Conversion From Subtypes of Mild Cognitive Impairment to Alzheimer Dementia

Hussain, Hadi Meeran

doi:10.1212/01.wnl.0000278072.42014.6d

Cited by 10 publications

(6 citation statements)

References 2 publications

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“…These findings are in good agreement with previous observations [18,19]. However, as previously noted by Fischer et al [20], the subtypes of MCI were not very useful in defining with precision the evolution to different types of dementia; indeed, both aMCI and naMCI progressed to LOAD, while the evolution to VD was not restricted to naMCI.…”

Section: Discussionsupporting

confidence: 92%

Clinical and demographic parameters predict the progression from mild cognitive impairment to dementia in elderly patients

et al. 2020

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Objectives To evaluate the possibility of predicting the risk of progression from mild cognitive impairment (MCI) to dementia using a combination of clinical/demographic parameters. Methods A total of 462 MCI elderly patients (follow-up: 33 months). Variable measured included cognitive functions, age, gender, MCI type, education, comorbidities, clinical chemistry, and functional status. Results Amnestic type (aMCI) represented 63% of the sample, non-amnestic (naMCI) 37%; 190 subjects progressed to dementia, 49% among aMCI, and 28% among naMCI. At Cox multivariate regression analysis, only MMSE (one point increase HR 0.84; 95% CI 0.79–0.90), aMCI (HR 2.35; 95% CI 1.39–3.98), and age (1 year increase HR 1.05; 95% CI 1.01–1.10) were independently associated with progression to dementia. A score was created based on these dichotomized variables (score 0–3): age (≥ or < 78 years), MMSE score (≥ or < 25/30) and aMCI type. The conversion rate progressed from 6% in subjects with score 0 (negative predictive value: 0.94), to 31% in individuals with score 1, to 53% in subjects with score 2, to 72% in individuals with score 3 (positive predictive value: 0.72). ROC curve analysis showed an area under the curve of 0.72 (95% CI 0.66–0.75, p 0.0001). Conclusions We have described a simple score, based on previously recognized predictors such as age, MMSE, and MCI type, which may be useful for an initial stratification of the risk of progression to dementia in patients affected by MCI. The score might help the clinicians to evaluate the need for more expansive/invasive examinations and for a closer follow-up in MCI patients.

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Section: Discussionsupporting

confidence: 92%

Clinical and demographic parameters predict the progression from mild cognitive impairment to dementia in elderly patients

et al. 2020

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“…Type 2 diabetes or impairment of glucose metabolism may increase the risk of cognitive impairment and accelerate the progress from MCI to dementia, and it is up to 80% of patients with AD (Ganguli et al, 2004; Busse et al, 2006; Yaffe et al, 2006; Hussain, 2007; Xu et al, 2010; Tuma, 2012; Roberts et al, 2014). …”

Section: Discussionmentioning

confidence: 99%

Relative power and coherence of EEG series are related to amnestic mild cognitive impairment in diabetes

Bian

Wang

et al. 2014

Front. Aging Neurosci.

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Objective: Diabetes is a risk factor for dementia and mild cognitive impairment. The aim of this study was to investigate whether some features of resting-state EEG (rsEEG) could be applied as a biomarker to distinguish the subjects with amnestic mild cognitive impairment (aMCI) from normal cognitive function in type 2 diabetes.Materials and Methods: In this study, 28 patients with type 2 diabetes (16 aMCI patients and 12 controls) were investigated. Recording of the rsEEG series and neuropsychological assessments were performed. The rsEEG signal was first decomposed into delta, theta, alpha, beta, gamma frequency bands. The relative power of each given band/sum of power and the coherence of waves from different brain areas were calculated. The extracted features from rsEEG and neuropsychological assessments were analyzed as well.Results: The main findings of this study were that: (1) compared with the control group, the ratios of power in theta band [P(theta)] vs. power in alpha band [P(alpha)] [P(theta)/P(alpha)] in the frontal region and left temporal region were significantly higher for aMCI, and (2) for aMCI, the alpha coherences in posterior, fronto-right temporal, fronto-posterior, right temporo-posterior were decreased; the theta coherences in left central-right central (LC-RC) and left posterior-right posterior (LP-RP) regions were also decreased; but the delta coherences in left temporal-right temporal (LT-RT) region were increased.Conclusion: The proposed indexes from rsEEG recordings could be employed to track cognitive function of diabetic patients and also to help in the diagnosis of those who develop aMCI.

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“…AD is only one of the possible underlying aetiologies of MCI [59] and for this reason there is no automatic correspondence between MCI and AD. This means that MCI patients with an amnestic phenotype (which, theoretically, might predicts future conversion to AD dementia) do not necessarily convert to AD dementia and, vice versa, non-amnestic MCI might convert to AD dementia [60]. This suggests that the population of MCI patients is quite heterogeneous with regard to the neural and cognitive status, and, therefore it might have a heterogeneous response to CS, whatever the rationale of the exercises is.…”

Section: Part 2: Cognitive Stimulation In the Presence Of A Diagnosismentioning

confidence: 99%

Cognitive stimulation of the default-mode network modulates functional connectivity in healthy aging

Marco

Meneghello

Duzzi

et al. 2016

Brain Research Bulletin

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A cognitive-stimulation tool was created to regulate functional connectivity within the brain Default-Mode Network (DMN). Computerized exercises were designed based on the hypothesis that repeated task-dependent coactivation of multiple DMN regions would translate into regulation of resting-state network connectivity. Forty seniors (mean age: 65.90 years; SD: 8.53) were recruited and assigned either to an experimental group (n=21) who received one month of intensive cognitive stimulation, or to a control group (n=19) who maintained a regime of daily-life activities explicitly focused on social interactions. An MRI protocol and a battery of neuropsychological tests were administered at baseline and at the end of the study. Changes in the DMN (measured via functional connectivity of posterior-cingulate seeds), in brain volumes, and in cognitive performance were measured with mixed models assessing group-by-timepoint interactions. Moreover, regression models were run to test gray-matter correlates of the various stimulation tasks. Significant associations were found between task performance and gray-matter volume of multiple DMN core regions. Training-dependent up-regulation of functional connectivity was found in the posterior DMN component. This interaction was driven by a pattern of increased connectivity in the training group, while little or no up-regulation was seen in the control group. Minimal changes in brain volumes were found, but there was no change in cognitive performance. The training-dependent regulation of functional connectivity within the posterior DMN component suggests that this stimulation program might exert a beneficial impact in the prevention and treatment of early AD neurodegeneration, in which this neurofunctional pathway is progressively affected by the disease.

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Conversion From Subtypes of Mild Cognitive Impairment to Alzheimer Dementia

Cited by 10 publications

References 2 publications

Clinical and demographic parameters predict the progression from mild cognitive impairment to dementia in elderly patients

Clinical and demographic parameters predict the progression from mild cognitive impairment to dementia in elderly patients

Relative power and coherence of EEG series are related to amnestic mild cognitive impairment in diabetes

Cognitive stimulation of the default-mode network modulates functional connectivity in healthy aging

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