987 resultados para Distance Scale


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To date, there is no widely accepted clinical scale to monitor the evolution of depressive symptoms in demented patients. We assessed the sensitivity to treatment of a validated French version of the Health of the Nation Outcome Scale (HoNOS) 65+ compared to five routinely used scales. Thirty elderly inpatients with ICD-10 diagnosis of dementia and depression were evaluated at admission and discharge using paired t-test. Using the Brief Psychiatric Rating Scale (BPRS) "depressive mood" item as gold standard, a receiver operating characteristic curve (ROC) analysis assessed the validity of HoNOS65+F "depressive symptoms" item score changes. Unlike Geriatric Depression Scale, Mini Mental State Examination and Activities of Daily Living scores, BPRS scores decreased and Global Assessment Functioning Scale score increased significantly from admission to discharge. Amongst HoNOS65+F items, "behavioural disturbance", "depressive symptoms", "activities of daily life" and "drug management" items showed highly significant changes between the first and last day of hospitalization. The ROC analysis revealed that changes in the HoNOS65+F "depressive symptoms" item correctly classified 93% of the cases with good sensitivity (0.95) and specificity (0.88) values. These data suggest that the HoNOS65+F "depressive symptoms" item may provide a valid assessment of the evolution of depressive symptoms in demented patients.

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Rapport de synthèse Introduction : Le Glasgow coma score (GCS) est un outil reconnu permettant l'évaluation des patients après avoir subi un traumatisme crânien. Il est réputé pour sa simplicité et sa reproductibilité permettant ainsi aux soignants une évaluation appropriée et continue du status neurologique des patients. Le GCS est composé de trois catégories évaluant la réponse oculaire, verbale et motrice. En Suisse, les soins préhospitaliers aux patients victimes d'un trauma crânien sévère sont effectués par des médecins, essdntiellement à bord des hélicoptères médicalisés. Avant une anesthésie générale nécessaire à ces patients, une évaluation du GCS est essentielle indiquant au personnel hospitalier la gravité des lésions cérébrales. Afin d'évaluer la connaissance du GCS par les médecins à bord des hélicoptères médicalisés en Suisse, nous avons élaboré un questionnaire, contenant dans une première partie des questions sur les connaissances générales du GCS suivi d'un cas clinique. Objectif : Evaluation des connaissances pratiques et théoriques du GCS par les médecins travaillant à bord des hélicoptères médicalisés en Suisse. Méthode : Etude observationnelle prospective et anonymisée à l'aide d'un questionnaire. Evaluation des connaissances générales du GCS et de son utilisation clinique lors de la présentation d'un cas. Résultats : 16 des 18 bases d'hélicoptères médicalisés suisses ont participé à notre étude. 130 questionnaires ont été envoyés et le taux de réponse a été de 79.2%. Les connaissances théoriques du GCS étaient comparables pour tous les médecins indépendamment de leur niveau de formation. Des erreurs dans l'appréciation du cas clinique étaient présentes chez 36.9% des participants. 27.2% ont commis des erreurs dans le score moteur et 18.5% dans le score verbal. Les erreurs ont été répertoriées le plus fréquemment chez les médecins assistants (47.5%, p=0.09), suivi par les chefs de clinique (31.6%, p=0.67) et les médecins installés en cabinet (18.4%, p=1.00). Les médecins cadres ont fait significativement moins d'erreurs que les autres participants (0%, p<0.05). Aucune différence significative n'à été observée entre les différentes spécialités (anesthésie, médecine interne, médecine général et «autres »). Conclusion Même si les connaissances théoriques du GCS sont adéquates parmi les médecins travaillant à bord des hélicoptères médicalisés, des erreurs dans son application clinique sont présentes dans plus d'un tiers des cas. Les médecins avec le moins d'expériences professionnelle font le plus d'erreurs. Au vu de l'importance de l'évaluation correcte du score de Glasgow initial, une amélioration des connaissances est indispensable.

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This study aimed to investigate the influence of ankle osteoarthritis (AOA) treatments, i.e., ankle arthrodesis (AA) and total ankle replacement (TAR), on the kinematics of multi-segment foot and ankle complex during relatively long-distance gait. Forty-five subjects in four groups (AOA, AA, TAR, and control) were equipped with a wearable system consisting of inertial sensors installed on the tibia, calcaneus, and medial metatarsals. The subjects walked 50-m twice while the system measured the kinematic parameters of their multi-segment foot: the range of motion of joints between tibia, calcaneus, and medial metatarsals in three anatomical planes, and the peaks of angular velocity of these segments in the sagittal plane. These parameters were then compared among the four groups. It was observed that the range of motion and peak of angular velocities generally improved after TAR and were similar to the control subjects. However, unlike AOA and TAR, AA imposed impairments in the range of motion in the coronal plane for both the tibia-calcaneus and tibia-metatarsals joints. In general, the kinematic parameters showed significant correlation with established clinical scales (FFI and AOFAS), which shows their convergent validity. Based on the kinematic parameters of multi-segment foot during 50-m gait, this study showed significant improvements in foot mobility after TAR, but several significant impairments remained after AA.

