scholarly journals Pilot Evaluation of the Unsupervised, At-Home Cogstate Brief Battery in ADNI-2

2021 ◽  
pp. 1-11
Author(s):  
Chris J. Edgar ◽  
Eric Siemers ◽  
Paul Maruff ◽  
Ronald C. Petersen ◽  
Paul S. Aisen ◽  
...  

Background: There is a need for feasible, scalable assessments to detect cognitive impairment and decline. The Cogstate Brief Battery (CBB) is validated for Alzheimer’s disease (AD) and in unsupervised and bring your own device contexts. The CBB has shown usability for self-completion in the home but has not been employed in this way in a multisite clinical trial in AD. Objective: The objective of the pilot was to evaluate feasibility of at-home, self-completion of the CBB in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) over 24 months. Methods: The CBB was included as a pilot for cognitively normal (CN) and mild cognitive impairment (MCI) participants in ADNI-2, invited to take the assessment in-clinic, then at at-home over a period of 24 months follow-up. Data were analyzed to explore acceptability/usability, concordance of in-clinic and at-home assessment, and validity. Results: Data were collected for 104 participants (46 CN, 51 MCI, and 7 AD) who consented to provide CBB data. Subsequent analyses were performed for the CN and MCI groups only. Test completion rates were 100%for both the first in-clinic supervised and first at-home unsupervised assessments, with few repeat performances required. However, availability follow-up data declined sharply over time. Good concordance was seen between in-clinic and at-home assessments, with non-significant and small effect size differences (Cohen’s d between -0.04 and 0.28) and generally moderate correlations (r = 0.42 to 0.73). Known groups validity was also supported (11/16 comparisons with Cohen’s d≥0.3). Conclusion: These data demonstrate the feasibility of use for the CBB for unsupervised at-home, testing, including MCI groups. Optimal approaches to the application of assessments to support compliance over time remain to be determined.

2020 ◽  
Vol 17 ◽  
Author(s):  
Hyung-Ji Kim ◽  
Jae-Hong Lee ◽  
E-nae Cheong ◽  
Sung-Eun Chung ◽  
Sungyang Jo ◽  
...  

Background: Amyloid PET allows for the assessment of amyloid β status in the brain, distinguishing true Alzheimer’s disease from Alzheimer’s disease-mimicking conditions. Around 15–20% of patients with clinically probable Alzheimer’s disease have been found to have no significant Alzheimer’s pathology on amyloid PET. However, a limited number of studies had been conducted this subpopulation in terms of clinical progression. Objective: We investigated the risk factors that could affect the progression to dementia in patients with amyloid-negative amnestic mild cognitive impairment (MCI). Methods: This study was a single-institutional, retrospective cohort study of patients over the age of 50 with amyloidnegative amnestic MCI who visited the memory clinic of Asan Medical Center with a follow-up period of more than 36 months. All participants underwent brain magnetic resonance imaging (MRI), detailed neuropsychological testing, and fluorine-18[F18]-florbetaben amyloid PET. Results: During the follow-up period, 39 of 107 patients progressed to dementia from amnestic MCI. In comparison with the stationary group, the progressed group had a more severe impairment in verbal and visual episodic memory function and hippocampal atrophy, which showed an Alzheimer’s disease-like pattern despite the lack of evidence for significant Alzheimer’s disease pathology. Voxel-based morphometric MRI analysis revealed that the progressed group had a reduced gray matter volume in the bilateral cerebellar cortices, right temporal cortex, and bilateral insular cortices. Conclusion: Considering the lack of evidence of amyloid pathology, clinical progression of these subpopulation may be caused by other neuropathologies such as TDP-43, abnormal tau or alpha synuclein that lead to neurodegeneration independent of amyloid-driven pathway. Further prospective studies incorporating biomarkers of Alzheimer’s diseasemimicking dementia are warranted.


2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S290-S291
Author(s):  
Johannes Lieslehto ◽  
Erika Jääskeläinen ◽  
Jouko Miettunen ◽  
Matti Isohanni ◽  
Dominic Dwyer ◽  
...  

