143 research outputs found

    CERAD und NOSGER: Der prädiktive Wert dieser Verfahren in der Demenzdiagnostik einer Schweizer gerontopsychiatrischen Patientenpopulation

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    Zusammenfassung: Hintergrund: Die CERAD-Batterie (Consortium to Establish a Registry for Alzheimer's Disease) ist ein gängiges Screeninginstrument in der Diagnostik der Alzheimer-Demenz. Dem NOSGER (Nurses Observation' Scale for Geriatric Patients), eigentlich entwickelt, um Verhaltensauffälligkeiten im Alltag zu erfassen, scheint bei der Alzheimer-Demenz auch eine diagnostische Bedeutung zuzukommen. Material und Methode: In einer retrospektiven Studie mit 400 Patienten unserer Klinik, die bei unterschiedlichen psychiatrischen Erkrankungen kognitive Störungen aufwiesen, haben wir CERAD und NOSGER mittels logistischer Berechnung in uni- und multivariaten Modellen auf ihren prädiktiven Wert für die Diagnose Demenz untersucht. Ergebnisse: Im univariaten Modell waren alle CERAD-Subtests signifikante Prädiktoren für Demenz. Das beste multivariate Modell umfasste die Subtests "Verbale Flüssigkeit", "Wortliste Abrufen", "Konstruktive Praxie Abrufen" und MMS (Mini-Mental Status). Der NOSGER zeigte keinen prädiktiven diagnostischen Wert. Schlussfolgerung: Innerhalb einer gerontopsychiatrischen Population grenzt der CERAD Demenzpatienten von nicht dementen mit hoher Vorhersagewahrscheinlichkeit ab, während der NOSGER keinen prädiktiven Wert für die Diagnose Demenz aufweis

    Mitigation of ionospheric signatures in Swarm GPS gravity field estimation using weighting strategies

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    Even though ESA's three-satellite low-earth orbit (LEO) mission Swarm is primarily a magnetic field mission, it can also serve as a gravity field mission. Located in a near-polar orbit with initial altitudes of 480&thinsp;km for Swarm A and Swarm C and 530&thinsp;km for Swarm B and equipped with geodetic-type dual frequency Global Positioning System (GPS) receivers, it is suitable for gravity field computation. Of course, the Swarm GPS-only gravity fields cannot compete with the gravity fields derived from the ultra-precise Gravity Recovery And Climate Experiment (GRACE) K-band measurements. But for various reasons like the end of the GRACE mission in October 2017, data gaps in the previous months due to battery aging, and the gap between GRACE and the recently launched GRACE Follow-On mission, Swarm gravity fields became important to maintain a continuous time series and to bridge the gap between the two dedicated gravity missions. By comparing the gravity fields derived from Swarm kinematic positions to the GRACE gravity fields, systematic errors have been observed in the Swarm results, especially around the geomagnetic equator. These errors are already visible in the kinematic positions as spikes up to a few centimeters, from where they propagate into the gravity field solutions. We investigate these systematic errors by analyzing the geometry-free linear combination of the GPS carrier-phase observations and its time derivatives using a combination of a Gaussian filter and a Savitzky–Golay filter and the Rate of Total Electron Content (TEC) Index (ROTI). Based on this, we present different weighting schemes and investigate their impact on the gravity field solutions in order to assess the success of different mitigation strategies. We will show that a combination of a derivative-based weighting approach with a ROTI-based weighting approach is capable of reducing the geoid rms from 21.6 to 12.0&thinsp;mm for a heavily affected month and that almost 10&thinsp;% more kinematic positions can be preserved compared to a derivative-based screening.</p

    All-optical reporting of inhibitory receptor driving force in the nervous system

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    Ionic driving forces provide the net electromotive force for ion movement across receptors, channels, and transporters, and are a fundamental property of all cells. In the nervous system, fast synaptic inhibition is mediated by chloride permeable GABAA and glycine receptors, and single-cell intracellular recordings have been the only method for estimating driving forces across these receptors (DFGABAA). Here we present a tool for quantifying inhibitory receptor driving force named ORCHID: all-Optical Reporting of CHloride Ion Driving force. We demonstrate ORCHID’s ability to provide accurate, high-throughput measurements of resting and dynamic DFGABAA from genetically targeted cell types over multiple timescales. ORCHID confirms theoretical predictions about the biophysical mechanisms that establish DFGABAA, reveals differences in DFGABAA between neurons and astrocytes, and affords the first in vivo measurements of intact DFGABAA. This work extends our understanding of inhibitory synaptic transmission and demonstrates the potential for all-optical methods to assess ionic driving forces

    Preliminary evidence for an increased likelihood of a stable trajectory in mild cognitive impairment in individuals with higher motivational abilities