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High-throughput technologies are now used to generate more than one type of data from the same biological samples. To properly integrate such data, we propose using co-modules, which describe coherent patterns across paired data sets, and conceive several modular methods for their identification. We first test these methods using in silico data, demonstrating that the integrative scheme of our Ping-Pong Algorithm uncovers drug-gene associations more accurately when considering noisy or complex data. Second, we provide an extensive comparative study using the gene-expression and drug-response data from the NCI-60 cell lines. Using information from the DrugBank and the Connectivity Map databases we show that the Ping-Pong Algorithm predicts drug-gene associations significantly better than other methods. Co-modules provide insights into possible mechanisms of action for a wide range of drugs and suggest new targets for therapy

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INTRODUCTION: Spectral frequencies of the surface electromyogram (sEMG) increase with contraction force, but debate still exists on whether this increase is affected by various methodological and anatomical factors. This study aimed to investigate the influence of inter-electrode distance (IED) and contraction modality (step-wise vs. ramp) on the changes in spectral frequencies with increasing contraction strength for the vastus lateralis (VL) and vastus medialis (VM) muscles. METHODS: Twenty healthy male volunteers were assessed for isometric sEMG activity of the VM and VL, with the knee at 90° flexion. Subjects performed isometric ramp contractions in knee extension (6-s duration) with the force gradually increasing from 0 to 80 % MVC. Also, subjects performed 4-s step-wise isometric contractions at 10, 20, 30, 40, 50, 60, 70, and 80 % MVC. Interference sEMG signals were recorded simultaneously at different IEDs: 10, 20, 30, and 50 mm. The mean (F mean) and median (F median) frequencies and root mean square (RMS) of sEMG signals were calculated. RESULTS: For all IEDs, contraction modalities, and muscles tested, spectral frequencies increased significantly with increasing level of force up to 50-60 % MVC force. Spectral indexes increased systematically as IED was decreased. The sensitivity of spectral frequencies to changes in contraction force was independent of IED. The behaviour of spectral indexes with increasing contraction force was similar for step-wise and ramp contractions. CONCLUSIONS: In the VL and VM muscles, it is highly unlikely that a particular inter-electrode distance or contraction modality could have prevented the observation of the full extent of the increase in spectral frequencies with increasing force level.

