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Are saving appearance responses typical communication patterns in Alzheimer's disease?

ABSTRACT: INTRODUCTION:To keep up appearances, people with dementia sometimes pretend to know the correct answer, as seen during administration of neuropsychological tests such as the Mini-Mental State Examination (MMSE). These saving appearance responses (SARs) of people with dementia often lead to caregivers and/or medical staff underestimating the severity of dementia and impede proper early initiation of treatment. However, most descriptions of SARs are based on empirical knowledge of clinicians. In this study, we investigated whether SARs are typical communication patterns in people with Alzheimer's disease (AD), compared with mild cognitive impairment (MCI) or dementia with Lewy bodies (DLB). METHODS:The participants were 107 outpatients with AD, 16 with mixed AD with cerebrovascular dementia, 55 with MCI, and 30 with DLB. We assessed the occurrence of SARs during the MMSE. The relationships between the SARs and AD were examined by the ?2 test and logistic regression analysis. RESULTS:People with AD who showed SARs were 57.9%, whereas those with MCI were 18.2% and DLB were 20.0% (P with Bonferroni correction < 0.05). Although there were significant differences in some variables in each group of diagnosis, logistic regression analysis showed that people with AD were more likely to show SARs than those with MCI (Odds ratio = 3.48, 95% Confidential Interval = 1.18-10.28) and DLB (Odds ratio = 4.24, 95% Confidential Interval = 1.50-12.01), even after controlling for sex, estimated disease duration, MMSE, and frontal assessment battery scores. CONCLUSION:The occurrence of SARs could be found most frequently in people with AD. Clinicians should develop a respectful attitude toward dementia patients with SARs because SARs imply conflicted feelings about questions that patients cannot answer correctly.

SUBMITTER: Matsushita M

PROVIDER: S-EPMC5965895 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Are saving appearance responses typical communication patterns in Alzheimer's disease?

Matsushita Masateru M Yatabe Yusuke Y Koyama Asuka A Katsuya Akiko A Ijichi Daisuke D Miyagawa Yusuke Y Ikezaki Hiroto H Furukawa Noboru N Ikeda Manabu M Hashimoto Mamoru M

PloS one 20180523 5

<h4>Introduction</h4>To keep up appearances, people with dementia sometimes pretend to know the correct answer, as seen during administration of neuropsychological tests such as the Mini-Mental State Examination (MMSE). These saving appearance responses (SARs) of people with dementia often lead to caregivers and/or medical staff underestimating the severity of dementia and impede proper early initiation of treatment. However, most descriptions of SARs are based on empirical knowledge of clinicia ...[more]

PMID: 29791460

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Project description:ObjectivesTo investigate the global cortical and regional quantitative features of cortical neural architecture in the brains of patients with posterior cortical atrophy (PCA) and typical Alzheimer's disease (tAD) compared with elderly healthy controls (HC).MethodsA novel diffusion MRI method, that has been shown to correlate with minicolumnar organization changes in the cerebral cortex, was used as a surrogate of neuropathological changes in dementia. A cohort of 15 PCA patients, 23 tAD and 22 healthy elderly controls (HC) were enrolled to investigate the changes in cortical diffusivity among groups. For each subject, 3 T MRI T1-weighted images and diffusion tensor imaging (DTI) scans were analysed to extract novel cortical DTI derived measures (AngleR, PerpPD and ParlPD). Receiver operating characteristics (ROC) curve analysis and the area under the curve (AUC) were used to assess the group discrimination capability of the method.ResultsThe results showed that the global cortical DTI derived measures were able to detect differences, in both PCA and tAD patients compared to healthy controls. The AngleR was the best measure to discriminate HC from tAD (AUC?=?0.922), while PerpPD was the best measure to discriminate HC from PCA (AUC?=?0.961). Finally, the best global measure to differentiate the two patient groups was ParlPD (AUC?=?0.771). The comparison between PCA and tAD patients revealed a different pattern of damage within the AD spectrum and the regional comparisons identified significant differences in key regions including parietal and temporal lobe cortical areas. The best AUCs were shown by PerpPD right lingual cortex (AUC?=?0.856), PerpPD right superior parietal cortex (AUC?=?0.842) and ParlPD right lateral occipital cortex (AUC?=?0.826).ConclusionsDiagnostic group differences were found, suggesting that the new cortical DTI analysis method may be useful to investigate cortical changes in dementia, providing better characterization of neurodegeneration, and potentially aiding differential diagnosis and prognostic accuracy.

Project description:Neuroimaging biomarkers that distinguish between changes due to typical brain ageing and Alzheimer's disease are valuable for determining how much each contributes to cognitive decline. Supervised machine learning models can derive multivariate patterns of brain change related to the two processes, including the Spatial Patterns of Atrophy for Recognition of Alzheimer's Disease (SPARE-AD) and of Brain Aging (SPARE-BA) scores investigated herein. However, the substantial overlap between brain regions affected in the two processes confounds measuring them independently. We present a methodology, and associated results, towards disentangling the two. T1-weighted MRI scans of 4054 participants (48-95 years) with Alzheimer's disease, mild cognitive impairment (MCI), or cognitively normal (CN) diagnoses from the Imaging-based coordinate SysTem for AGIng and NeurodeGenerative diseases (iSTAGING) consortium were analysed. Multiple sets of SPARE scores were investigated, in order to probe imaging signatures of certain clinically or molecularly defined sub-cohorts. First, a subset of clinical Alzheimer's disease patients (n = 718) and age- and sex-matched CN adults (n = 718) were selected based purely on clinical diagnoses to train SPARE-BA1 (regression of age using CN individuals) and SPARE-AD1 (classification of CN versus Alzheimer's disease) models. Second, analogous groups were selected based on clinical and molecular markers to train SPARE-BA2 and SPARE-AD2 models: amyloid-positive Alzheimer's disease continuum group (n = 718; consisting of amyloid-positive Alzheimer's disease, amyloid-positive MCI, amyloid- and tau-positive CN individuals) and amyloid-negative CN group (n = 718). Finally, the combined group of the Alzheimer's disease continuum and amyloid-negative CN individuals was used to train SPARE-BA3 model, with the intention to estimate brain age regardless of Alzheimer's disease-related brain changes. The disentangled SPARE models, SPARE-AD2 and SPARE-BA3, derived brain patterns that were more specific to the two types of brain changes. The correlation between the SPARE-BA Gap (SPARE-BA minus chronological age) and SPARE-AD was significantly reduced after the decoupling (r = 0.56-0.06). The correlation of disentangled SPARE-AD was non-inferior to amyloid- and tau-related measurements and to the number of APOE ε4 alleles but was lower to Alzheimer's disease-related psychometric test scores, suggesting the contribution of advanced brain ageing to the latter. The disentangled SPARE-BA was consistently less correlated with Alzheimer's disease-related clinical, molecular and genetic variables. By employing conservative molecular diagnoses and introducing Alzheimer's disease continuum cases to the SPARE-BA model training, we achieved more dissociable neuroanatomical biomarkers of typical brain ageing and Alzheimer's disease.

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Are saving appearance responses typical communication patterns in Alzheimer's disease?

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Are saving appearance responses typical communication patterns in Alzheimer's disease?

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