Publications by authors named "P O'Keefe"

Article Synopsis
  • - This study analyzes generational shifts in disease incidence and mortality among older adults in England, similar to previous findings in the U.S., using data from the English Longitudinal Study of Ageing (ELSA).
  • - Researchers found that diseases like memory complaints, heart conditions, and cancer have higher incidence rates in later-born cohorts, paralleling trends observed in the U.S., but with more negative outcomes in England.
  • - While some diseases showed no significant difference between men and women, when differences were present, women generally exhibited lower risks. The findings suggest a potential increase in disease burden for future generations.
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To contribute to our understanding of cohort differences and the Flynn effect in the cognitive decline among older Americans, this study aims to compare rates of cognitive decline between two birth cohorts within a study of older Americans and to examine the importance of medical and demographic confounders. Analyses used data from the National Health and Aging Trends Study (2011-2019), which recruited older Americans in 2011 and again in 2015 who were then followed for 5 years. We employed mixed-effect models to examine the linear and quadratic main and interaction effects of year of birth while adjusting for covariates such as annual round, sex/gender, education, race/ethnicity, heart disease, hypertension, diabetes, test unfamiliarity, and survey design.

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Spinocerebellar ataxias (SCA) are rare inherited neurodegenerative disorders characterized by a progressive impairment of gait, balance, limb coordination, and speech. There is currently no composite scale that includes multiple aspects of the SCA experience to assess disease progression and treatment effects. Applying the method of partial least squares (PLS) regression, we developed the Spinocerebellar Ataxia Composite Scale (SCACOMS) from two SCA natural history datasets (NCT01060371, NCT02440763).

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Background: Disease modifying therapies (DMTs) may be most beneficial in early disease, when progression is slow and changes small, with clinical relevance difficult to interpret.

Objectives: Time component tests (TCTs) translate differences between treatments from mean change, vertical distance between longitudinal trajectories, into intuitively understood time saved, horizontal distance between trajectories, which can be readily combined across endpoints in a global TCT (gTCT).

Design: The value of composites, time savings estimates, and combination scores to optimize measurement and interpretation of DMTs are demonstrated, along with construction details and simulation studies.

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