Tracking Cognitive Performance in the General Population and in Patients with Mild Cognitive Impairment with a Self-Applied Computerized Test (Brain on Track)

2019 ◽  
Vol 71 (2) ◽  
pp. 541-548 ◽  
Author(s):  
Luis Ruano ◽  
Milton Severo ◽  
Andreia Sousa ◽  
Catarina Ruano ◽  
Mariana Branco ◽  
...  
2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Manfred Berres ◽  
Andreas U. Monsch ◽  
René Spiegel

Abstract Background The Placebo Group Simulation Approach (PGSA) aims at partially replacing randomized placebo-controlled trials (RPCTs), making use of data from historical control groups in order to decrease the needed number of study participants exposed to lengthy placebo treatment. PGSA algorithms to create virtual control groups were originally derived from mild cognitive impairment (MCI) data of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. To produce more generalizable algorithms, we aimed to compile five different MCI databases in a heuristic manner to create a “standard control algorithm” for use in future clinical trials. Methods We compared data from two North American cohort studies (n=395 and 4328, respectively), one company-sponsored international clinical drug trial (n=831) and two convenience patient samples, one from Germany (n=726), and one from Switzerland (n=1558). Results Despite differences between the five MCI samples regarding inclusion and exclusion criteria, their baseline demographic and cognitive performance data varied less than expected. However, the five samples differed markedly with regard to their subsequent cognitive performance and clinical development: (1) MCI patients from the drug trial did not deteriorate on verbal fluency over 3 years, whereas patients in the other samples did; (2) relatively few patients from the drug trial progressed from MCI to dementia (about 10% after 4 years), in contrast to the other four samples with progression rates over 30%. Conclusion Conventional MCI criteria were insufficient to allow for the creation of well-defined and internationally comparable samples of MCI patients. More recently published criteria for MCI or “MCI due to AD” are unlikely to remedy this situation. The Alzheimer scientific community needs to agree on a standard set of neuropsychological tests including appropriate selection criteria to make MCI a scientifically more useful concept. Patient data from different sources would then be comparable, and the scientific merits of algorithm-based study designs such as the PGSA could be properly assessed.


Author(s):  
Filipe Godinho ◽  
Carolina Maruta ◽  
Cláudia Borbinha ◽  
Isabel Pavão Martins

BMJ Open ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. e046879
Author(s):  
Bernhard Grässler ◽  
Fabian Herold ◽  
Milos Dordevic ◽  
Tariq Ali Gujar ◽  
Sabine Darius ◽  
...  

IntroductionThe diagnosis of mild cognitive impairment (MCI), that is, the transitory phase between normal age-related cognitive decline and dementia, remains a challenging task. It was observed that a multimodal approach (simultaneous analysis of several complementary modalities) can improve the classification accuracy. We will combine three noninvasive measurement modalities: functional near-infrared spectroscopy (fNIRS), electroencephalography and heart rate variability via ECG. Our aim is to explore neurophysiological correlates of cognitive performance and whether our multimodal approach can aid in early identification of individuals with MCI.Methods and analysisThis study will be a cross-sectional with patients with MCI and healthy controls (HC). The neurophysiological signals will be measured during rest and while performing cognitive tasks: (1) Stroop, (2) N-back and (3) verbal fluency test (VFT). Main aims of statistical analysis are to (1) determine the differences in neurophysiological responses of HC and MCI, (2) investigate relationships between measures of cognitive performance and neurophysiological responses and (3) investigate whether the classification accuracy can be improved by using our multimodal approach. To meet these targets, statistical analysis will include machine learning approaches.This is, to the best of our knowledge, the first study that applies simultaneously these three modalities in MCI and HC. We hypothesise that the multimodal approach improves the classification accuracy between HC and MCI as compared with a unimodal approach. If our hypothesis is verified, this study paves the way for additional research on multimodal approaches for dementia research and fosters the exploration of new biomarkers for an early detection of nonphysiological age-related cognitive decline.Ethics and disseminationEthics approval was obtained from the local Ethics Committee (reference: 83/19). Data will be shared with the scientific community no more than 1 year following completion of study and data assembly.Trial registration numberClinicalTrials.gov, NCT04427436, registered on 10 June 2020, https://clinicaltrials.gov/ct2/show/study/NCT04427436.


2017 ◽  
Vol 24 (2) ◽  
pp. 176-187 ◽  
Author(s):  
Shanna L. Burke ◽  
Miriam J. Rodriguez ◽  
Warren Barker ◽  
Maria T Greig-Custo ◽  
Monica Rosselli ◽  
...  

