Search results
Found 21086 matches for
Stroke: management and prevention
Acute stroke treatment requires clear protocols to rapidly triage patients – using appropriate investigations – for mechanical thrombectomy and intravenous thrombolysis. Computed tomography (CT) excludes haemorrhage, CT angiography locates the occluded vessel, and CT perfusion and perfusion magnetic resonance imaging identify viable tissue. An organized approach to stroke care in a specialist environment reduces disability and saves lives. Adoption of a ‘care bundle’ approach, including the active management of pyrexia and hyperglycaemia, and early screening for swallowing difficulties, is beneficial. Tailored secondary prevention, including assessment of the carotid arteries, is urgent as, for eligible patients, carotid endarterectomy should be done within two weeks. Anticoagulation in elderly individuals with atrial fibrillation is safer than is often assumed, and direct oral anticoagulants have changed the landscape of secondary prevention.
Cognitive decline and diabetes: a systematic review of the neuropathological correlates accounting for cognition at death
Given conflicting findings in epidemiologic studies, we determined the relative contributions of different neuropathologies to the excess risk of cognitive decline in diabetes mellitus (DM) through a systematic review of the literature. Included studies compared subjects with and without DM and reported neuropathological outcomes accounting for cognition at death. Data on Alzheimer’s disease (AD) pathology, cerebrovascular disease and non-vascular, non-AD pathology were extracted from each study. Eleven studies (n=6 prospective cohorts, n=5 retrospective post-mortem series, total n=6330) met inclusion criteria. All 11 studies quantified AD changes and 10/11 measured cerebrovascular disease: macroscopic lesions (n=9), microinfarcts (n=8), cerebral amyloid angiopathy (CAA, n=7), lacunes (n=6), white matter disease (n=5), haemorrhages (n=4), microbleeds (n=1), hippocampal microvasculature (n=1). Other pathology was infrequently examined. No study reported increased AD pathology in DM, three studies showed a decrease (n=872) and four (n= 4018) showed no difference, after adjustment for cognition at death. No study reported reduced cerebrovascular pathology in DM. Three studies (n=2345) reported an increase in large infarcts, lacunes and microinfarcts. One study found lower cognitive scores in DM compared to non-DM subjects despite similar cerebrovascular and AD-pathology load suggesting contributions from other neuropathological processes. In conclusion, lack of an association between DM and AD-related neuropathology was consistent across studies, irrespective of methodology. In contrast to AD, DM was associated with increased large and small vessel disease. Data on other pathologies such as non-AD neurodegeneration, and blood-brain-barrier breakdown were lacking. Further studies evaluating relative contributions of different neuropathologies to the excess risk of DM are needed.
Regional contribution of vascular dysfunction in white matter dementia: clinical and neuropathological insights.
The maintenance of adequate blood supply and vascular integrity is fundamental to ensure cerebral function. A wide range of studies report vascular dysfunction in white matter dementias, a group of cerebral disorders characterized by substantial white matter damage in the brain leading to cognitive impairment. Despite recent advances in imaging, the contribution of vascular-specific regional alterations in white matter dementia has been not extensively reviewed. First, we present an overview of the main components of the vascular system involved in the maintenance of brain function, modulation of cerebral blood flow and integrity of the blood-brain barrier in the healthy brain and during aging. Second, we review the regional contribution of cerebral blood flow and blood-brain barrier disturbances in the pathogenesis of three distinct conditions: the archetypal white matter predominant neurocognitive dementia that is vascular dementia, a neuroinflammatory predominant disease (multiple sclerosis) and a neurodegenerative predominant disease (Alzheimer's). Finally, we then examine the shared landscape of vascular dysfunction in white matter dementia. By emphasizing the involvement of vascular dysfunction in the white matter, we put forward a hypothetical map of vascular dysfunction during disease-specific progression to guide future research aimed to improve diagnostics and facilitate the development of tailored therapies.
The German version of the Oxford Cognitive Screen (D-OCS): Normative data and validation in acute stroke and a mixed neurological sample.
