While the associations of mid-life cardiovascular risk factors with late-life white matter lesions (WMH) and cognitive decline have been established, the role of cerebral haemodynamics is unclear. We investigated the relation of late-life (69-71 years) arterial spin labelling (ASL) MRI-derived cerebral blood flow (CBF) with life-course cardiovascular risk factors (36-71 years) and late-life white matter hyperintensity (WMH) load in 282 cognitively healthy participants (52.8% female).
View Article and Find Full Text PDFBackground: Between 25 and 75% of people with persistent post-acute sequelae of SARS-CoV-2 infection (PASC) experience cognitive difficulties, compromising functional ability, quality of life, and activities of daily living, including work. Despite this significant morbidity, there is a paucity of interventions for this disorder that have undergone evaluation within a formal trial setting. Therefore, we have developed a cognitive rehabilitation programme, specifically designed to address the cognitive symptoms of PASC, notably impaired attention and processing speed, while also accounting for other PASC symptoms (fatigue, post-exertional malaise) that may aggravate the cognitive impairment.
View Article and Find Full Text PDFJ Public Health Manag Pract
September 2024
As the COVID-19 pandemic progressed, reliable, accessible, and equitable community-based testing strategies were sought that did not flood already overburdened hospitals and emergency departments. In Hamilton County, Ohio, home to ~800 000 people across urban, suburban, and rural areas, we sought to develop and optimize an accessible, equitable county-wide COVID-19 testing program. Using Coronavirus Aid, Relief, and Economic Security Act funding, multidisciplinary, multiorganization partners created the test and protect program to deliver safe, reliable testing in neighborhoods and organizations needing it most.
View Article and Find Full Text PDFCurrent methods for identifying temporal windows of effect for time-varying exposures in omics settings can control false discovery rates at the biomarker-level but cannot efficiently screen for timing-specific effects in high dimensions. Current approaches leverage separate models for site screening and identification of susceptible time windows, which miss associations that vary over time. We introduce the epigenome-wide distributed lag model (EWDLM), a novel approach that combines traditional false discovery rate methods with the distributed lag model (DLM) to screen for timing-specific effects in high dimensional settings.
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