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Microbes without frontiers: severe haemolytic-uraemic syndrome due to E coli O104:H4.
Antibiotic use in infection with Shiga-toxin-producing strains of Escherichia coli (E coli) is thought to increase the risk of developing haemolytic-uraemic syndrome (HUS). One paediatric study concluded that E coli O157:H7-infected patients who had received antibiotic therapy were 17 times more likely to progress to HUS than those who had not. Quinolones are among those incriminated. In vitro experiments suggest toxin induction of 80-fold with ciprofloxacin and E coli O104:H4. We report here the case of a 44-year-old man returning from Hamburg who presented with a 5 day history of bloody diarrhoea which had worsened after starting ciprofloxacin. A severe illness of overlapping HUS and thrombotic thrombocytopaenic purpura (TTP) ensued, with neurological complications requiring ventilation and intensive care admission. Stool sample eventually confirmed E coli O104:H4. Although the patient made a good recovery following treatment with haemofiltration and plasma exchange with fresh frozen plasma (FFP), ciprofloxacin may have exacerbated his clinical course.
Risk Factors, Epidemiology and Treatment Strategies for Metabolic Bone Disease in Patients with Neurological Disease.
Metabolic bone disease is a major public health concern, especially when it manifests as hip fracture which carries significant morbidity and mortality. Individuals with neurological disease are at higher risk of osteopenia, osteoporosis and fragility fracture compared to age-matched controls, yet this is under-appreciated by these patients. Clinician attention to this topic is therefore of importance and should address the bone health of men as well as women, a group in whom it may be an under-recognised problem. Evidence for optimal management of bone health in neurological disease remains to be defined, but a growing literature provides some useful guidance. This review focuses on two conditions, multiple sclerosis and Parkinson's disease, where research has been active over recent years. In neuroinflammation, shared immunological pathways between bone and brain are a current domain of interest and it will be intriguing to interrogate the action of emerging immunotherapies on these dual compartments.
Abolition of lifelong specific phobia: a novel therapeutic consequence of left mesial temporal lobectomy.
Numerous imaging studies have confirmed the amygdala as prominent within a neural network mediating specific phobia, including arachnophobia. We report the case of a patient in whom arachnophobia was abolished after left temporal mesial lobectomy, with unchanged fear responses to other stimuli. The phenomenon of abolition of specific phobia after amygdala removal has not, to our knowledge, been previously reported.
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.