Given the frequency of stroke worldwide, tools for neuropsychological assessment of patients with acute stroke are needed to identify cognitive impairments, guide rehabilitation efforts and allow for a prognosis of outcome. However, requirements for assessment tools for acute cognitive deficits differ substantially from tests for chronic neuropsychological impairments and screening tools for suspected dementia. The Oxford Cognitive Screen (OCS) has been developed as a quick to administer neurocognitive screening for acute neurological patients providing information on various cognitive domains. It is available in different languages. The present study reports cut-off scores, parallel-test reliability and concurrent validity of the German version (D-OCS). Following standardized language adaptation and translation, the D-OCS was administered to 100 healthy individuals to generate cut-off scores (5th percentile). Subsequently, 88 neurological patients were assessed with both versions of the D-OCS as well as other tests to evaluate reliability and validity of the D-OCS subscales. In a further study, the D-OCS was compared to the MoCA test in 65 acute stroke patients revealing comparable sensitivity but also differences between both tools. The cut-off scores were comparable to other international versions of the OCS. Intraclass correlations were highly significant and document reliability of the D-OCS subtests. Scores on subtests correlated significantly with independent tests securing validity. Comparison with the MoCA revealed comparable sensitivity and specificity. The D-OCS is a reliable and valid assessment tool well suited for patients with acute stroke. Differences to the MoCA test are discussed.
Acoustic and Language Based Deep Learning Approaches for Alzheimer's Dementia Detection From Spontaneous Speech
Current methods for early diagnosis of Alzheimer's Dementia include structured questionnaires, structured interviews, and various cognitive tests. Language difficulties are a major problem in dementia as linguistic skills break down. Current methods do not provide robust tools to capture the true nature of language deficits in spontaneous speech. Early detection of Alzheimer's Dementia (AD) from spontaneous speech overcomes the limitations of earlier approaches as it is less time consuming, can be done at home, and is relatively inexpensive. In this work, we re-implement the existing NLP methods, which used CNN-LSTM architectures and targeted features from conversational transcripts. Our work sheds light on why the accuracy of these models drops to 72.92% on the ADReSS dataset, whereas, they gave state of the art results on the DementiaBank dataset. Further, we build upon these language input-based recurrent neural networks by devising an end-to-end deep learning-based solution that performs a binary classification of Alzheimer's Dementia from the spontaneous speech of the patients. We utilize the ADReSS dataset for all our implementations and explore the deep learning-based methods of combining acoustic features into a common vector using recurrent units. Our approach of combining acoustic features using the Speech-GRU improves the accuracy by 2% in comparison to acoustic baselines. When further enriched by targeted features, the Speech-GRU performs better than acoustic baselines by 6.25%. We propose a bi-modal approach for AD classification and discuss the merits and opportunities of our approach.
Bayesian networks and imaging-derived phenotypes highlight the role of fat deposition in COVID-19 hospitalisation risk.
Objective: Obesity is a significant risk factor for adverse outcomes following coronavirus infection (COVID-19). However, BMI fails to capture differences in the body fat distribution, the critical driver of metabolic health. Conventional statistical methodologies lack functionality to investigate the causality between fat distribution and disease outcomes. Methods: We applied Bayesian network (BN) modelling to explore the mechanistic link between body fat deposition and hospitalisation risk in 459 participants with COVID-19 (395 non-hospitalised and 64 hospitalised). MRI-derived measures of visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and liver fat were included. Conditional probability queries were performed to estimate the probability of hospitalisation after fixing the value of specific network variables. Results: The probability of hospitalisation was 18% higher in people living with obesity than those with normal weight, with elevated VAT being the primary determinant of obesity-related risk. Across all BMI categories, elevated VAT and liver fat (>10%) were associated with a 39% mean increase in the probability of hospitalisation. Among those with normal weight, reducing liver fat content from >10% to <5% reduced hospitalisation risk by 29%. Conclusion: Body fat distribution is a critical determinant of COVID-19 hospitalisation risk. BN modelling and probabilistic inferences assist our understanding of the mechanistic associations between imaging-derived phenotypes and COVID-19 hospitalisation risk.