92 research outputs found

    Comparing the Identification of Recommendations by Different Accident Investigators Using a Common Methodology

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    Accident reports play a key role in the safety of complex systems. These reports present the recommendations that are intended to help avoid any recurrence of past failures. However, the value of these findings depends upon the causal analysis that helps to identify the reasons why an accident occurred. Various techniques have been developed to help investigators distinguish root causes from contributory factors and contextual information. This paper presents the results from a study into the individual differences that can arise when a group of investigators independently apply the same technique to identify the causes of an accident. This work is important if we are to increase the consistency and coherence of investigations following major accidents

    Influence of microsatellite instability and KRAS and BRAF mutations on lymph node harvest in stage I–III colon cancers

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    Lymph node (LN) harvest is influenced by several factors, including tumor genetics. Microsatellite instability (MSI) is associated with improved node harvest, but the association to other genetic factors is largely unknown. Research methods included a prospective series of stage I–III colon cancer patients undergoing ex vivo sentinel-node sampling. The presence of MSI, KRAS mutations in codons 12 and 13, and BRAF V600E mutations was analyzed. Uni- and multivariate regression models for node sampling were adjusted for clinical, pathological and molecular features. Of 204 patients, 67% had an adequate harvest (≥12 nodes). Adequate harvest was highest in patients whose tumors exhibited MSI (79%; odds ratio [OR] 2.5, 95% confidence interval [CI] 1.2–4.9; P = 0.007) or were located in the proximal colon (73%; 2.8, 1.5–5.3; P = 0.002). In multiple linear regression, MSI was a significant predictor of the total LN count (P = 0.02). Total node count was highest for cancers with MSI and no KRAS/BRAF mutations. The independent association between MSI and a high LN count persisted for stage I and II cancers (P = 0.04). Tumor location in the proximal colon was the only significant predictor of an adequate LN harvest (adjusted OR 2.4, 95% CI 1.2–4.9; P = 0.01). An increase in the total number of nodes harvested was not associated with an increase in nodal metastasis. In conclusion, number of nodes harvested is highest for cancers of the proximal colon and with MSI. The nodal harvest associated with MSI is influenced by BRAF and KRAS genotypes, even for cancers of proximal location. Mechanisms behind the molecular diversity and node yield should be further explored.publishedVersio

    Dynamic clamp with StdpC software

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    Dynamic clamp is a powerful method that allows the introduction of artificial electrical components into target cells to simulate ionic conductances and synaptic inputs. This method is based on a fast cycle of measuring the membrane potential of a cell, calculating the current of a desired simulated component using an appropriate model and injecting this current into the cell. Here we present a dynamic clamp protocol using free, fully integrated, open-source software (StdpC, for spike timing-dependent plasticity clamp). Use of this protocol does not require specialist hardware, costly commercial software, experience in real-time operating systems or a strong programming background. The software enables the configuration and operation of a wide range of complex and fully automated dynamic clamp experiments through an intuitive and powerful interface with a minimal initial lead time of a few hours. After initial configuration, experimental results can be generated within minutes of establishing cell recording

    The Generic Short Patient Experiences Questionnaire (GS-PEQ): identification of core items from a survey in Norway

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    <p>Abstract</p> <p>Background</p> <p>Questionnaires are commonly used to collect patient, or user, experiences with health care encounters; however, their adaption to specific target groups limits comparison between groups. We present the construction of a generic questionnaire (maximum of ten questions) for user evaluation across a range of health care services.</p> <p>Methods</p> <p>Based on previous testing of six group-specific questionnaires, we first constructed a generic questionnaire with 23 items related to user experiences. All questions included a "not applicable" response option, as well as a follow-up question about the item's importance. Nine user groups from one health trust were surveyed. Seven groups received questionnaires by mail and two by personal distribution. Selection of core questions was based on three criteria: applicability (proportion "not applicable"), importance (mean scores on follow-up questions), and comprehensiveness (content coverage, maximum two items per dimension).</p> <p>Results</p> <p>1324 questionnaires were returned providing subsample sizes ranging from 52 to 323. Ten questions were excluded because the proportion of "not applicable" responses exceeded 20% in at least one user group. The number of remaining items was reduced to ten by applying the two other criteria. The final short questionnaire included items on outcome (2), clinician services (2), user involvement (2), incorrect treatment (1), information (1), organisation (1), and accessibility (1).</p> <p>Conclusion</p> <p>The Generic Short Patient Experiences Questionnaire (GS-PEQ) is a short, generic set of questions on user experiences with specialist health care that covers important topics for a range of groups. It can be used alone or with other instruments in quality assessment or in research. The psychometric properties and the relevance of the GS-PEQ in other health care settings and countries need further evaluation.</p

