, 3) large-scale multiprovider and 4) mixed. CONCLUSIONS: The results of this study provide a detailed description of the organizations where physiotherapists practice, and highlight the importance of human resources in differentiating organizational models. Further research examining the influences of these organizational characteristics and models on outcomes such as physiotherapists' professional practices and patient outcomes are needed.

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1. Statistical modelling is often used to relate sparse biological survey data to remotely derived environmental predictors, thereby providing a basis for predictively mapping biodiversity across an entire region of interest. The most popular strategy for such modelling has been to model distributions of individual species one at a time. Spatial modelling of biodiversity at the community level may, however, confer significant benefits for applications involving very large numbers of species, particularly if many of these species are recorded infrequently. 2. Community-level modelling combines data from multiple species and produces information on spatial pattern in the distribution of biodiversity at a collective community level instead of, or in addition to, the level of individual species. Spatial outputs from community-level modelling include predictive mapping of community types (groups of locations with similar species composition), species groups (groups of species with similar distributions), axes or gradients of compositional variation, levels of compositional dissimilarity between pairs of locations, and various macro-ecological properties (e.g. species richness). 3. Three broad modelling strategies can be used to generate these outputs: (i) 'assemble first, predict later', in which biological survey data are first classified, ordinated or aggregated to produce community-level entities or attributes that are then modelled in relation to environmental predictors; (ii) 'predict first, assemble later', in which individual species are modelled one at a time as a function of environmental variables, to produce a stack of species distribution maps that is then subjected to classification, ordination or aggregation; and (iii) 'assemble and predict together', in which all species are modelled simultaneously, within a single integrated modelling process. These strategies each have particular strengths and weaknesses, depending on the intended purpose of modelling and the type, quality and quantity of data involved. 4. Synthesis and applications. The potential benefits of modelling large multispecies data sets using community-level, as opposed to species-level, approaches include faster processing, increased power to detect shared patterns of environmental response across rarely recorded species, and enhanced capacity to synthesize complex data into a form more readily interpretable by scientists and decision-makers. Community-level modelling therefore deserves to be considered more often, and more widely, as a potential alternative or supplement to modelling individual species.

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Introduction: Fragile X syndrome (FXS) is the most common inherited cause of intellectual disability. With no curative treatment available, current therapeutic approaches are aimed at symptom management. FXS is caused by silencing the FMR1 gene, which encodes FMRP; as loss of FMRP leads to the development of symptoms associated with FXS. Areas covered: In this evaluation, the authors examine the role of the metabotropic glutamate receptor 5 (mGluR5) in the pathophysiology of FXS, and its suitability as a target for rescuing the disease state. Furthermore, the authors review the evidence from preclinical studies of pharmacological interventions targeting mGluR5 in FXS. Lastly, the authors assess the findings from clinical studies in FXS, in particular the use of the Aberrant Behavior Checklist-Community Edition (ABC-C) and the recently developed ABC-C for FXS scale, as clinical endpoints to assess disease modification in this patient population. Expert opinion: There is cautious optimism for the successful treatment of the core behavioral and cognitive symptoms of FXS based on preclinical data in animal models and early studies in humans. However, the association between mGluR5-heightened responsiveness and the clinical phenotype in humans remains to be demonstrated. Many questions regarding the optimal treatment and outcome measures of FXS remain unanswered.

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BACKGROUND: Low 24-hour urine volume (24 UV) may be a significant risk factor for decline in kidney function. We therefore aimed to study associated markers and possible determinants of 24 UV in a sample of the Swiss population. METHODS: The cross-sectional Swiss Salt Study included a population-based sample of 1535 (746 men and 789 women) individuals from three linguistic regions of Switzerland. Data from 1300 subjects were available for the present analysis. 24 UV was measured using 24-hour urine collection. Determinants of 24 UV were identified using multivariable linear regression models. RESULTS: In bivariate analysis, 24 UV was higher in women compared to men (2000 ml/24 h [interquartile range (IQR): 1354, 2562] versus 1780 ml/24 h [IQR: 1244, 2360], p = 0.002). In multivariable regression analyses, independent associated markers of 24 UV were female sex (β = 280, 95% confidence interval [CI]: 174, 386, p < 0.0001), fluid intake (β = 604, 95% CI: 539, 670, p < 0.0001), sodium excretion (β = 4.2, 95% CI: 3.4, 4.9, p < 0.0001) age (β = 6.6, CI: 3.4, 9.7, p < .0001), creatinine clearance (β = 2.4, CI: 0.2, 4.6, p = 0.04), living in the German-speaking part of Switzerland (β = 124, CI: 29, 219, p = 0.01), alcohol consumption (β = 41, CI: 9, 73, p = 0.01 for increasing categories of alcohol consumption), body mass index (β = -32, CI: -45, -18, p < 0.0001), current smoking (β = -146, CI: -265, -26, p = 0.02), and consumption of meat and cold cut (β = -56, CI: -108, -5, p = 0.03). CONCLUSION: In this large population-based, cross-sectional study, we found several strong and independent correlates for 24 UV. These findings may be important to improve our understanding in the development of chronic kidney disease.

