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Independent effects of white matter hyperintensities on frailty among individuals with Alzheimer's disease
Author(s) -
Yang Hyunju,
Park Joon Hyuk
Publication year - 2021
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1002/alz.053552
Subject(s) - dementia , medicine , grip strength , comorbidity , gerontology , body mass index , population , hyperintensity , charlson comorbidity index , physical therapy , disease , radiology , environmental health , magnetic resonance imaging
Background With an aging global population, recent years have seen rapid expansion in the attention of the frailty. Thus, understanding, and determinant the potentially modifiable risk factor for frailty is a major concern for health care policy and provision. Method Subjects were recruited for the study from the dementia clinic of Jeju National University Hospital between January 2018 and January 2020. All of the subjects were evaluated by using CERAD‐K and diagnosed probable AD and possible AD by a panel of two experienced dementia research neuropsychiatrists. WMH volume was calculated using automated segmentation analysis and further partitioned into three categories (Kim, BIOL PSYCHIATRY 2008). Frailty evaluated by Korean Frailty Index (KFI) and classified into three categories according to the cutpoints. Other physical performances such as BMI, muscle mass index, grip strength, and gait speed measures were performed by experienced researchers specialized in geriatric assessment. comorbidity status using the Charlson comorbidity index, and depressive symptoms using GDS was examined. Result In total, 34 subjects (23.6 %) were classified as frail 47 subjects (32.6 %) were classified as prefrail, and 63 subjects (43.8 %) were classified as a non‐frail group. The frail group had higher WMH volume compared to the non‐frail group ( p =0.002), and these trends remained significant after linear regression analyses. According to the new subclassification of WMH, using the non‐frail group as a reference, total WMH volume (OR=6.297, p=0.013), JVWMH volume (OR=12.955, p=0.014), and PVWMH (OR=3.382, p=0.025) were associated with frail. Furthermore, according to the path model, only the gait speed mediated the association between WMH and frailty. Conclusion In our study provides evidence of a cross‐sectional relationship between WMH and frailty, and there is a difference in the association between the subclassification of WMH volume and frailty. Furthermore, we suggest that gait speed could be a useful biomarker for assessment of the frailty.