Validation study of the Alzheimer's Disease Assessment Scale‐Cognitive Subscale for people with mild cognitive impairment and Alzheimer's disease in Chinese communities

Yang, Hongyu; Zhang, Cheng; Li, Zemei; Jiang, Yan; Zhao, Jinfa; Wu, Yue; Gu, Shouquan; Xu, Hong

doi:10.1002/gps.5179

Cited by 13 publications

(19 citation statements)

References 35 publications

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“…[ 18 ] acknowledged a limitation to the ADAS-Cog assessment is the various versions available that makes it difficult for cross-comparison of its validity and reliability. The most frequently used assessment in validation studies is the ADAS-Cog, where for MCI patients, the accuracy is of 82–83%, sensitivity 58–61% and specificity of 91–93%; and for AD patients, the accuracy is of 90.5–99.6%, sensitivity of 74–94% and specificity of 92–98% [ 22 , 23 ].…”

Section: Methodsmentioning

confidence: 99%

Examining Cognitive Factors for Alzheimer’s Disease Progression Using Computational Intelligence

2022

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Prognosis of Alzheimer’s disease (AD) progression has been recognized as a challenging problem due to the massive numbers of cognitive, and pathological features recorded for patients and controls. While there have been many studies investigated the diagnosis of dementia using pathological characteristics, predicting the advancement of the disease using cognitive elements has not been heavily studied particularly using technologies like artificial intelligence and machine learning. This research aims at evaluating items of the Alzheimer’s Disease Assessment Scale-Cognitive 13 (ADAS-Cog-13) test to determine key cognitive items that influence the progression of AD. A methodology that consists of machine learning and feature selection (FS) techniques was designed, implemented, and then tested against real data observations (cases and controls) of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) repository with a narrow scope on cognitive items of the ADAS-Cog-13 test. Results obtained by ten-fold cross validation and using dissimilar classification and FS techniques revealed that the decision tree algorithm produced classification models with the best performing results from the cognitive items. For ADAS-Cog-13 test, memory and learning features including word recall, delayed word recall and word recognition were the key items pinpointing to AD advancement. When these three cognitive items are processed excluding demographics by C4.5 algorithm the models derived showed 82.90% accuracy, 87.60% sensitivity and 78.20% specificity.

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Section: Methodsmentioning

confidence: 99%

Examining Cognitive Factors for Alzheimer’s Disease Progression Using Computational Intelligence

2022

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“…31 Its sensitivity and specificity for screening dementia are 95% and 100%, respectively, 15,32 both higher than MMSE (92.5%, 79.1%) and ADAS-cog (73.7%, 92.4%). 17,18 Assessing the association between cognitive function and plasma biomarkers is an important part of AD protein biomarker research. We confirmed the difference of plasma Aβ42 levels in different clinical stages of AD and the association between plasma Aβ42 and CDR.…”

Section: Discussionmentioning

confidence: 99%

“… 31 Its sensitivity and specificity for screening dementia are 95% and 100%, respectively, 15 , 32 both higher than MMSE (92.5%, 79.1%) and ADAS-cog (73.7%, 92.4%). 17 , 18 …”

Section: Discussionmentioning

confidence: 99%

“…It contains of 13 items aimed at assessing four functional domains, including memory function, temporal orientation, work efficiency, and mental pathology, with total score of more than 4 points indicating subjective cognitive impairment. The Clinical Dementia Rating (CDR), Alzheimer’s Dementia Assessment Scale-cognitive subscale (ADAS-cog), 17 and Mini Mental State Examination (MMSE) 18 were used to evaluate overall objective cognitive impairment. The criteria for normal cognition were CDR = 0, or ADAS-cog: 0–9, or MMSE: 28–30; mild cognitive impairment were CDR = 0.5, or ADAS-cog: 10–15, or MMSE: 20–27 and severe cognitive impairment were CDR ≥1, or ADAS-cog≥16, or MMSE <20.…”

Section: Methodsmentioning

confidence: 99%

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Association Plasma Aβ42 Levels with Alzheimer’s Disease and Its Influencing Factors in Chinese Elderly Population