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Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

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Mycorrhizal symbioses link the biosphere with the lithosphere by mediating nutrient cycles and energy flow though terrestrial ecosystems. A more mechanistic understanding of these plant-fungal associations may help ameliorate anthropogenic changes to C and N cycles and biotic communities. We explore three interacting principles: (1) optimal allocation, (2) biotic context and (3) fungal adaptability that may help predict mycorrhizal responses to carbon dioxide enrichment, nitrogen eutrophication, invasive species and land-use changes. Plant-microbial feedbacks and thresholds are discussed in light of these principles with the goal of generating testable hypotheses. Ideas to develop large-scale collaborative research efforts are presented. It is our hope that mycorrhizal symbioses can be effectively integrated into global change models and eventually their ecology will be understood well enough so that they can be managed to help offset some of the detrimental effects of anthropogenic environmental change.

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The reported prevalence of late-life depressive symptoms varies widely between studies, a finding that might be attributed to cultural as well as methodological factors. The EURO-D scale was developed to allow valid comparison of prevalence and risk associations between European countries. This study used Confirmatory Factor Analysis (CFA) and Rasch models to assess whether the goal of measurement invariance had been achieved; using EURO-D scale data collected in 10 European countries as part of the Survey of Health, Ageing and Retirement in Europe (SHARE) (n = 22,777). The results suggested a two-factor solution (Affective Suffering and Motivation) after Principal Component Analysis (PCA) in 9 of the 10 countries. With CFA, in all countries, the two-factor solution had better overall goodness-of-fit than the one-factor solution. However, only the Affective Suffering subscale was equivalent across countries, while the Motivation subscale was not. The Rasch model indicated that the EURO-D was a hierarchical scale. While the calibration pattern was similar across countries, between countries agreement in item calibrations was stronger for the items loading on the affective suffering than the motivation factor. In conclusion, there is evidence to support the EURO-D as either a uni-dimensional or bi-dimensional scale measure of depressive symptoms in late-life across European countries. The Affective Suffering sub-component had more robust cross-cultural validity than the Motivation sub-component.

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A better understanding of the factors that mould ecological community structure is required to accurately predict community composition and to anticipate threats to ecosystems due to global changes. We tested how well stacked climate-based species distribution models (S-SDMs) could predict butterfly communities in a mountain region. It has been suggested that climate is the main force driving butterfly distribution and community structure in mountain environments, and that, as a consequence, climate-based S-SDMs should yield unbiased predictions. In contrast to this expectation, at lower altitudes, climate-based S-SDMs overpredicted butterfly species richness at sites with low plant species richness and underpredicted species richness at sites with high plant species richness. According to two indices of composition accuracy, the Sorensen index and a matching coefficient considering both absences and presences, S-SDMs were more accurate in plant-rich grasslands. Butterflies display strong and often specialised trophic interactions with plants. At lower altitudes, where land use is more intense, considering climate alone without accounting for land use influences on grassland plant richness leads to erroneous predictions of butterfly presences and absences. In contrast, at higher altitudes, where climate is the main force filtering communities, there were fewer differences between observed and predicted butterfly richness. At high altitudes, even if stochastic processes decrease the accuracy of predictions of presence, climate-based S-SDMs are able to better filter out butterfly species that are unable to cope with severe climatic conditions, providing more accurate predictions of absences. Our results suggest that predictions should account for plants in disturbed habitats at lower altitudes but that stochastic processes and heterogeneity at high altitudes may limit prediction success of climate-based S-SDMs.

