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Background: Subjective cognitive decline (SCD) is a risk factor for Alzheimer's disease (AD); however, the rates of cognitive decline are variable according to underlying pathologies and biomarker status. We conducted an observational study and aimed to investigate baseline characteristics and biomarkers related with cognitive declines in SCD. Our study also assessed whether SCD participants showed different cognitive and biomarker trajectories according to baseline amyloid deposition. Methods: This study is a part of a longitudinal cohort study conducted in multi-centers in South Korea between 2018 and 2021. Individuals (≥ 60 years old) with persistent cognitive complaint despite of normal cognitive functions were eligible for the study. All participants underwent neuropsychological tests, florbetaben PET scans, plasma amyloid markers, and brain MRI scans. Annual follow-up evaluations included neuropsychological tests and assessments for clinical progressions. Regional brain volumetry and amyloid burden represented by PET-based standardized uptake value ratio (SUVR) were measured. We compared cognitive and brain atrophic changes over 24 months between amyloid positive-SCD (Aβ + SCD) and amyloid negative-SCD (Aβ-SCD) groups. Baseline factors associated with cognitive outcomes were investigated. Results: A total of 120 participants with SCD were enrolled and 107 completed follow-up evaluations. Aβ + SCD participants (n = 20, 18.5%) were older and more frequently APOE4 carriers compared with Aβ-SCD participants (n = 87). Baseline cognitive scores were not different between the two groups, except the Seoul Verbal Learning Test (SVLT) scores showing lower scores in the Aβ + SCD group. After 24 months, plasma amyloid markers were higher, and regional volumes (entorhinal, hippocampal, and pallidum) were smaller in the Aβ + SCD participants compared with Aβ-SCD participants adjusted by age, sex, and baseline volumes. SVLT delayed recall and controlled oral word association test (COWAT) scores indicated more declines in Aβ + SCD participants. Baseline left entorhinal volumes were related to verbal memory decline, while baseline frontal volumes and global SUVR values were related to frontal functional decline. Conclusion: Aβ + SCD participants showed more cognitive decline and medial temporal atrophic changes during 24 months. Baseline neurodegeneration and amyloid burden were related with future cognitive trajectories in SCD. Trial registration: This study was registered at CRIS (KCT0003397). [ABSTRACT FROM AUTHOR]

Background: Neuropsychological tests (NPTs) are important tools for informing diagnoses of cognitive impairment (CI). However, interpreting NPTs requires specialists and is thus time-consuming. To streamline the application of NPTs in clinical settings, we developed and evaluated the accuracy of a machine learning algorithm using multi-center NPT data.Methods: Multi-center data were obtained from 14,926 formal neuropsychological assessments (Seoul Neuropsychological Screening Battery), which were classified into normal cognition (NC), mild cognitive impairment (MCI) and Alzheimer's disease dementia (ADD). We trained a machine learning model with artificial neural network algorithm using TensorFlow (https://www.tensorflow.org) to distinguish cognitive state with the 46-variable data and measured prediction accuracies from 10 randomly selected datasets. The features of the NPT were listed in order of their contribution to the outcome using Recursive Feature Elimination.Results: The ten times mean accuracies of identifying CI (MCI and ADD) achieved by 96.66 ± 0.52% of the balanced dataset and 97.23 ± 0.32% of the clinic-based dataset, and the accuracies for predicting cognitive states (NC, MCI or ADD) were 95.49 ± 0.53 and 96.34 ± 1.03%. The sensitivity to the detection CI and MCI in the balanced dataset were 96.0 and 96.0%, and the specificity were 96.8 and 97.4%, respectively. The 'time orientation' and '3-word recall' score of MMSE were highly ranked features in predicting CI and cognitive state. The twelve features reduced from 46 variable of NPTs with age and education had contributed to more than 90% accuracy in predicting cognitive impairment.Conclusions: The machine learning algorithm for NPTs has suggested potential use as a reference in differentiating cognitive impairment in the clinical setting. [ABSTRACT FROM AUTHOR]

Background: High-dose donepezil is currently prescribed for patients with Alzheimer's disease (AD) who showed poor or waning response to a lower dose at the risk of increasing cholinergic side effects. However, the adverse events (AEs) depending on the method of dose escalation have not been clarified yet. This study aimed to find out whether dose titration before escalating to donepezil 23 mg is preferred. We investigated safety and tolerability of donepezil 23 mg during the first 12 weeks of dose escalation in patients with moderate to severe AD. Methods: This study was a 12-week, multicenter, randomized, open-label prospective trial. We included patients with moderate to severe AD who were treated with a stable dose of donepezil 10 mg/day. Patients were randomized into 3 groups according to the dose escalation method: 15 mg of donepezil for 4 weeks before escalating to 23 mg (group 1), 10 mg and 23 mg on alternate days for 4 weeks prior to escalation (group 2), and direct escalation to 23 mg (group 3). Safety analyses included incidence, severity, timing of AEs, relationship to the study drug, and premature study discontinuation due to AEs between the groups. Results: Among 175 enrolled, 110 patients completed the study. Baseline characteristics were similar among the groups. Using safety population (N = 160), cholinergic gastrointestinal symptoms including anorexia and nausea were the most common AEs and titration groups showed significantly fewer cases of nausea as compared with those in no-titration group. Conclusions: In this study, dose titration before escalating to donepezil 23 mg/day showed better safety in terms of cholinergic AEs. We suggest that dose titration during the first 4 weeks can be recommended for patients with moderate to severe AD. Trial registration: Clinicaltrials.gov, NCT02550665. Retrospectively registered on 15 Sep 2015. [ABSTRACT FROM AUTHOR]