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    BACKGROUND: Motivational abilities (MA), that describe skills in relation to goal-oriented behavior, have recently been found to be associated with neuropathological aging. Here we examine the impact of MA on the long-term course of mild cognitive impairment (MCI). METHODS: We followed-up N = 64 individuals diagnosed with MCI (M = 73 years, 44% female) for 3 years. MA were assessed by long-term informants of the participants using two scales: motivation and decision regulation [Volitional Components Questionnaires, VCQ, (Kuhl and Fuhrmann, Decomposing self-regulation and self-control: the volitional components inventory, 1998)]. Cognitive abilities were assessed with the Mini Mental State Examination (J Psychiatr Res 12:189-98, 1975). Survival analyses and multilevel modeling (MLM) were applied to determine the predicting effect of informant-rated MA at baseline on the likelihood of MCI stability and on the trajectory of cognitive abilities. RESULTS: Fifty percent (n = 32) of the MCI participants remained stable, while 32.8% (n = 21) and 17.2% (n = 11) converted to Alzheimer's disease (AD) or dropped-out, respectively. Survival analyses revealed that MCI cases with higher-rated MA at baseline were more likely to exert a stable course in MCI over 3 years (p = 0.036) when controlling for demographic characteristics and executive function. MLM analyses indicated that higher informant-rated MA at baseline were significantly related to higher cognitive abilities, even when controlling for MCI subtype (p = 0.030). CONCLUSIONS: This study provides preliminary longitudinal evidence for a lower risk of conversion to AD and higher cognitive abilities by higher rated MA at an early stage of MCI

    How does study quality affect the results of a diagnostic meta-analysis?

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    Background: The use of systematic literature review to inform evidence based practice in diagnostics is rapidly expanding. Although the primary diagnostic literature is extensive, studies are often of low methodological quality or poorly reported. There has been no rigorously evaluated, evidence based tool to assess the methodological quality of diagnostic studies. The primary objective of this study was to determine the extent to which variations in the quality of primary studies impact the results of a diagnostic meta-analysis and whether this differs with diagnostic test type. A secondary objective was to contribute to the evaluation of QUADAS, an evidence-based tool for the assessment of quality in diagnostic accuracy studies. Methods: This study was conducted as part of large systematic review of tests used in the diagnosis and further investigation of urinary tract infection (UTI) in children. All studies included in this review were assessed using QUADAS, an evidence-based tool for the assessment of quality in systematic reviews of diagnostic accuracy studies. The impact of individual components of QUADAS on a summary measure of diagnostic accuracy was investigated using regression analysis. The review divided the diagnosis and further investigation of UTI into the following three clinical stages: diagnosis of UTI, localisation of infection, and further investigation of the UTI. Each stage used different types of diagnostic test, which were considered to involve different quality concerns. Results: Many of the studies included in our review were poorly reported. The proportion of QUADAS items fulfilled was similar for studies in different sections of the review. However, as might be expected, the individual items fulfilled differed between the three clinical stages. Regression analysis found that different items showed a strong association with test performance for the different tests evaluated. These differences were observed both within and between the three clinical stages assessed by the review. The results of regression analyses were also affected by whether or not a weighting (by sample size) was applied. Our analysis was severely limited by the completeness of reporting and the differences between the index tests evaluated and the reference standards used to confirm diagnoses in the primary studies. Few tests were evaluated by sufficient studies to allow meaningful use of meta-analytic pooling and investigation of heterogeneity. This meant that further analysis to investigate heterogeneity could only be undertaken using a subset of studies, and that the findings are open to various interpretations. Conclusion: Further work is needed to investigate the influence of methodological quality on the results of diagnostic meta-analyses. Large data sets of well-reported primary studies are needed to address this question. Without significant improvements in the completeness of reporting of primary studies, progress in this area will be limited

    Multiway Array Decomposition Analysis of EEGs in Alzheimer’s Disease

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    Methods for the extraction of features from physiological datasets are growing needs as clinical investigations of Alzheimer’s disease (AD) in large and heterogeneous population increase. General tools allowing diagnostic regardless of recording sites, such as different hospitals, are essential and if combined to inexpensive non-invasive methods could critically improve mass screening of subjects with AD. In this study, we applied three state of the art multiway array decomposition (MAD) methods to extract features from electroencephalograms (EEGs) of AD patients obtained from multiple sites. In comparison to MAD, spectral-spatial average filter (SSFs) of control and AD subjects were used as well as a common blind source separation method, algorithm for multiple unknown signal extraction (AMUSE). We trained a feed-forward multilayer perceptron (MLP) to validate and optimize AD classification from two independent databases. Using a third EEG dataset, we demonstrated that features extracted from MAD outperformed features obtained from SSFs AMUSE in terms of root mean squared error (RMSE) and reaching up to 100% of accuracy in test condition. We propose that MAD maybe a useful tool to extract features for AD diagnosis offering great generalization across multi-site databases and opening doors to the discovery of new characterization of the disease
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