Abstract Background Previous machine learning studies using structural MRI (sMRI) have been able to separate schizophrenia from controls with relatively high (about 80%) sensitivity and specificity (Kambeitz et al. Neuropsychopharmacology 2015). Interestingly, prediction accuracy in first-episode psychosis is lower compared to older and probably more chronic patients. One possibility is that the appearance of the neurodiagnostic fingerprints (NF) originated from the schizophrenia vs. controls classifier become more visible over time in schizophrenia due to the progressive nature of the disorder. Methods Using the Cobre sample (70 schizophrenia and 74 controls), we trained support vector machine (SVM) to differentiate schizophrenia from controls using sMRI. Next, we utilized the Northern Finland Birth Cohort 1966 (NFBC 1966) sample of 29 schizophrenia and 61 non-psychotic controls who participated in the nine-year follow-up. We applied the Cobre-trained SVM models at the baseline (participants 34 years old) and the follow-up (participants 43 years old) using out of sample cross-validation without any in-between retraining. Two independent schizophrenia datasets (the Neuromorphometry by Computer Algorithm Chicago [NMorphCH] and the Consortium for Neuropsychiatric Phenomics [CNP]) were utilized for replication analyses of the SVM generalizability. To address the possibility that the NF mainly capture some general psychopathology, we tested whether the NF generalize to depression using two independent MDD samples from Munich and Münster, Germany. Results Using the Cobre-trained SVM models for schizophrenia vs. controls differentiation in the NFBC 1966, we found balanced accuracy (i.e. mean of sensitivity and specificity, [BAC]) of 72.8% (sensitivity=58.6%, specificity=86.9%) at the baseline and BAC of 79.7% (sensitivity=75.9%, specificity=83.6%) at the follow-up. In the NFBC 1966 schizophrenia patients, we found that SVM decision scores varied as a function of timepoint into the direction of more schizophrenia-likeness at the follow-up (paired T-test, Cohen’s d=0.58, P=0.004). The same was not true in controls (Cohen’s d=0.09, P=0.49). The SVM decision score difference*timepoint interaction related to the decrease of hippocampus and medial prefrontal cortex. The SVM models’ performance was also validated at the two replication samples (BAC of 77.5% in the CNP and BAC of 69.1% in the NMorphCH). In the NFBC 1966 the strongest clinical variable correlating with the trajectory of SVM decision scores over the follow-up was poor performance in the California Verbal Learning Test. This finding was also replicated in the CNP dataset. Further, in the NFBC 1966, those schizophrenia patients with a low degree of SVM decision scores had a higher probability of being in remission, being able to work, and being without antipsychotic medication at the follow-up. The generalization of the SVM models to MDD was worse compared to schizophrenia classification (DeLong’s tests for the two ROC curves: P<0.001). Discussion The degree of schizophrenia-related neurodiagnostic fingerprints appear to magnify over time in schizophrenia. By contrast, the discernibility of these fingerprints in controls does not change over time. This indicates that the NF captures some schizophrenia-related progressive neural changes, and not, e.g., normal aging-related brain volume loss. The fingerprints were also generalizable to other schizophrenia samples. Further, the fingerprints seem to have some disorder specificity as the SVM models do not generalize to depression. Lastly, it appears that a low degree of schizophrenia-related NF in schizophrenia might possess some value in predicting patients’ future remission and recovery-related factors.


2016 ◽  
Vol 52 (1) ◽  
pp. 133-143 ◽  
Author(s):  
María Eugenia López ◽  
Agustín Turrero ◽  
Pablo Cuesta ◽  
David López-Sanz ◽  
Ricardo Bruña ◽  
...  

2019 ◽  
Author(s):  
Rewadee Jenraumjit ◽  
Surarong Chinwong ◽  
Dujrudee Chinwong ◽  
Tipaporn Kanjanarach ◽  
Thanat Kshetradat ◽  
...  

Abstract Objective Age-associated decline in central cholinergic activity makes older adults susceptible to harmful effects of anticholinergics (ACs). Evidence exists of an association between effects of AC medications on cognition. This retrospective cohort study examines how ACs affect cognition among older adults with Alzheimer’s disease (AD) who received acetylcholine esterase inhibitors (AChEIs) over the course of 12 months. Results A total of 133 (80% women, mean age 78.38 years, SD 7.4) were recruited. No difference in sex, age and comorbid diseases was observed between participants who took ACs, Benzodiazepines (BZDs) and AChEIs. The most common prescribed ACs was quetiapine, being used for behavioral and psychological symptoms (BPSD). Multilevel analysis showed that the change of mental state examination scores were significantly predicted in the group using ACs (t (169), -2.52, p = .020) but not with the groups using BZD (t (162), 0.84, p = .440). Evidence showed that older adults with Alzheimer’s disease and exposed to ACs exhibited lower global cognitive scores than those without AC exposure. Using ACs could be a trade-off between controlling BPSD and aggravating cognitive impairment. Highlighting the awareness of the potential anticholinergic effect is important and may be the best policy.


