5 research outputs found

    Complementary pre-screening strategies to uncover hidden prodromal and mild Alzheimer's disease : Results from the MOPEAD project

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    The Models of Patient Engagement for Alzheimer's Disease (MOPEAD) project was conceived to explore innovative complementary strategies to uncover hidden prodromal and mild Alzheimer's disease (AD) dementia cases and to raise awareness both in the general public and among health professionals about the importance of early diagnosis. Four different strategies or RUNs were used: (a) a web-based (WB) prescreening tool, (2) an open house initiative (OHI), (3) a primary care-based protocol for early detection of cognitive decline (PC), and (4) a tertiary care-based pre-screening at diabetologist clinics (DC). A total of 1129 patients at high risk of having prodromal AD or dementia were identified of 2847 pre-screened individuals (39.7%). The corresponding proportion for the different initiatives were 36.8% (WB), 35.6% (OHI), 44.4% (PC), and 58.3% (DC). These four complementary pre-screening strategies were useful for identifying individuals at high risk of having prodromal or mild AD

    Complementary pre-screening strategies to uncover hidden prodromal and mild Alzheimer's disease : Results from the MOPEAD project

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    Introduction: The Models of Patient Engagement for Alzheimer's Disease (MOPEAD) project was conceived to explore innovative complementary strategies to uncover hidden prodromal and mild Alzheimer's disease (AD) dementia cases and to raise awareness both in the general public and among health professionals about the importance of early diagnosis. Methods: Four different strategies or RUNs were used: (a) a web-based (WB) prescreening tool, (2) an open house initiative (OHI), (3) a primary care–based protocol for early detection of cognitive decline (PC), and (4) a tertiary care–based pre-screening at diabetologist clinics (DC). Results: A total of 1129 patients at high risk of having prodromal AD or dementia were identified of 2847 pre-screened individuals (39.7%). The corresponding proportion for the different initiatives were 36.8% (WB), 35.6% (OHI), 44.4% (PC), and 58.3% (DC). Conclusion: These four complementary pre-screening strategies were useful for identifying individuals at high risk of having prodromal or mild AD

    Complementary pre-screening strategies to uncover hidden prodromal and mild Alzheimer's disease: Results from the MOPEAD project

    Get PDF
    Introduction: The Models of Patient Engagement for Alzheimer's Disease (MOPEAD) project was conceived to explore innovative complementary strategies to uncover hidden prodromal and mild Alzheimer's disease (AD) dementia cases and to raise awareness both in the general public and among health professionals about the importance of early diagnosis. Methods: Four different strategies or RUNs were used: (a) a web-based (WB) prescreening tool, (2) an open house initiative (OHI), (3) a primary care–based protocol for early detection of cognitive decline (PC), and (4) a tertiary care–based pre-screening at diabetologist clinics (DC). Results: A total of 1129 patients at high risk of having prodromal AD or dementia were identified of 2847 pre-screened individuals (39.7%). The corresponding proportion for the different initiatives were 36.8% (WB), 35.6% (OHI), 44.4% (PC), and 58.3% (DC). Conclusion: These four complementary pre-screening strategies were useful for identifying individuals at high risk of having prodromal or mild AD

    Complementary pre-screening strategies to uncover hidden prodromal and mild Alzheimer's disease: Results from the MOPEAD project

    Full text link
    Introduction The Models of Patient Engagement for Alzheimer's Disease (MOPEAD) project was conceived to explore innovative complementary strategies to uncover hidden prodromal and mild Alzheimer's disease (AD) dementia cases and to raise awareness both in the general public and among health professionals about the importance of early diagnosis. Methods Four different strategies or RUNs were used: (a) a web-based (WB) prescreening tool, (2) an open house initiative (OHI), (3) a primary care-based protocol for early detection of cognitive decline (PC), and (4) a tertiary care-based pre-screening at diabetologist clinics (DC). Results A total of 1129 patients at high risk of having prodromal AD or dementia were identified of 2847 pre-screened individuals (39.7%). The corresponding proportion for the different initiatives were 36.8% (WB), 35.6% (OHI), 44.4% (PC), and 58.3% (DC). Conclusion These four complementary pre-screening strategies were useful for identifying individuals at high risk of having prodromal or mild AD

    The MOPEAD project: Advancing patient engagement for the detection of hidden undiagnosed cases of Alzheimer's disease in the community

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    In most, if not all health systems, dementia is underdiagnosed, and when diagnosis occurs, it is typically at a relatively late stage in the disease process despite mounting evidence showing that a timely diagnosis would result in numerous benefits for patients, families, and society. Moving toward earlier diagnoses in Alzheimer's disease (AD) requires a conscientious and collective effort to implement a global strategy addressing the multiple causes hindering patient engagement at different levels of society. This article describes the design of the Models of Patient Engagement for Alzheimer's Disease project, an ongoing EU-funded public-private multinational initiative that will compare four innovative patient engagement strategies across five European countries regarding their ability to identify individuals with prodromal AD and mild AD dementia, which are hidden in their communities and traditionally not found in the typical memory clinic setting. The strategies include an online AD citizen science platform, an open house initiative at the memory clinics, and patient engagement at primary care and diabetologist clinics. (C) 2019 The Authors. Published by Elsevier Inc. on behalf of the Alzheimer's Association. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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