{ "items": [ "\n\n
Abstract\n\nBackground:\nDaydreaming may contribute to the maintenance of grandiose delusions. Repeated, pleasant and vivid daydreams about the content of grandiose delusions may keep the ideas in mind, elaborate the details, and increase the degree of conviction in the delusion. Pleasant daydreams more generally could contribute to elevated mood, which may influence the delusion content.\n\n\nAims:\nWe sought to develop a brief questionnaire, suitable for research and clinical practice, to assess daydreaming and test potential associations with grandiosity.\n\n\nMethod:\n798 patients with psychosis (375 with grandiose delusions) and 4518 non-clinical adults (1788 with high grandiosity) were recruited. Participants completed a daydreaming item pool and measures of grandiosity, time spent thinking about the grandiose belief, and grandiose belief conviction. Factor analysis was used to derive the Qualities of Daydreaming Scale (QuOD) and associations were tested using pairwise correlations and structural equation modelling.\n\n\nResults:\nThe questionnaire had three factors: realism, pleasantness, and frequency of daydreams. The measure was invariant across clinical and non-clinical groups. Internal consistency was good (alpha-ordinals: realism=0.86, pleasantness=0.93, frequency=0.82) as was test\u2013retest reliability (intra-class coefficient=0.75). Daydreaming scores were higher in patients with grandiose delusions than in patients without grandiose delusions or in the non-clinical group. Daydreaming was significantly associated with grandiosity, time spent thinking about the grandiose delusion, and grandiose delusion conviction, explaining 19.1, 7.7 and 5.2% of the variance in the clinical group data, respectively. Similar associations were found in the non-clinical group.\n\n\nConclusions:\nThe process of daydreaming may be one target in psychological interventions for grandiose delusions.\n
\n \n\n \n \nAbstract\nBackground\n\nTo improve the treatment of painful Diabetic Peripheral Neuropathy (DPN) and associated co-morbidities, a better understanding of the pathophysiology and risk factors for painful DPN is required. Using harmonised cohorts (N\u2009=\u20091230) we have built models that classify painful versus painless DPN using quality of life (EQ5D), lifestyle (smoking, alcohol consumption), demographics (age, gender), personality and psychology traits (anxiety, depression, personality traits), biochemical (HbA1c) and clinical variables (BMI, hospital stay and trauma at young age) as predictors.\n\nMethods\nThe Random Forest, Adaptive Regression Splines and Naive Bayes machine learning models were trained for classifying painful/painless DPN. Their performance was estimated using cross-validation in large cross-sectional cohorts (N\u2009=\u2009935) and externally validated in a large population-based cohort (N\u2009=\u2009295). Variables were ranked for importance using model specific metrics and marginal effects of predictors were aggregated and assessed at the global level. Model selection was carried out using the Mathews Correlation Coefficient (MCC) and model performance was quantified in the validation set using MCC, the area under the precision/recall curve (AUPRC) and accuracy.\n\nResults\nRandom Forest (MCC\u2009=\u20090.28, AUPRC\u2009=\u20090.76) and Adaptive Regression Splines (MCC\u2009=\u20090.29, AUPRC\u2009=\u20090.77) were the best performing models and showed the smallest reduction in performance between the training and validation dataset. EQ5D index, the 10-item personality dimensions, HbA1c, Depression and Anxiety t-scores, age and Body Mass Index were consistently amongst the most powerful predictors in classifying painful vs painless DPN.\n\nConclusions\nMachine learning models trained on large cross-sectional cohorts were able to accurately classify painful or painless DPN on an independent population-based dataset. Painful DPN is associated with more depression, anxiety and certain personality traits. It is also associated with poorer self-reported quality of life, younger age, poor glucose control and high Body Mass Index (BMI). The models showed good performance in realistic conditions in the presence of missing values and noisy datasets. These models can be used either in the clinical context to assist patient stratification based on the risk of painful DPN or return broad risk categories based on user input. Model\u2019s performance and calibration suggest that in both cases they could potentially improve diagnosis and outcomes by changing modifiable factors like BMI and HbA1c control and institute earlier preventive or supportive measures like psychological interventions.\n
\n \n\n \n \nThis chapter introduces the topic of error as an essential foundation for an understanding of patient safety. We introduce psychological classifications of error and then, using clinical examples, show how we can use these ideas to understand how errors occur and how chains of small errors can combine to cause harm to patients. We outline a practical approach to conducting investigations into healthcare incidents. Finally, we offer some reflections on how doctors experience errors and how best to support yourself or your colleagues when things do not go as well as intended.
