Impact of Comorbidity Burden on Cognitive Decline: A Prospective Cohort Study of Older Adults with Dementia

Author(s):  
Sheng-Lun Kao ◽  
Jen-Hung Wang ◽  
Shu-Cin Chen ◽  
Yu-Ying Li ◽  
Ya-Lin Yang ◽  
...  

<b><i>Introduction:</i></b> The lack of longitudinal data of comorbidity burden makes the association between comorbidity and cognitive decline inconclusive. We aimed to measure comorbidity and assess its effects on cognitive decline in mild to moderate dementia. <b><i>Methods:</i></b> This was a prospective cohort study. The participants were enrolled from the Hualien Tzu Chi Hospital between January 2015 and December 2018. We enrolled 175 older adults with mild to moderate dementia and conducted in-person interviews to follow-up comorbidity and cognitive function annually. The comorbidity burden indices included Cumulative Illness Rating Scale for Geriatrics (CIRS-G), Charlson Comorbidity Index (CCI), and Medication Regimen Complexity Index (MRCI), and cognitive function was measured by Mini-Mental State Examination (MMSE) and clock drawing test. We employed the generalized estimating equations to assess the longitudinal effect of time-varying comorbidity burden on cognitive decline after adjusting for age, sex, and education. <b><i>Results:</i></b> Most patients were diagnosed with Alzheimer’s disease (88.6%) and in the early stage of dementia (Clinical Dementia Rating [CDR] = 0.5, 57.1%; CDR = 1, 36.6%). Multimorbidity was common (median: 3), and the top 3 most common comorbidities were osteoarthritis (67.4%), hypertension (65.7%), and hyperlipidemia (36.6%). The severity index of CIRS-G was significantly associated with cognitive decline in MMSE after adjusting for age, sex, and education. CCI and MRCI scores were, however, not associated with cognitive function. <b><i>Conclusion:</i></b> The severity index of CIRS-G outperforms CCI and MRCI in reflecting the longitudinal effect of comorbidity burden on cognitive decline in mild to moderate dementia.

Author(s):  
Satoshi Kurita ◽  
Takehiko Doi ◽  
Kota Tsutsumimoto ◽  
Sho Nakakubo ◽  
Hideaki Ishii ◽  
...  

2013 ◽  
Vol 21 (2) ◽  
pp. 119-128 ◽  
Author(s):  
Sebastian Köhler ◽  
Judith Allardyce ◽  
Frans R.J. Verhey ◽  
Ian G. McKeith ◽  
Fiona Matthews ◽  
...  

2021 ◽  
pp. 1-8
Author(s):  
Xiao Liu ◽  
Ayiguli Abudukeremu ◽  
Yuan Jiang ◽  
Zhengyu Cao ◽  
Maoxiong Wu ◽  
...  

Background: Several kinds of motor dysfunction can predict future cognitive impairment in elderly individuals. However, the ability of the fine motor index (FINEA) and gross motor index (GROSSA) to predict the risk of cognitive impairment has not been assessed. Objective: We investigated the associations between FINEA/GROSSA and cognitive impairment. Methods: The data of 4,745 participants from The Irish Longitudinal Study on Ageing (TILDA) were analyzed. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). We first assessed the correlation between the FINEA GROSSA and MMSE in a cross-sectional study. Then, we further investigated the predictive role of the incidence of cognitive impairment in a prospective cohort study. Results: We found that both FINEA and GROSSA were negatively correlated with MMSE in both the unadjusted (FINEA: B = –1.00, 95%confidence intervals (CI): –1.17, –0.83, t = –11.53, p <  0.001; GROSSA: B = –0.85, 95%CI: –0.94, –0.76, t = –18.29, p <  0.001) and adjusted (FINEA: B = –0.63, 95%CI: –0.79, –0.47, t = –7.77, p <  0.001; GROSSA: B = –0.57, 95%CI: –0.66, –0.48, t = –12.61, p <  0.001) analyses in a cross-sectional study. In a prospective cohort study, both high FINEA and high GROSSA were associated with an increased incidence of cognitive function impairment (FINEA: adjusted odds ratios (OR) = 2.35, 95%CI: 1.05, 5.23, p = 0.036; GROSSA adjusted OR = 3.00, 95%CI: 1.49, 6.03, p = 0.002) after 2 years of follow-up. Conclusion: Higher FINEA and GROSSA scores were both associated with an increased incidence of cognitive impairment. FINEA or GROSSA might be a simple tool for identifying patients with cognitive impairment.


2021 ◽  
Vol 40 (1) ◽  
pp. 229-236 ◽  
Author(s):  
Chi Hsien Huang ◽  
Beatriz Arakawa Martins ◽  
Kiwako Okada ◽  
Eiji Matsushita ◽  
Chiharu Uno ◽  
...  

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