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    Background and Objective Current studies of end-of-life care in Parkinson disease (PD) do not focus on diverse patient samples or provide national views of end-of-life resource utilization. We determined sociodemographic and geographic differences in end-of-life inpatient care intensity among persons with PD in the United States (US). Methods This retrospective cohort study included Medicare Part A and Part B beneficiaries 65 years and older with a qualifying PD diagnosis who died between January 1, 2017, and December 31, 2017. Medicare Advantage beneficiaries and those with atypical or secondary parkinsonism were excluded. Primary outcomes included rates of hospitalization, intensive care unit (ICU) admission, in-hospital death, and hospice discharge in the last 6 months of life. Descriptive analyses and multivariable logistic regression models compared differences in end-of-life resource utilization and treatment intensity. Adjusted models included demographic and geographic variable

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    • This retrospective cohort study determined sociodemographic and geographic differences in end-of-life inpatient care intensity among persons with #ParkinsonDisease in the United States: https://t.co/Ij8yKdfEn4 #NeuroTwitter https://t.co/Cvz3wowICe

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    Home > Dementia > Playing Football Increases Risk of Developing Parkinson Disease Playing American football is linked with a higher risk of developing Parkinson disease (PD), according to a study published in JAMA Network Open. Identifying risk factors for PD is critical for early detection and diagnosis. One such risk factor is traumatic brain injury, as observed in both nonhuman models and autopsies. The exposure to repetitive head impact related to playing American football has been associated with

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    • Playing American football is linked with a higher risk of developing Parkinson disease (PD), according to a recent study published in JAMA Network Open. https://t.co/3949uCQAre #football #NFL #Parkinsondisease #Americanfootball #CTE https://t.co/4F9R1pfJ10

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    Background and Objective Current studies of end-of-life care in Parkinson disease (PD) do not focus on diverse patient samples or provide national views of end-of-life resource utilization. We determined sociodemographic and geographic differences in end-of-life inpatient care intensity among persons with PD in the United States (US). Methods This retrospective cohort study included Medicare Part A and Part B beneficiaries 65 years and older with a qualifying PD diagnosis who died between January 1, 2017, and December 31, 2017. Medicare Advantage beneficiaries and those with atypical or secondary parkinsonism were excluded. Primary outcomes included rates of hospitalization, intensive care unit (ICU) admission, in-hospital death, and hospice discharge in the last 6 months of life. Descriptive analyses and multivariable logistic regression models compared differences in end-of-life resource utilization and treatment intensity. Adjusted models included demographic and geographic variable

    Tweet Tweets with this article
    • This retrospective cohort study determined sociodemographic and geographic differences in end-of-life inpatient care intensity among persons with #ParkinsonDisease in the United States: https://t.co/Ij8yKdfEn4 #NeuroTwitter https://t.co/0cqOQrsLGP

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    Background and Objectives Parkinson disease (PD) and progressive supranuclear palsy (PSP) are often difficult to differentiate in the clinic. The MR parkinsonism index (MRPI) has been recommended to assist in making this distinction. We aimed to assess the usefulness of this tool in our real-world practice of movement disorders. Methods We prospectively obtained MRI scans on consecutive patients with movement disorders with a clinical indication for imaging and obtained measures of MRI regions of interest (ROIs) from our neuroradiologists. The authors reviewed all MRI scans and corrected any errors in the original ROI drawings for this analysis. We retrospectively assigned diagnoses using established consensus criteria from progress notes stored in our electronic medical record. We analyzed the data using multinomial logistic regression models and receiver operating curve analysis to determine the predictive accuracy of the MRI ratios. Results MRI measures and consensus diagnoses were

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    • Structural MRI Ratios Fail to Distinguish Progressive Supranuclear Palsy From #ParkinsonDisease in Individual Patients: https://t.co/d7NPdGpKjh #NeuroTwitter https://t.co/Hg62T75u1h