\n \n\n \n \nPURPOSE: The delay alternating with nutation for tailored excitation (DANTE)-sampling perfection with application-optimized contrasts (SPACE) sequence facilitates 3D intracranial vessel wall imaging with simultaneous suppression of blood and CSF. However, the achieved image contrast depends closely on the selected sequence parameters, and the clinical use of the sequence is limited in vivo by observed signal variations in the vessel wall, CSF, and blood. This paper introduces a comprehensive DANTE-SPACE simulation framework, with the aim of providing a better understanding of the underlying contrast mechanisms and facilitating improved parameter selection and contrast optimization. METHODS: An extended phase graph formalism was developed for efficient spin ensemble simulation of the DANTE-SPACE sequence. Physiological processes such as pulsatile flow velocity variation, varying flow directions, intravoxel velocity variation, diffusion, and B 1 + $$ {\\mathrm{B}}_1^{+} $$ effects were included in the framework to represent the mechanisms behind the achieved signal levels accurately. RESULTS: Intravoxel velocity variation improved temporal stability and robustness against small velocity changes. Time-varying pulsatile velocity variation affected CSF simulations, introducing periods of near-zero velocity and partial rephasing. Inclusion of diffusion effects was found to substantially reduce the CSF signal. Blood flow trajectory variations had minor effects, but B 1 + $$ {\\mathrm{B}}_1^{+} $$ differences along the trajectory reduced DANTE efficiency in low- B 1 + $$ {\\mathrm{B}}_1^{+} $$ areas. Introducing low-velocity pulsatility of both CSF and vessel wall helped explain the in vivo observed signal heterogeneity in both tissue types. CONCLUSION: The presented simulation framework facilitates a more comprehensive optimization of DANTE-SPACE sequence parameters. Furthermore, the simulation framework helps to explain observed contrasts in acquired data.
\n \n\n \n \nNeuroimaging involves the acquisition of extensive 3D images and 4D time series data to gain insights into brain structure and function. The analysis of such data necessitates both spatial and temporal processing. In this context, \u201cfslmaths\u201d has established itself as a foundational software tool within our field, facilitating domain-specific image processing. Here, we introduce \u201cniimath,\u201d a clone of fslmaths. While the term \u201cclone\u201d often carries negative connotations, we illustrate the merits of replicating widely-used tools, touching on aspects of licensing, performance optimization, and portability. For instance, our work enables the popular functions of fslmaths to be disseminated in various forms, such as a high-performance compiled R package known as \u201cimbibe\u201d, a Windows executable, and a WebAssembly plugin compatible with JavaScript. This versatility is demonstrated through our NiiVue live demo web page. This application allows \u2018edge computing\u2019 where image processing can be done with a zero-footprint tool that runs on any web device without requiring private data to be shared to the cloud. Furthermore, our efforts have contributed back to FSL, which has integrated the optimizations that we\u2019ve developed. This synergy has enhanced the overall transparency, utility and efficiency of tools widely relied upon in the neuroimaging community.
\n \n\n \n \nAbstract\nWe present MMORF\u2014FSL\u2019s MultiMOdal Registration Framework\u2014a newly released nonlinear image registration tool designed primarily for application to magnetic resonance imaging (MRI) images of the brain. MMORF is capable of simultaneously optimising both displacement and rotational transformations within a single registration framework by leveraging rich information from multiple scalar and tensor modalities. The regularisation employed in MMORF promotes local rigidity in the deformation, and we have previously demonstrated how this effectively controls both shape and size distortion, leading to more biologically plausible warps. The performance of MMORF is benchmarked against three established nonlinear registration methods\u2014FNIRT, ANTs, and DR-TAMAS\u2014across four domains: FreeSurfer label overlap, diffusion tensor imaging (DTI) similarity, task-fMRI cluster mass, and distortion. The evaluation is based on 100 unrelated subjects from the Human Connectome Project (HCP) dataset registered to the Oxford-MultiModal-1 (OMM-1) multimodal template via either the T1w contrast alone or in combination with a DTI/DTI-derived contrast. Results show that MMORF is the most consistently high-performing method across all domains\u2014both in terms of accuracy and levels of distortion. MMORF is available as part of FSL, and its inputs and outputs are fully compatible with existing workflows. We believe that MMORF will be a valuable tool for the neuroimaging community, regardless of the domain of any downstream analysis, providing state-of-the-art registration performance that integrates into the rich and widely adopted suite of analysis tools in FSL.