    Longitudinal resting-state network connectivity changes in electroconvulsive therapy patients compared to healthy controls

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    Objective: Electroconvulsive therapy (ECT) is effective for major depressive episodes. Understanding of underlying mechanisms has been increased by examining changes of brain connectivity but studies often do not correct for test-retest variability in healthy controls (HC). In this study, we investigated changes in resting-state networks after ECT in a multicenter study. Methods: Functional resting-state magnetic resonance imaging data, acquired before start and within one week after ECT, from 90 depressed patients were analyzed, as well as longitudinal data of 24 HC. Group-information guided independent component analysis (GIG-ICA) was used to spatially restrict decomposition to twelve canonical resting-state networks. Selected networks of interest were the default mode network (DMN), salience network (SN), and left and right frontoparietal network (LFPN, and RFPN). Whole-brain voxel-wise analyses were used to assess group differences at baseline, group by time interactions, and correlations with treatment effectiveness. In addition, between-network connectivity and within-network strengths were computed. Results: Within-network strength of the DMN was lower at baseline in ECT patients which increased after ECT compared to HC, after which no differences were detected. At baseline, ECT patients showed lower whole-brain voxel-wise DMN connectivity in the precuneus. Increase of within-network strength of the LFPN was correlated with treatment effectiveness. We did not find whole-brain voxel-wise or between-network changes. Conclusion: DMN within-network connectivity normalized after ECT. Within-network increase of the LFPN in ECT patients was correlated with higher treatment effectiveness. In contrast to earlier studies, we found no whole-brain voxel-wise changes, which highlights the necessity to account for test-retest effects.</p

    Effective resting-state connectivity in severe unipolar depression before and after electroconvulsive therapy

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    Background Electroconvulsive therapy (ECT) is one of the most effective treatments for severe depressive disorders. A recent multi-center study found no consistent changes in correlation-based (undirected) resting-state connectivity after ECT. Effective (directed) connectivity may provide more insight into the working mechanism of ECT. Objective We investigated whether there are consistent changes in effective resting-state connectivity. Methods This multi-center study included data from 189 patients suffering from severe unipolar depression and 59 healthy control participants. Longitudinal data were available for 81 patients and 24 healthy controls. We used dynamic causal modeling for resting-state functional magnetic resonance imaging to determine effective connectivity in the default mode, salience and central executive networks before and after a course of ECT. Bayesian general linear models were used to examine differences in baseline and longitudinal effective connectivity effects associated with ECT and its effectiveness. Results Compared to controls, depressed patients showed many differences in effective connectivity at baseline, which varied according to the presence of psychotic features and later treatment outcome. Additionally, effective connectivity changed after ECT, which was related to ECT effectiveness. Notably, treatment effectiveness was associated with decreasing and increasing effective connectivity from the posterior default mode network to the left and right insula, respectively. No effects were found using correlation-based (undirected) connectivity. Conclusions A beneficial response to ECT may depend on how brain regions influence each other in networks important for emotion and cognition. These findings further elucidate the working mechanisms of ECT and may provide directions for future non-invasive brain stimulation research.publishedVersio

    The Global ECT-MRI Research Collaboration (GEMRIC): Establishing a multi-site investigation of the neural mechanisms underlying response to electroconvulsive therapy.

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    Major depression, currently the world's primary cause of disability, leads to profound personal suffering and increased risk of suicide. Unfortunately, the success of antidepressant treatment varies amongst individuals and can take weeks to months in those who respond. Electroconvulsive therapy (ECT), generally prescribed for the most severely depressed and when standard treatments fail, produces a more rapid response and remains the most effective intervention for severe depression. Exploring the neurobiological effects of ECT is thus an ideal approach to better understand the mechanisms of successful therapeutic response. Though several recent neuroimaging studies show structural and functional changes associated with ECT, not all brain changes associate with clinical outcome. Larger studies that can address individual differences in clinical and treatment parameters may better target biological factors relating to or predictive of ECT-related therapeutic response. We have thus formed the Global ECT-MRI Research Collaboration (GEMRIC) that aims to combine longitudinal neuroimaging as well as clinical, behavioral and other physiological data across multiple independent sites. Here, we summarize the ECT sample characteristics from currently participating sites, and the common data-repository and standardized image analysis pipeline developed for this initiative. This includes data harmonization across sites and MRI platforms, and a method for obtaining unbiased estimates of structural change based on longitudinal measurements with serial MRI scans. The optimized analysis pipeline, together with the large and heterogeneous combined GEMRIC dataset, will provide new opportunities to elucidate the mechanisms of ECT response and the factors mediating and predictive of clinical outcomes, which may ultimately lead to more effective personalized treatment approaches
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