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Des progrès significatifs ont été réalisés dans le domaine de l'intégration quantitative des données géophysique et hydrologique l'échelle locale. Cependant, l'extension à de plus grandes échelles des approches correspondantes constitue encore un défi majeur. Il est néanmoins extrêmement important de relever ce défi pour développer des modèles fiables de flux des eaux souterraines et de transport de contaminant. Pour résoudre ce problème, j'ai développé une technique d'intégration des données hydrogéophysiques basée sur une procédure bayésienne de simulation séquentielle en deux étapes. Cette procédure vise des problèmes à plus grande échelle. L'objectif est de simuler la distribution d'un paramètre hydraulique cible à partir, d'une part, de mesures d'un paramètre géophysique pertinent qui couvrent l'espace de manière exhaustive, mais avec une faible résolution (spatiale) et, d'autre part, de mesures locales de très haute résolution des mêmes paramètres géophysique et hydraulique. Pour cela, mon algorithme lie dans un premier temps les données géophysiques de faible et de haute résolution à travers une procédure de réduction déchelle. Les données géophysiques régionales réduites sont ensuite reliées au champ du paramètre hydraulique à haute résolution. J'illustre d'abord l'application de cette nouvelle approche dintégration des données à une base de données synthétiques réaliste. Celle-ci est constituée de mesures de conductivité hydraulique et électrique de haute résolution réalisées dans les mêmes forages ainsi que destimations des conductivités électriques obtenues à partir de mesures de tomographic de résistivité électrique (ERT) sur l'ensemble de l'espace. Ces dernières mesures ont une faible résolution spatiale. La viabilité globale de cette méthode est testée en effectuant les simulations de flux et de transport au travers du modèle original du champ de conductivité hydraulique ainsi que du modèle simulé. Les simulations sont alors comparées. Les résultats obtenus indiquent que la procédure dintégration des données proposée permet d'obtenir des estimations de la conductivité en adéquation avec la structure à grande échelle ainsi que des predictions fiables des caractéristiques de transports sur des distances de moyenne à grande échelle. Les résultats correspondant au scénario de terrain indiquent que l'approche d'intégration des données nouvellement mise au point est capable d'appréhender correctement les hétérogénéitées à petite échelle aussi bien que les tendances à gande échelle du champ hydraulique prévalent. Les résultats montrent également une flexibilté remarquable et une robustesse de cette nouvelle approche dintégration des données. De ce fait, elle est susceptible d'être appliquée à un large éventail de données géophysiques et hydrologiques, à toutes les gammes déchelles. Dans la deuxième partie de ma thèse, j'évalue en détail la viabilité du réechantillonnage geostatique séquentiel comme mécanisme de proposition pour les méthodes Markov Chain Monte Carlo (MCMC) appliquées à des probmes inverses géophysiques et hydrologiques de grande dimension . L'objectif est de permettre une quantification plus précise et plus réaliste des incertitudes associées aux modèles obtenus. En considérant une série dexemples de tomographic radar puits à puits, j'étudie deux classes de stratégies de rééchantillonnage spatial en considérant leur habilité à générer efficacement et précisément des réalisations de la distribution postérieure bayésienne. Les résultats obtenus montrent que, malgré sa popularité, le réechantillonnage séquentiel est plutôt inefficace à générer des échantillons postérieurs indépendants pour des études de cas synthétiques réalistes, notamment pour le cas assez communs et importants où il existe de fortes corrélations spatiales entre le modèle et les paramètres. Pour résoudre ce problème, j'ai développé un nouvelle approche de perturbation basée sur une déformation progressive. Cette approche est flexible en ce qui concerne le nombre de paramètres du modèle et lintensité de la perturbation. Par rapport au rééchantillonage séquentiel, cette nouvelle approche s'avère être très efficace pour diminuer le nombre requis d'itérations pour générer des échantillons indépendants à partir de la distribution postérieure bayésienne. - Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending corresponding approaches beyond the local scale still represents a major challenge, yet is critically important for the development of reliable groundwater flow and contaminant transport models. To address this issue, I have developed a hydrogeophysical data integration technique based on a two-step Bayesian sequential simulation procedure that is specifically targeted towards larger-scale problems. The objective is to simulate the distribution of a target hydraulic parameter based on spatially exhaustive, but poorly resolved, measurements of a pertinent geophysical parameter and locally highly resolved, but spatially sparse, measurements of the considered geophysical and hydraulic parameters. To this end, my algorithm links the low- and high-resolution geophysical data via a downscaling procedure before relating the downscaled regional-scale geophysical data to the high-resolution hydraulic parameter field. I first illustrate the application of this novel data integration approach to a realistic synthetic database consisting of collocated high-resolution borehole measurements of the hydraulic and electrical conductivities and spatially exhaustive, low-resolution electrical conductivity estimates obtained from electrical resistivity tomography (ERT). The overall viability of this method is tested and verified by performing and comparing flow and transport simulations through the original and simulated hydraulic conductivity fields. The corresponding results indicate that the proposed data integration procedure does indeed allow for obtaining faithful estimates of the larger-scale hydraulic conductivity structure and reliable predictions of the transport characteristics over medium- to regional-scale distances. The approach is then applied to a corresponding field scenario consisting of collocated high- resolution measurements of the electrical conductivity, as measured using a cone penetrometer testing (CPT) system, and the hydraulic conductivity, as estimated from electromagnetic flowmeter and slug test measurements, in combination with spatially exhaustive low-resolution electrical conductivity estimates obtained from surface-based electrical resistivity tomography (ERT). The corresponding results indicate that the newly developed data integration approach is indeed capable of adequately capturing both the small-scale heterogeneity as well as the larger-scale trend of the prevailing hydraulic conductivity field. The results also indicate that this novel data integration approach is remarkably flexible and robust and hence can be expected to be applicable to a wide range of geophysical and hydrological data at all scale ranges. In the second part of my thesis, I evaluate in detail the viability of sequential geostatistical resampling as a proposal mechanism for Markov Chain Monte Carlo (MCMC) methods applied to high-dimensional geophysical and hydrological inverse problems in order to allow for a more accurate and realistic quantification of the uncertainty associated with the thus inferred models. Focusing on a series of pertinent crosshole georadar tomographic examples, I investigated two classes of geostatistical resampling strategies with regard to their ability to efficiently and accurately generate independent realizations from the Bayesian posterior distribution. The corresponding results indicate that, despite its popularity, sequential resampling is rather inefficient at drawing independent posterior samples for realistic synthetic case studies, notably for the practically common and important scenario of pronounced spatial correlation between model parameters. To address this issue, I have developed a new gradual-deformation-based perturbation approach, which is flexible with regard to the number of model parameters as well as the perturbation strength. Compared to sequential resampling, this newly proposed approach was proven to be highly effective in decreasing the number of iterations required for drawing independent samples from the Bayesian posterior distribution.