\n \n\n \n \nBACKGROUND: The Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) total score is a widely used measure of functional status in Amyotrophic Lateral Sclerosis/Motor Neuron Disease (ALS), but recent evidence has raised doubts about its validity. The objective was to examine the measurement properties of the ALSFRS-R, aiming to produce valid measurement from all 12 scale items. METHOD: Longitudinal ALSFRS-R data were collected between 2013-2020 from 1120 people with ALS recruited from 35 centers, together with other scales in the Trajectories of Outcomes in Neurological Conditions-ALS (TONiC-ALS) study. The ALSFRS-R was analyzed by confirmatory factor analysis (CFA), Rasch Analysis (RA) and Mokken scaling. RESULTS: No definite factor structure of the ALSFRS-R was confirmed by CFA. RA revealed the raw score total to be invalid even at the ordinal level because of multidimensionality; valid interval level subscale measures could be found for the Bulbar, Fine-Motor and Gross-Motor domains but the Respiratory domain was only valid at an ordinal level. All four domains resolved into a single valid, interval level measure by using a bifactor RA. The smallest detectable difference was 10.4% of the range of the interval scale. CONCLUSION: A total ALSFRS-R ordinal raw score can lead to inferential bias in clinical trial results due to its non-linear nature. On the interval level transformation, more than 5 points difference is required before a statistically significant detectable difference can be observed. Transformation to interval level data should be mandatory in clinical trials.
\n \n\n \n \nTime-of-day significantly influences the severity and incidence of stroke. Evidence has emerged not only for circadian governance over stroke risk factors, but also for important determinants of clinical outcome. In this review, we provide a comprehensive overview of the interplay between chronobiology and cerebrovascular disease. We discuss circadian regulation of pathophysiological mechanisms underlying stroke onset or tolerance as well as in vascular dementia. This includes cell death mechanisms, metabolism, mitochondrial function, and inflammation/immunity. Furthermore, we present clinical evidence supporting the link between disrupted circadian rhythms and increased susceptibility to stroke and dementia. We propose that circadian regulation of biochemical and physiological pathways in the brain increase susceptibility to damage after stroke in sleep and attenuate treatment effectiveness during the active phase. This review underscores the importance of considering circadian biology for understanding the pathology and treatment choice for stroke and vascular dementia and speculates that considering a patient\u2019s chronotype may be an important factor in developing precision treatment following stroke.
\n \n\n \n \nBACKGROUND: Regional anaesthesia use is growing worldwide, and there is an increasing emphasis on research in regional anaesthesia to improve patient outcomes. However, priorities for future study remain unclear. We therefore conducted an international research prioritisation exercise, setting the agenda for future investigators and funding bodies. METHODS: We invited members of specialist regional anaesthesia societies from six continents to propose research questions that they felt were unanswered. These were consolidated into representative indicative questions, and a literature review was undertaken to determine if any indicative questions were already answered by published work. Unanswered indicative questions entered a three-round modified Delphi process, whereby 29 experts in regional anaesthesia (representing all participating specialist societies) rated each indicative question for inclusion on a final high priority shortlist. If \u226575% of participants rated an indicative question as 'definitely' include in any round, it was accepted. Indicative questions rated as 'definitely' or 'probably' by <50% of participants in any round were excluded. Retained indicative questions were further ranked based on the rating score in the final Delphi round. The final research priorities were ratified by the Delphi expert group. RESULTS: There were 1318 responses from 516 people in the initial survey, from which 71 indicative questions were formed, of which 68 entered the modified Delphi process. Eleven 'highest priority' research questions were short listed, covering themes of pain management; training and assessment; clinical practice and efficacy; technology and equipment. CONCLUSIONS: We prioritised unanswered research questions in regional anaesthesia. These will inform a coordinated global research strategy for regional anaesthesia and direct investigators to address high-priority areas.
\n \n\n \n \nRotenone (RT) produces reactive oxygen species (ROS) by inhibiting the mitochondrial electron transport chain; causing dopaminergic (DA) cell death in the substantia nigra (SN) and simulates other models of induced Parkinson's disease (PD). There is a sincere dearth of knowledge regarding the status of glial cells, neuroprotective estrogen and the status of neuroinflammatory TNF-\u03b1 in the different brain regions in either sex during healthy, as well as during PD conditions. In the present study of RT-induced mouse model of PD, we have selected the frontal cortex (FC), hippocampus (HC) and SN from either sex of Swiss albino mice as these are the major regions involved during PD pathogenesis.During non pathogenic conditions, the ROS-scavenging enzyme activity varied among the brain regions and also in between genders. The number of DOPA decarboxylase-positive cells, astrocytes and microglia was similar in the respective regions of the brain in both the sexes. The level of proinflammatory cytokine TNF-\u03b1 was same in the respective FC and HC in either sex except that of SN. The expression level of estrogen and its receptors varied among the three brain regions. During RT treatment, ROS-scavenging enzyme activities increased, DOPA decarboxylase-positive neurons and fibers in DA as well as in norepinephrinergic (NE) systems become degenerated, number of astrocytes decreased and microglial cells increased in those specific brain regions in either of the sexes except in the SN region of males where astrocyte number remained unaltered and microglial cell percentage decreased. TNF-\u03b1 increased in the FC and SN but remained unaltered in the HC of both sexes. Estradiol level decreased in the HC and SN but the level unevenly varied in the FC. Similarly, the estrogen bound and nuclear-cytosolic receptor \u03b1 and \u03b2 also varied differentially among the brain regions of the two sexes.Therefore our present study depicts that there exists a clear variation of neuronal and astroglial cell population, estrogen and its receptor levels in different brain regions of both the sexes during control and RT-treated pathogenic condition and these variations have major implication in PD pathogenesis and progression.
