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Navigating Sex-Specific Disease Dynamics in Incident Dementia.
Garg, Muskan; Liu, Xingyi; Vassilaki, Maria; Petersen, Ronald C; St Sauver, Jennifer; Sohn, Sunghwan.
Afiliação
  • Garg M; Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, USA.
  • Liu X; Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, USA.
  • Vassilaki M; Quantitative Health Science Research, Mayo Clinic, Rochester, MN, USA.
  • Petersen RC; Department of Neurology, Mayo Clinic, Rochester, MN, USA.
  • St Sauver J; Quantitative Health Science Research, Mayo Clinic, Rochester, MN, USA.
  • Sohn S; Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, USA.
Article em En | MEDLINE | ID: mdl-38404695
ABSTRACT
Dementia is among the leading causes of cognitive and functional loss and disability in older adults. Past studies suggested sex differences in health conditions and progression of cognitive decline. Existing studies on the temporal trajectory of health conditions for patient characterization after dementia diagnosis are scarce and ambiguous. Thus, there's limited and unclear research on how health conditions change over time after a dementia diagnosis. To this end, we aim to analyze the shift in medical conditions and examine sex-specific changes in patterns of chronic health conditions after dementia diagnosis. We centered our analysis on a 15-year window around the point of dementia diagnosis, encompassing the 5 years leading up to the diagnosis and the 10 years following it. We introduce (i) MedMet, a network metric to quantify the contribution of each medical condition, and (ii) growth and decay function for temporal trajectory analysis of medical conditions. Our experiments demonstrate that certain health conditions are more prevalent among females than males. Thus, our findings underscore the pressing need to examine differences between men and women, which could be important for healthcare utilization after a dementia diagnosis.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article