Wu¹,

Wang²,

Yin³

et al. 2022

NDT

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Background and Purpose: Intracerebral Aβ protein deposition is an important pathological mechanism of Alzheimer's disease (AD) and is one of the indicators of early diagnosis of AD. However, invasive lumbar puncture and Aβ PET are difficult to perform in primary units, resulting delays in early diagnosis of AD. In recent years, it has been found that plasma Aβ can reflect the pathological state of AD in early stage, but the results are not consistent. The objective of this study was to explore the association between plasma Aβ42 levels and AD cognitive impairment and its influencing factors in Chinese elderly population, so as to provide guidance for the clinical application of plasma Aβ42 as a blood biomarker of AD. Methods: This is a cross-sectional study based on the community population. Plasma samples were collected from 604 healthy controls (HC), 508 mild cognitive impairment (MCI) and 202 dementia with Alzheimer's type (DAT) patients from three cities. We analyzed the correlation between plasma Aβ42 levels and cognitive function and the influence of confounding factors on the relationship between plasma Aβ42 levels and AD. The independent influencing factors of plasma Aβ42 levels were determined by covariance and linear regression analysis. Results: Our results suggest that there is a special linear relationship between plasma Aβ42 and cognitive impairment of AD in Chinese elderly population, with Aβ42 levels slightly decreased in early AD and significantly increased in moderate-to-severe AD (P<0.01). There are many factors influencing the association between plasma Aβ42 levels and AD cognitive impairment, and sample source, gender and BMI are independent influencing factors of plasma Aβ42. Conclusion:This indentifies that plasma Aβ42 may be a peripheral biomarker for AD screening in Chinese elderly population, but it is necessary to establish standardized detection methods and establish different demarcation criteria for various influencing factors.

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“…The primary end point index was the Alzheimer's disease assessment scale-cognitive subscale (ADAS-Cog/12) score [18]. Secondary end point indexes were the clinician's interview-based impression of change plus caregiver input (CIBIC-Plus) scale [19], Alzheimer's disease cooperative study ADL scale (ADCS-ADL) [20], and neuropsychiatric inventory (NPI) scale [21].…”

Section: Trial End Point and Evaluation Indexesmentioning

confidence: 99%

DL-3-n-butylphthalide Delays Cognitive Decline in Patients With Mild to Moderate Alzheimer's Disease Already Receiving Donepezil: A Multicenter, Prospective Cohort Study

Wang

Guo

et al. 2020

Preprint

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Abstract Background：Vascular factors and mitochondria dysfunction contributeto thepathogenesis of Alzheimer’s Disease (AD).DL-3-n-butylphthalide (NBP)has an effect in protecting mitochondria and improving microcirculation. We investigated the effect of NBP in patients with mild-moderate AD already receiving donepezil.Methods: It was a prospective cohort study. 92 mild-moderate AD patients were classified into the donepezil alone group (n=43) or the donepezil combined NBP group (n=49) for 48 weeks. The primary outcome was change of Alzheimer’s disease assessment scale-cognitive subscale (ADAS-cog) from baseline after treatment 48 weeks. All patients were also evaluated with clinician’s interview-based impression of change plus caregiver input (CIBIC-plus), Alzheimer's disease cooperative study-activities of daily living (ADCS-ADL) and neuropsychiatric inventory (NPI) every 12 weeks. All patients were monitored for adverse events (AEs). The efficacy was analyzed using logistic regression analysis.Results:The univariate analysis showed that age wasolder in donepezil alone group(P=0.005), prevalence of hypertension was higher in donepezil alone group(P=0.026).The ADAS-cog score change from baseline in thedonepezil alone group was significant than that in the donepezil combined NBP group at 48 weeks(1.82±5.20 vs -0.38±4.46, P=0.048). The multivariate logistic regression analysis showed that between the 2 groups, there were significant differencesin changes on the ADAS-cog(OR=0.879,95% CI:[0.785,0.984],P=0.026),MMSE(OR=1.270,95% CI:[1.036,1.557],P=0.021), and ADCS-ADL(OR=1.067,95% CI:[1.002,1.136],P=0.042) but no significant differences for changes on the NPI(OR=0.955,95% CI:[0.901，1.013],P=0.125)and CIBIC-plus (OR=0.356,95% CI:[0.093,1.364],P=0.132). The occurrence of AEs was similar in the 2 groups.Conclusions:Over the 48-week treatment period, donepezil combined NBP group had slower cognitive decline and better activities of daily living in patients with mild to moderate AD. These indicated that the multi-target therapeutic effect of NBP may be a new choice for AD treatment.Trial registration:Clinical trial registration URL:https://clinicaltrials.gov/ct2/show/NCT02711683?term=NCT02711683&draw=2&rank=1ClinicalTrials.gov Identifier: NCT02711683. Date of registration: March 14,2016.

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Validation study of the Alzheimer's Disease Assessment Scale‐Cognitive Subscale for people with mild cognitive impairment and Alzheimer's disease in Chinese communities

Cited by 13 publications

References 35 publications

Examining Cognitive Factors for Alzheimer’s Disease Progression Using Computational Intelligence

Examining Cognitive Factors for Alzheimer’s Disease Progression Using Computational Intelligence

Association Plasma Aβ42 Levels with Alzheimer’s Disease and Its Influencing Factors in Chinese Elderly Population

DL-3-n-butylphthalide Delays Cognitive Decline in Patients With Mild to Moderate Alzheimer's Disease Already Receiving Donepezil: A Multicenter, Prospective Cohort Study

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