AbstractObjectives:The aim of this study was to determine the presence and severity of potential cultural and language bias in widely used cognitive and other assessment instruments, using structural MRI measures of neurodegeneration as biomarkers of disease stage and severity.Methods:Hispanic (n=75) and White non-Hispanic (WNH) (n=90) subjects were classified as cognitively normal (CN), amnestic mild cognitive impairment (aMCI) and mild dementia. Performance on the culture-fair and educationally fair Fuld Object Memory Evaluation (FOME) and Clinical Dementia Rating Scale (CDR) between Hispanics and WNHs was equivalent, in each diagnostic group. Volumetric and visually rated measures of the hippocampus entorhinal cortex, and inferior lateral ventricles (ILV) were measured on structural MRI scans for all subjects. A series of analyses of covariance, controlling for age, depression, and education, were conducted to compare the level of neurodegeneration on these MRI measures between Hispanics and WNHs in each diagnostic group.Results:Among both Hispanics and WNH groups there was a progressive decrease in volume of the hippocampus and entorhinal cortex, and an increase in volume of the ILV (indicating increasing atrophy in the regions surrounding the ILV) from CN to aMCI to mild dementia. For equivalent levels of performance on the FOME and CDR, WNHs had greater levels of neurodegeneration than did Hispanic subjects.Conclusions:Atrophy in medial temporal regions was found to be greater among WNH than Hispanic diagnostic groups, despite the lack of statistical differences in cognitive performance between these two ethnic groups. Presumably, unmeasured factors result in better cognitive performance among WNH than Hispanics for a given level of neurodegeneration. (JINS, 2018,24, 176–187)


2021 ◽  
Vol 12 ◽  
Author(s):  
Yifei Zhang ◽  
Xiaodan Chen ◽  
Xinyuan Liang ◽  
Zhijiang Wang ◽  
Teng Xie ◽  
...  

The topological organization of human brain networks can be mathematically characterized by the connectivity degree distribution of network nodes. However, there is no clear consensus on whether the topological structure of brain networks follows a power law or other probability distributions, and whether it is altered in Alzheimer's disease (AD). Here we employed resting-state functional MRI and graph theory approaches to investigate the fitting of degree distributions of the whole-brain functional networks and seven subnetworks in healthy subjects and individuals with amnestic mild cognitive impairment (aMCI), i.e., the prodromal stage of AD, and whether they are altered and correlated with cognitive performance in patients. Forty-one elderly cognitively healthy controls and 30 aMCI subjects were included. We constructed functional connectivity matrices among brain voxels and examined nodal degree distributions that were fitted by maximum likelihood estimation. In the whole-brain networks and all functional subnetworks, the connectivity degree distributions were fitted better by the Weibull distribution [f(x)~x(β−1)e(−λxβ)] than power law or power law with exponential cutoff. Compared with the healthy control group, the aMCI group showed lower Weibull β parameters (shape factor) in both the whole-brain networks and all seven subnetworks (false-discovery rate-corrected, p < 0.05). These decreases of the Weibull β parameters in the whole-brain networks and all subnetworks except for ventral attention were associated with reduced cognitive performance in individuals with aMCI. Thus, we provided a short-tailed model to capture intrinsic connectivity structure of the human brain functional networks in health and disease.


Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Carla P Rodriguez Monserrate ◽  
Rajeshwari Jakkam ◽  
Emily Clay ◽  
Kimberlee Gauvreau ◽  
Michelle Z GURVITZ

Introduction: The most common comorbidities in children with congenital heart disease (CHD) are neurodevelopmental and psychosocial impairments, particularly in areas of executive function, memory, attention, and behavioral control. Limited studies in the adult CHD population suggest similar impairments exist and adults with CHD may be at increased risk for dementia. No studies have screened specifically for mild cognitive impairment and dementia in adult CHD patients. Methods: We performed a prospective cross-sectional study of adult CHD patients, ages 30-65 years, who were coming for routine clinic visits. We administered the Mini-Mental State Exam (MMSE) and scores were compared with population norms adjusted by age and education level. We also evaluated the association of MMSE scores with CHD complexity, demographic and clinical risk factors. Results: A total of 125 patients were recruited (55% male). The median age was 40 years (range 30-65). Almost all participants (97%) had a high school degree and 75% had some college education or advanced degrees. The majority of patients (94%) had moderate or complex CHD. Adjusting for age and education, CHD participants scored significantly lower than the general population (median 1 point lower, p=0.001). The greatest impairments occurred in recall and orientation. Factors associated with lower scores included decreased systemic ventricular function (p=0.028) and having ≥2 cardiac catheterizations (p=0.006). Five percent of the total cohort met the general threshold for mild cognitive impairment (MMSE<24). Clinical factors associated with this degree of cognitive impairment were duration of cyanosis (p=0.005) and decreased systemic ventricular function (p=0.003). Conclusions: Our pilot study showed that, when adjusted for age and education level, adult CHD patients had significantly lower MMSE scores than the general population, with 5% meeting criteria for mild cognitive impairment. These findings suggest that subtle and early neurodevelopmental changes are present in the adult CHD population. Further studies are needed to investigate those changes and evaluate potential disease modifying therapies that might influence long-term outcomes in the adult CHD population.


