| 1. |
- Leung, Y., et al.
(författare)
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Cognition, function, and prevalent dementia in centenarians and near-centenarians: An individual participant data (IPD) meta-analysis of 18 studies
- 2023
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Ingår i: Alzheimers & Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 19:6, s. 2265-2275
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Tidskriftsartikel (refereegranskat)abstract
- IntroductionThere are limited data on prevalence of dementia in centenarians and near-centenarians (C/NC), its determinants, and whether the risk of dementia continues to rise beyond 100. MethodsParticipant-level data were obtained from 18 community-based studies (N = 4427) in 11 countries that included individuals >= 95 years. A harmonization protocol was applied to cognitive and functional impairments, and a meta-analysis was performed. ResultsThe mean age was 98.3 years (SD = 2.67); 79% were women. After adjusting for age, sex, and education, dementia prevalence was 53.2% in women and 45.5% in men, with risk continuing to increase with age. Education (OR 0.95;0.92-0.98) was protective, as was hypertension (odds ratio [OR] 0.51;0.35-0.74) in five studies. Dementia was not associated with diabetes, vision and hearing impairments, smoking, and body mass index (BMI). DiscussionAmong the exceptional old, dementia prevalence remains higher in the older participants. Education was protective against dementia, but other factors for dementia-free survival in C/NC remain to be understood.
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| 2. |
- Ge, R, et al.
(författare)
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Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization
- 2023
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Ingår i: bioRxiv : the preprint server for biology. - : Cold Spring Harbor Laboratory.
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Background: Normative modeling is a statistical approach to quantify the degree to which a particular individual-level measure deviates from the pattern observed in a normative reference population. When applied to human brain morphometric measures it has the potential to inform about the significance of normative deviations for health and disease. Normative models can be implemented using a variety of algorithms that have not been systematically appraised. Methods: To address this gap, eight algorithms were compared in terms of performance and computational efficiency using brain regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) collated from 87 international MRI datasets. Performance was assessed with the mean absolute error (MAE) and computational efficiency was inferred from central processing unit (CPU) time. The algorithms evaluated were Ordinary Least Squares Regression (OLSR), Bayesian Linear Regression (BLR), Generalized Additive Models for Location, Scale, and Shape (GAMLSS), Parametric Lambda, Mu, Sigma (LMS), Gaussian Process Regression (GPR), Warped Bayesian Linear Regression (WBLG), Hierarchical Bayesian Regression (HBR), and Multivariable Fractional Polynomial Regression (MFPR). Model optimization involved testing nine covariate combinations pertaining to acquisition features, parcellation software versions, and global neuroimaging measures (i.e., total intracranial volume, mean cortical thickness, and mean cortical surface area). Findings: Statistical comparisons across models at PFDR<0.05 indicated that the MFPR-derived sex- and region-specific models with nonlinear polynomials for age and linear effects of global measures had superior predictive accuracy; the range of the MAE of the models of regional subcortical volumes was 70-520 mm3 and the corresponding ranges for regional cortical thickness and regional cortical surface area were 0.09-0.26 mm and 24-560 mm2, respectively. The MFPR-derived models were also computationally more efficient with a CPU time below one second compared to a range of 2 seconds to 60 minutes for the other algorithms. The performance of all sex- and region-specific MFPR models plateaued at sample sizes exceeding 3,000 and showed comparable MAEs across distinct 10-year age-bins covering the human lifespan. Interpretation: These results provide an empirically benchmarked framework for normative modeling of brain morphometry that is useful for interpreting prior literature and supporting future study designs. The model and tools described here are freely available through CentileBrain (https://centilebrain.org/), a user-friendly web platform.
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| 3. |
- Oh, D. J., et al.
(författare)
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Parental history of dementia and the risk of dementia: A cross-sectional analysis of a global collaborative study
- 2023
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Ingår i: Psychiatry and Clinical Neurosciences. - 1323-1316 .- 1440-1819. ; 77:8, s. 449-456
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Tidskriftsartikel (refereegranskat)abstract
- Background: Parental history of dementia appears to increase the risk of dementia, but there have been inconsistent results. We aimed to investigate whether the association between parental history of dementia and the risk of dementia are different by dementia subtypes and sex of parent and offspring. Methods: For this cross-sectional study, we harmonized and pooled data for 17,194 older adults from nine population-based cohorts of eight countries. These studies conducted face-to-face diagnostic interviews, physical and neurological examinations, and neuropsychological assessments to diagnose dementia. We investigated the associations of maternal and paternal history of dementia with the risk of dementia and its subtypes in offspring. Results: The mean age of the participants was 72.8 +/- 7.9 years and 59.2% were female. Parental history of dementia was associated with higher risk of dementia (odds ratio [OR] = 1.47, 95% confidence interval [CI] = 1.15-1.86) and Alzheimer's disease (AD) (OR = 1.72, 95% CI = 1.31-2.26), but not with the risk of non-AD. This was largely driven by maternal history of dementia, which was associated with the risk of dementia (OR = 1.51, 95% CI = 1.15-1.97) and AD (OR = 1.80, 95% CI = 1.33-2.43) whereas paternal history of dementia was not. These results remained significant when males and females were analyzed separately (OR = 2.14, 95% CI = 1.28-3.55 in males; OR = 1.68, 95% CI = 1.16-2.44 for females). Conclusions: Maternal history of dementia was associated with the risk of dementia and AD in both males and females. Maternal history of dementia may be a useful marker for identifying individuals at higher risk of AD and stratifying the risk for AD in clinical trials.
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| 4. |
- Truong, Quoc Cuong, et al.
(författare)
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Establishing conversion of the 16-item Informant Questionnaire on Cognitive Decline in the Elderly scores into interval-level data across multiple samples using Rasch methodology
- 2023
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Ingår i: Psychogeriatrics. - : Wiley. - 1346-3500 .- 1479-8301. ; 23:3, s. 411-421
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Tidskriftsartikel (refereegranskat)abstract
- Background: The 16-item Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE-16) is a well-validated and widely-used measure of cognitive changes (CCs) among older adults. This study aimed to use Rasch methodology to establish psychometric properties of the IQCODE-16 and validate the existing ordinal-to-interval transformation algorithms across multiple large samples. Methods: A Partial Credit Rasch model was employed to examine psychometric properties of the IQCODE-16 using data (n = 918) from two longitudinal studies of participants aged 57–99 years: the Older Australian Twins Study (n = 450) and the Canberra Longitudinal Study (n = 468), and reusing the Sydney Memory and Ageing Study (MAS) sample (n = 400). Results: Initial analyses indicated good reliability for the IQCODE-16 (Person Separation Index range: 0.82–0.90). However, local dependency was identified between items, with several items showing misfit to the model. Replicating the existing Rasch solution could not reproduce the best Rasch model fit for all samples. Combining locally dependent items into three testlets resolved all misfit and local dependency issues and resulted in the best Rasch model fit for all samples with evidence of unidimensionality, strong reliability, and invariance across person factors. Accordingly, new ordinal-to-interval transformation algorithms were produced to convert the IQCODE-16 ordinal scores into interval data to improve the accuracy of its scores. Conclusions: The findings of this study support the reliability and validity of the IQCODE-16 in measuring CCs among older adults. New ordinal-to-interval conversion tables generated using samples from multiple independent datasets are more generalizable and can be used to enhance the precision of the IQCODE-16 without changing its original format. An easy-to-use converter has been made available for clinical and research use.
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