40 research outputs found

    Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

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    Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease

    Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

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    Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

    Cancer drugs with high repositioning potential for Alzheimer\u27s disease

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    INTRODUCTION: Despite the recent full FDA approval of lecanemab, there is currently no disease modifying therapy (DMT) that can efficiently slow down the progression of Alzheimer\u27s disease (AD) in the general population. This statement emphasizes the need to identify novel DMTs in the shortest time possible to prevent a global epidemic of AD cases as the world population experiences an increase in lifespan. AREAS COVERED: Here, we review several classes of anti-cancer drugs that have been or are being investigated in Phase II/III clinical trials for AD, including immunomodulatory drugs, RXR agonists, sex hormone therapies, tyrosine kinase inhibitors, and monoclonal antibodies. EXPERT OPINION: Given the overall course of brain pathologies during the progression of AD, we express a great enthusiasm for the repositioning of anti-cancer drugs as possible AD DMTs. We anticipate an increasing number of combinatorial therapy strategies to tackle AD symptoms and their underlying pathologies. However, we strongly encourage improvements in clinical trial study designs to better assess target engagement and possible efficacy over sufficient periods of drug exposure

    Does Shared Decision Making Actually Occur in the Emergency Department? Looking at It from the Patients’ Perspective

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    ObjectiveWe sought to assess the frequency, content, and quality of shared decision making (SDM) in the emergency department (ED), from patients' perspectives.MethodsUtilizing a cross-sectional, multisite approach, we administered an instrument, consisting of two validated SDM assessment tools-the CollaboRATE and the SDM-Q-9-and one newly developed tool to a sample of ED patients. Our primary outcome was the occurrence of SDM in the clinical encounter, as defined by participants giving "top-box" scores on the CollaboRATE measure, and the ability of patients to identify the topic of their SDM conversation. Secondary outcomes included the content of the SDM conversations, as judged by patients, and whether patients were able to complete each of the two validated scales included in the instrument.ResultsAfter exclusions, 285 participants from two sites completed the composite instrument. Just under half identified as female (47%) or as white (47%). Roughly half gave top-box scores (i.e., indicating optimal SDM) on the CollaboRATE scale (49%). Less than half of the participants were able to indicate a decision they were involved in (44%), although those who did gave high scores for such conversations (73/100 via the SDM-Q-9 tool). The most frequently identified decisions discussed were admission versus discharge (19%), medication options (17%), and options for follow-up care (15%).ConclusionsFewer than half of ED patients surveyed reported they were involved in SDM. The most common decision for which SDM was used was around ED disposition (admission vs. discharge). When SDM was employed, patients generally rated the discussion highly
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