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Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the scale of a field site represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed downscaling procedure based on a non-linear Bayesian sequential simulation approach. The main objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity logged at collocated wells and surface resistivity measurements, which are available throughout the studied site. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariatekernel density function. Then a stochastic integration of low-resolution, large-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities is applied. The overall viability of this downscaling approach is tested and validated by comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure allows obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

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This paper introduces local distance-based generalized linear models. These models extend (weighted) distance-based linear models firstly with the generalized linear model concept, then by localizing. Distances between individuals are the only predictor information needed to fit these models. Therefore they are applicable to mixed (qualitative and quantitative) explanatory variables or when the regressor is of functional type. Models can be fitted and analysed with the R package dbstats, which implements several distancebased prediction methods.

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L'objectif de l'étude présentée est d'adapter et de valider une version française de la Stigma Scale (King, 2007) auprès d'une population de personnes souffrant de troubles psychiques. Dans une première phase, la stabilité temporelle (fidélité test-retest), la cohérence interne et la validité convergente de l'instrument original à 28 items traduit en français ont été évaluées auprès d'un échantillon de 183 patients. Les résultats d'analyses factorielles confirmatoires ne nous ont pas permis de confirmer la structure originale de l'instrument. Nous avons donc proposé, sur la base des résultats d'une analyse factorielle exploratoire, une version courte de l'échelle de stigmatisation (9 items) qui conserve la structure en trois facteurs du modèle original. Dans une deuxième phase, nous avons examiné les qualités psychométriques et validé cette version abrégée de l'échelle de stigmatisation auprès d'un second échantillon de 234 patients. Les indices d'ajustements de notre analyse factorielle confirmatoire confirme la structure en trois facteurs de la version abrégée de la Stigma Scale. Les résultats suggèrent que la version française abrégée de l'échelle de stigmatisation constitue un instrument utile, fiable et valide dans l'autoévaluation de la stigmatisation perçue par des personnes souffrant de troubles psychiques. - Aim People suffering from mental illness are exposed to stigma. However, only few tools are available to assess stigmatization as perceived from the patient's perspective. The aim of this study is to adapt and validate a French version of the Stigma Scale (King, 2007). This self-report questionnaire has a three-factor structure: discrimination, disclosure and positive aspects of mental illness. Discrimination subscale refers to perceived negative reactions by others. Disclosure subscale refers mainly to managing disclosure to avoid discrimination and finally positive aspects subscale taps into how patients are becoming more accepting, more understanding toward their illness. Method In the first step, internal consistency, convergent validity and test-retest reliability of the French adaptation of the 28-item scale have been assessed on a sample of 183 patients. Results of confirmatory factor analyses (CFA) did not confirm the hypothesized structure. In light of the failed attempts to validate the original version, an alternative 9-item short-form version of the Stigma Scale, maintaining the integrity of the original model, was developed based on results of exploratory factor analyses in the first sample and cross- validated in a new sample of 234 patients. Results Results of CFA did not confirm that the data fitted well to the three-factor model of the 28-item Stigma Scale (χ2/άί=2.02, GFI=0.77, AGFI=0.73, RMSEA=0.07, CFI=0.77 et NNFI=0.75). Cronbach's α are excellent for discrimination (0.84) and disclosure (0.83) subscales but poor for potential positive aspects (0.46). External validity is satisfactory. Overall Stigma Scale total score is negatively correlated with score on Rosenberg's Self-Esteem Scale (r = -0.49), and each sub-scale is significantly correlated with a visual analogue scale that refers to the specific aspect of stigma (0.43 < |r| < 0.60). Intraclass correlation coefficients between 0.68 and 0.89 indicate good test- retest reliability. Results of CFA demonstrate that the items chosen for the short version of the Stigma Scale have the expected fit properties fa2/df=1.02, GFI=0.98, AGFI=0.98, RMSEA=0.01, CFI=1.0 et NNFI=1.0). Considering the small number (3 items) of items in each subscales of the short version of the Stigma Scale, a coefficients for the discrimination (0.57), disclosure (0.80) and potential positive aspects subscales (0.62) are considered as good. Conclusion Our results suggest that the 9-item French short-version of the Stigma Scale is a useful, reliable and valid self-report questionnaire to assess perceived stigmatization in people suffering from mental illness. The time of completion is really short and questions are well understood and accepted by the patients.