2020 ◽  
Vol 12 ◽  
Author(s):  
Fabienne Marlats ◽  
Guillaume Bao ◽  
Sylvain Chevallier ◽  
Marouane Boubaya ◽  
Leila Djabelkhir-Jemmi ◽  
...  

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S152-S152
Author(s):  
Katsuhiko Hagi ◽  
Tadashi Nosaka ◽  
Andrei Pikalov

Abstract Background Schizophrenia is associated with cognitive dysfunction as well as cardiovascular disease (CVD). A central risk factor for CVD is the metabolic syndrome (MetS), which is of special concern in schizophrenia. The prevalence of MetS in U.S. patients with schizophrenia is higher versus general population (32.5% versus 23%). The prevalence of MetS and diabetes mellitus (DM) in those with schizophrenia double that of the general population. Adverse events of some antipsychotics used to treat schizophrenia include weight gain, obesity and other MetS complications, particularly abnormal glucose and lipid metabolism. Patients with schizophrenia have low rates of treatment for MetS and its components. Furthermore, components of MetS are risk factors for cognitive impairment and dementia in the general population. Cognitive impairment is a hallmark feature of schizophrenia, and the level of community functioning is strongly correlated with the degree of cognitive impairment. Given the importance of cognitive impairment in schizophrenia, the potential role of MetS in contributing to cognitive dysfunction is important. The objective of this post-hoc analysis was to examine cross-sectional relationships between metabolic syndrome and cognitive performance in patients with schizophrenia treated with lurasidone or quetiapine XR for 6-weeks. Methods This post hoc analysis utilized data from 6-week, double-blind, placebo-controlled trial of patients with an acute exacerbation of schizophrenia who were randomized to fixed, once-daily oral doses of lurasidone 80 mg (LUR 80 n=125), lurasidone 160 mg (LUR 160, n=121), quetiapine XR 600 mg (QXR, n=120) and placebo (PBO, n=122). Patients with metabolic syndrome (MetS) at baseline were identified based on the National Cholesterol Education Program – Adult Treatment Panel III criteria (NCEP-ATP-III). Cognitive performance and functional capacity were assessed by the CogState computerized cognitive battery at baseline and 6 weeks. Results In the acute 6-week period, LUR160 was significantly superior on the cognitive composite score to PBO (p&lt;0.05, d=0.37), while LUR 80 and QXR did not separate from PBO in the evaluable analysis sample (excluding subjects with non-evaluable composite Z-scores; n=267). A total of 45/267 (16.9%) patients met criteria for MetS. Treatment of patients with MetS group with LUR 160 (vs placebo) was associated with significantly greater week 6 improvement in the cognitive composite score (p&lt;0.05, d=1.15), while LUR 80 and QXR did not separate from PBO. In the group without MetS, LUR dose groups and QXR did not differ from PBO in the CogState composite score. In the analysis of cognitive domain scores, LUR 80 was significantly superior to PBO on working memory in the group with MetS (p&lt;0.05, d=1.01) and reasoning/problem solving in the group without MetS (p&lt;0.05, d=0.46). LUR 160 was significantly superior to PBO on processing speed in the group with MetS (p&lt;0.05, d=1.20), reasoning/problem solving (p&lt;0.05, d=0.45) and social cognition (p&lt;0.05, d=0.46) in the group without MetS. QXR was significantly superior to PBO on verbal learning and reasoning/problem solving in the group without MetS (p&lt;0.05, d=0.38 and p&lt;0.05, d=0.37, respectively). Discussion Patients with MetS responded to treatment with lurasidone with significantly improved CogState composite and domain scores. No improvement on cognition was seen in patients with MetS treated with QXR. Evaluation of potential for MetS and improvements in cognition should be important elements in the algorithm of optimization of treatment in patients with schizophrenia.


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