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OBJECTIVE: To investigate the relationship between levels of cognitive impairment and health services utilization in older patients undergoing post-acute rehabilitation. DESIGN: Cross-sectional study. SETTING: Post-acute rehabilitation facility. PARTICIPANTS: Patients (N = 1764) aged 70 years and older admitted over 3 years. MEASUREMENTS: Sociodemographic, medical, and functional data were collected upon admission. Based on discharge diagnoses, patients were classified as cognitively intact, cognitively impaired with no dementia (CIND), and demented. RESULTS: Dementia and CIND were diagnosed in 425 (24.1%) and 301 (17.1%) patients, respectively. Gradients from cognitively intact to cognitively impaired to demented patients were observed in median length of stay (19, 22, and 25 days, P < .001), and institutionalization rates at discharge (4.2%, 7.6%, and 28.8%, P < .001). Among patients discharged home, similar gradients were observed in utilization of home care (68.2%, 79.7%, and 83.3%, P < .001) and day care (3.1%, 7.1%, and 14.3%, P < .001). After adjustment, compared with cognitively intact patients, only those with dementia still had longer stays (+2.7 days) and increased odds of institutionalization (adjOR 6.1, 95% CI 4.0-9.3, P < .001). Among patients discharged home, use of home and day care remained higher in those with dementia (adjOR 1.8, 95% CI 1.2-2.7, P = .005, and adjOR 1.8, 95% CI 1.2-2.7, P = .005, respectively), while CIND patients had higher odds of using home care (adjOR 1.6, 95% CI 1.1-2.4, P = .028). CONCLUSION: Among patients undergoing post-acute rehabilitation, those with dementia had increased use of both institutional and community care, whereas those with CIND had increased use of home care services only. Future studies should investigate specific strategies susceptible to reduce the related burden on health care systems.

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BACKGROUND: Male carriers of the FMR1 premutation are at risk of developing the fragile X-associated tremor/ataxia syndrome (FXTAS), a newly recognised and largely under-diagnosed late onset neurodegenerative disorder. Patients affected with FXTAS primarily present with cerebellar ataxia and intention tremor. Cognitive decline has also been associated with the premutation, but the lack of data on its penetrance is a growing concern for clinicians who provide genetic counselling. METHODS: The Mattis Dementia Rating Scale (MDRS) was administered in a double blind fashion to 74 men aged 50 years or more recruited from fragile X families (35 premutation carriers and 39 intrafamilial controls) regardless of their clinical manifestation. Based on previous publications, marked cognitive impairment was defined by a score <or=123 on the MDRS. RESULTS: Both logistic and survival models confirmed that in addition to age and education level, premutation size plays a significant (p<0.01 and p<0.03 for logistic and survival model, respectively) role in cognitive impairment. The estimated penetrance of marked cognitive impairment in our sample (adjusted for the mean age 63.4 years and mean education level 9.7 years) for midsize/large (70-200 CGG) and small (55-69 CGG) premutation alleles was 33.3% (relative risk (RR) 6.5; p = 0.01) and 5.9% (RR 1.15; p = 0.9) respectively. Penetrance in the control group was 5.1%. CONCLUSIONS: Male carriers of midsize to large premutation alleles had a sixfold increased risk of developing cognitive decline and the risk increases with allele size. In addition, it was observed that cognitive impairment may precede motor symptoms. These data provide guidance for genetic counselling although larger samples are required to refine these estimates.

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Cognitive impairment has emerged as a major driver of disability in old age, with profound effects on individual well-being and decision making at older ages. In the light of policies aimed at postponing retirement ages, an important question is whether continued labour supply helps to maintain high levels of cognition at older ages. We use data of older men from the US Health and Retirement Study to estimate the effect of continued labour market participation at older ages on later-life cognition. As retirement itself is likely to depend on cognitive functioning and may thus be endogenous, we use offers of early retirement windows as instruments for retirement in econometric models for later-life cognitive functioning. These offers of early retirement are legally required to be nondiscriminatory and thus, inter alia, unrelated to cognitive functioning. At the same time, these offers of early retirement options are significant predictors of retirement. Although the simple ordinary least squares estimates show a negative relationship between retirement duration and various measures of cognitive functioning, instrumental variable estimates suggest that these associations may not be causal effects. Specifically, we find no clear relationship between retirement duration and later-life cognition for white-collar workers and, if anything, a positive relationship for blue-collar workers. Copyright © 2011 John Wiley & Sons, Ltd.