\n \n\n \n \nObjectivesThe British Association of Spinal Surgeons recently called for updates in consenting practice. This study investigates the utility and acceptability of a personalised video consent tool to enhance patient satisfaction in the preoperative consent giving process.DesignA single-centre, prospective pilot study using questionnaires to assess acceptability of video consent and its impacts on preoperative patient satisfaction.SettingA single National Health Service centre with individuals undergoing surgery at a regional spinal centre in the UK.Outcome measureAs part of preoperative planning, study participants completed a self-administered questionnaire (CSQ-8), which measured their satisfaction with the use of a video consent tool as an adjunct to traditional consenting methods.Participants20 participants with a mean age of 56 years (SD=16.26) undergoing spinal surgery.ResultsMean patient satisfaction (CSQ-8) score was 30.2/32. Median number of video views were 2\u20133 times. Eighty-five per cent of patients watched the video with family and friends. Eighty per cent of participants reported that the video consent tool helped to their address preoperative concerns. All participants stated they would use the video consent service again. All would recommend the service to others requiring surgery. Implementing the video consent tool did not endure any significant time or costs.ConclusionsIntroduction of a video consent tool was found to be a positive adjunct to traditional consenting methods. Patient\u2013clinician consent dialogue can now be documented. A randomised controlled study to further evaluate the effects of video consent on patients\u2019 retention of information, preoperative and postoperative anxiety, patient reported outcome measures as well as length of stay may be beneficial.
\n \n\n \n \nPrevious work has shown that motor skill learning stimulates and requires generation of myelinating oligodendrocytes (OLs) from their precursor cells (OLPs) in the brains of adult mice. In the present study we ask whether OL production is also required for non-motor learning and cognition, using T-maze and radial-arm-maze tasks that tax spatial working memory. We find that maze training stimulates OLP proliferation and OL production in the medial prefrontal cortex (mPFC), anterior corpus callosum (genu), dorsal thalamus and hippocampal formation of adult male mice; myelin sheath formation is also stimulated in the genu. Genetic blockade of OL differentiation and neo-myelination in Myrf conditional-knockout mice strongly impairs training-induced improvements in maze performance. We find a strong positive correlation between the performance of individual wild type mice and the scale of OLP proliferation and OL generation during training, but not with the number or intensity of c-Fos+ neurons in their mPFC, underscoring the important role played by OL lineage cells in cognitive processing.
\n \n\n \n \nIntroductionThere is growing evidence that sleep is disrupted after stroke, with worse sleep relating to poorer motor outcomes. It is also widely acknowledged that consolidation of motor learning, a critical component of poststroke recovery, is sleep-dependent. However, whether the relationship between disrupted sleep and poor outcomes after stroke is related to direct interference of sleep-dependent motor consolidation processes, is currently unknown. Therefore, the aim of the present study is to understand whether measures of motor consolidation mediate the relationship between sleep and clinical motor outcomes post stroke.Methods and analysisWe will conduct a longitudinal observational study of up to 150 participants diagnosed with stroke affecting the upper limb. Participants will be recruited and assessed within 7\u2009days of their stroke and followed up at approximately 1 and 6 months. The primary objective of the study is to determine whether sleep in the subacute phase of recovery explains the variability in upper limb motor outcomes after stroke (over and above predicted recovery potential from the Predict Recovery Potential algorithm) and whether this relationship is dependent on consolidation of motor learning. We will also test whether motor consolidation mediates the relationship between sleep and whole-body clinical motor outcomes, whether motor consolidation is associated with specific electrophysiological sleep signals and sleep alterations during subacute recovery.Ethics and disseminationThis trial has received both Health Research Authority, Health and Care Research Wales and National Research Ethics Service approval (IRAS: 304135; REC: 22/LO/0353). The results of this trial will help to enhance our understanding of the role of sleep in recovery of motor function after stroke and will be disseminated via presentations at scientific conferences, peer-reviewed publication, public engagement events, stakeholder organisations and other forms of media where appropriate.Trial registration numberClinicalTrials.gov:NCT05746260, registered on 27 February 2023.
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