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OBJECTIVE: To determine the psychometric properties of an adapted version of the Falls Efficacy Scale (FES) in older rehabilitation patients. DESIGN: Cross-sectional survey. SETTING: Postacute rehabilitation facility in Switzerland. PARTICIPANTS: Seventy elderly persons aged 65 years and older receiving postacute, inpatient rehabilitation. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: FES questions asked about subject's confidence (range, 0 [none]-10 [full]) in performing 12 activities of daily living (ADLs) without falling. Construct validity was assessed using correlation with measures of physical (basic ADLs [BADLs]), cognitive (Mini-Mental State Examination [MMSE]), affective (15-item Geriatric Depression Scale [GDS]), and mobility (Performance Oriented Mobility Assessment [POMA]) performance. Predictive validity was assessed using the length of rehabilitation stay as the outcome. To determine test-retest reliability, FES administration was repeated in a random subsample (n=20) within 72 hours. RESULTS: FES scores ranged from 10 to 120 (mean, 88.7+/-26.5). Internal consistency was optimal (Cronbach alpha=.90), and item-to-total correlations were all significant, ranging from .56 (toilet use) to .82 (reaching into closets). Test-retest reliability was high (intraclass correlation coefficient, .97; 95% confidence interval, .95-.99; P<.001). Subjects reporting a fall in the previous year had lower FES scores than nonfallers (85.0+/-25.2 vs 94.4+/-27.9, P=.054). The FES correlated with POMA (Spearman rho=.40, P<.001), MMSE (rho=.37, P=.001), BADL (rho=.43, P<.001), and GDS (rho=-.53, P<.001) scores. These relationships remained significant in multivariable analysis for BADLs and GDS, confirming FES construct validity. There was a significant inverse relationship between FES score and the length of rehabilitation stay, independent of sociodemographic, functional, cognitive, and fall status. CONCLUSIONS: This adapted FES is reliable and valid in older patients undergoing postacute rehabilitation. The independent association between poor falls efficacy and increased length of stay has not been previously described and needs further investigations.

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The hypothesis of ecological divergence giving rise to premating isolation in the face of gene flow is controversial. However, this may be an important mechanism to explain the rapid multiplication of species during adaptive radiation following the colonization of a new environment when geographical barriers to gene flow are largely absent but underutilized niche space is abundant. Using cichlid fish, we tested the prediction of ecological speciation that the strength of premating isolation among species is predicted by phenotypic rather than genetic distance. We conducted mate choice experiments between three closely related, sympatric species of a recent radiation in Lake Mweru (Zambia/DRC) that differ in habitat use and phenotype, and a distantly related population from Lake Bangweulu that resembles one of the species in Lake Mweru. We found significant assortative mating among all closely related, sympatric species that differed phenotypically, but none between the distantly related allopatric populations of more similar phenotype. Phenotypic distance between species was a good predictor of the strength of premating isolation, suggesting that assortative mating can evolve rapidly in association with ecological divergence during adaptive radiation. Our data also reveals that distantly related allopatric populations that have not diverged phenotypically, may hybridize when coming into secondary contact, e.g. upon river capture because of diversion of drainage systems.

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BACKGROUND: Accurate catalogs of structural variants (SVs) in mammalian genomes are necessary to elucidate the potential mechanisms that drive SV formation and to assess their functional impact. Next generation sequencing methods for SV detection are an advance on array-based methods, but are almost exclusively limited to four basic types: deletions, insertions, inversions and copy number gains. RESULTS: By visual inspection of 100 Mbp of genome to which next generation sequence data from 17 inbred mouse strains had been aligned, we identify and interpret 21 paired-end mapping patterns, which we validate by PCR. These paired-end mapping patterns reveal a greater diversity and complexity in SVs than previously recognized. In addition, Sanger-based sequence analysis of 4,176 breakpoints at 261 SV sites reveal additional complexity at approximately a quarter of structural variants analyzed. We find micro-deletions and micro-insertions at SV breakpoints, ranging from 1 to 107 bp, and SNPs that extend breakpoint micro-homology and may catalyze SV formation. CONCLUSIONS: An integrative approach using experimental analyses to train computational SV calling is essential for the accurate resolution of the architecture of SVs. We find considerable complexity in SV formation; about a quarter of SVs in the mouse are composed of a complex mixture of deletion, insertion, inversion and copy number gain. Computational methods can be adapted to identify most paired-end mapping patterns.