2021 ◽  
pp. 1-12
Author(s):  
Heng Zhang ◽  
Diyang Lyu ◽  
Jianping Jia ◽  

Background: Synaptic degeneration has been suggested as an early pathological event that strongly correlates with severity of dementia in Alzheimer’s disease (AD). However, changes in longitudinal cerebrospinal fluid (CSF) growth-associated protein 43 (GAP-43) as a synaptic biomarker in the AD continuum remain unclear. Objective: To assess the trajectory of CSF GAP-43 with AD progression and its association with other AD hallmarks. Methods: CSF GAP-43 was analyzed in 788 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), including 246 cognitively normal (CN) individuals, 415 individuals with mild cognitive impairment (MCI), and 127 with AD dementia based on cognitive assessments. The associations between a multimodal classification scheme with amyloid-β (Aβ), tau, and neurodegeneration, and changes in CSF GAP-43 over time were also analyzed. Results: CSF GAP-43 levels were increased at baseline in MCI and dementia patients, and increased significantly over time in the preclinical (Aβ-positive CN), prodromal (Aβ-positive MCI), and dementia (Aβ-positive dementia) stages of AD. Higher levels of CSF GAP-43 were also associated with higher CSF phosphorylated tau (p-tau) and total tau (t-tau), cerebral amyloid deposition and hypometabolism on positron emission tomography, the hippocampus and middle temporal atrophy, and cognitive performance deterioration at baseline and follow-up. Furthermore, CSF GAP-43 may assist in effectively predicting the probability of dementia onset at 2- or 4-year follow-up. Conclusion: CSF GAP-43 can be used as a potential biomarker associated with synaptic degeneration in subjects with AD; it may also be useful for tracking the disease progression and for monitoring the effects of clinical trials.


2015 ◽  
Vol 13 (4) ◽  
pp. 462-471 ◽  
Author(s):  
Nathalie Sambuchi ◽  
Isabelle Muraccioli ◽  
Béatrice Alescio-Lautier ◽  
Véronique Paban ◽  
Roland Sambuc ◽  
...  

Author(s):  
S. Tolbert ◽  
Y. Liu ◽  
C. Hellegers ◽  
J.R. Petrella ◽  
M.W. Weiner ◽  
...  

Background: There is a need to more fully characterize financial capacity losses in the preclinical and prodromal stages of Alzheimer’s disease (AD) and their pathological substrates. Objectives: To test the association between financial skills and cortical β-amyloid deposition in aging and subjects at risk for AD. Design: Cross-sectional analyses of data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI-3) study conducted across 50 plus sites in the US and Canada. Setting: Multicenter biomarker study. Participants: 243 subjects (144 cognitively normal, 79 mild cognitive impairment [MCI], 20 mild AD). Measurements: 18F-Florbetapir brain PET scans to measure global cortical β-amyloid deposition (SUVr) and the Financial Capacity Instrument Short Form (FCI-SF) to evaluate an individual’s financial skills in monetary calculation, financial concepts, checkbook/register usage, and bank statement usage. There are five sub scores and a total score (range of 0–74) with higher scores indicating better financial skill. Results: FCI-SF total score was significantly worse in MCI [Cohen’s d= 0.9 (95%CI: 0.6-1.2)] and AD subjects [Cohen’s d=3.1(CI: 2.5-3.7)] compared to normals. Domain scores and completion times also showed significant difference. Across all subjects, higher cortical β-amyloid SUVr was significantly associated with worse FCI-SF total score after co-varying for age, education, and cognitive score [Cohen’s f2=0.751(CI: 0.5-1.1)]. In cognitively normal subjects, after covarying for age, gender, and education, higher β -amyloid PET SUVr was associated with longer task completion time [Cohen’s f2=0.198(CI: 0.06-0.37)]. Conclusion: Using a multicenter study sample, we document that financial capacity is impaired in the prodromal and mild stages of AD and that such impairments are, in part, associated with the extent of cortical β-amyloid deposition. In normal aging, β-amyloid deposition is associated with slowing of financial tasks. These data confirm and extend prior research highlighting the utility of financial capacity assessments in at risk samples.


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