This paper explores the trajectory of amyloid accumulation onset in the brain relative to cognitive decline to potentially improve secondary prevention efforts of Alzheimer’s disease (AD). This was...Show moreThis paper explores the trajectory of amyloid accumulation onset in the brain relative to cognitive decline to potentially improve secondary prevention efforts of Alzheimer’s disease (AD). This was accomplished by attempting a replication of the study "Spatiotemporal distribution of β-amyloid in Alzheimer's disease is the result of heterogeneous carrying capacities" (Whittington et al., 2018) using data obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Results showed that Whittington’s model of the temporal evolution of the in vivo PET β-amyloid signal over time (i.e. using the four parameters: the tracer nonspecific binding (NS), the exponential uninhibited growth rate (r), the time of half-maximal β -amyloid concentration (T50) and the carrying capacity (K)), and the derived “estimated time since disease onset” could be used to model β-amyloid accumulation trajectory. Additionally, by studying the relationship between the trajectory of amyloid accumulation and cognitive decline, the results showed that amyloid accumulation in the brain does precede cognitive decline and can be modeled to predict cognitive deterioration. Thus, it was concluded that “estimated time since disease onset” does serve as a possible effective predictive diagnostic tool of cognitive impairments and AD pathology. Additionally, this study emphasizes the need for future research on the mechanisms by which amyloid accumulation influences cognitive impairments.Show less
Depression and/or anxiety affect approximately one third of the Dutch population at least once in their lifetime. Cross-sectional research has shown the relationship between elevated depression and...Show moreDepression and/or anxiety affect approximately one third of the Dutch population at least once in their lifetime. Cross-sectional research has shown the relationship between elevated depression and/or anxiety symptoms and low scores on memory function. However, there is a scarcity of data on the effects of depression and/or anxiety on memory decline over time. Thus, Multilevel growth curve modelling was applied to assess associations between depression, anxiety and memory. We used nationally representative data from older adults in The Netherlands that participated in the LASA-study, that encompasses data on predictors and consequences of aging. The final sample included 4056 individuals, aged 55 – 86 and 51.3% female. Model B (main effects) showed a negative effect of depression on memory and a positive effect of anxiety on memory. Model C and D dealt with the rate of change and the acceleration of rate of change. Among the focal predictors, only depression and age significantly affected the staring rate of change in memory. The effect of anxiety on the initial rate of change in memory was non-significant and could not be generalized. The effect of measurement point (mp) on the starting rate of change, does not depend on the combination of values for depression and anxiety. Within model D, only age turned out to affect the (positive) starting rate of change and the de-acceleration of this starting rate of change. Relatively older people tend to start off with a somewhat lower positive rate of change in memory and are more likely to have a stronger decline of this rate of change over time. The effect of depression on the starting rate was still negative and had the same direction in model D as in model C, but depression lost its significance in model D. Also, it had a non-significant effect on the de acceleration of the rate of change. Anxiety, as in model C, did not contribute significantly to model D in any way. The interaction between depression and anxiety was non-significant and did not contribute. In conclusion, memory decline is not accelerated in people with high levels of depression and/or anxiety. Only older age and sex have effect on memory decline over time. Further research could take additional variables into account in predicting memory decline, such as dementia, since depression and anxiety are highly prevalent in patients with dementia and it is plausible that early AD is one of the most important factors in age-related memory decline. Further research could take other variables into account, such as dementia, other cognitive functions, education, lifestyle, health-risks, heart disease, diabetes. Moreover, further distinctions in the variables could be made, such as the difference in effects on memory decline between late-onset depression (LOD) and early-onset depression (EOD).Show less
Objective: The aim of this study was to assess whether the psychometric properties of a new version of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for elderly migrants...Show moreObjective: The aim of this study was to assess whether the psychometric properties of a new version of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for elderly migrants(IQCODE-sf-M) has better predictive quality for dementia than the original version in short form (IQCODE-sf) for dementia in elderly migrants with low or no education. The original version IQCODE-sf contains 16 items and the IQCODE-sf-M contains 21 items, of which 11 items are newly added, assuming to be less culturally biased.Methods: This study is a case control design. In this study 111 patients of the memory clinic and 50 healthy participants with the age of 55 years or older were included. The patient group was divided in three groups; dementia (n = 49), MCI (n = 34) and cognitively healthy (n = 28). At least 50% of participants in the patient sample were illiterate. The informants of the participants filled out the IQCODE, for example a caregiver or relative. Results: The area under the curve (AUROC) of the IQCODE-sf was 0.86. A cut-off point of 3.69 yielded a sensitivity of 88% and a specificity of 74%. The AUROC of the IQCODE-sf-M was 0.87. A cut-off point of 3.57 yielded a sensitivity of 81% and a specificity of 86%. We found no statistically significant difference in the psychometric properties between the new modified IQCODE (IQCODE sf-M) and IQCODE in short form (IQCODE-sf).Conclusion: In this study it has been shown that the original version of the IQCODE in short form works fine for the elderly migrants in the clinical and community settings and could not be improved by adding 11 new itemsShow less
Objectives. In the Netherlands, a significant part of the population consists of non-Western immigrants, such as people from Turkey, Morocco and Surinam. The number of these elderly, non-Western...Show moreObjectives. In the Netherlands, a significant part of the population consists of non-Western immigrants, such as people from Turkey, Morocco and Surinam. The number of these elderly, non-Western immigrants is expected to increase and they are now reaching an age at which cognitive deteriorations due to dementia might occur. Although many instruments are available for the diagnosis of dementia with native Dutch patients, research showed that there is a high rate of under- and misdiagnosis among ethnic minority patients. The diagnosis of dementia for this group can be considered as challenging, as there is a major lack of appropriate neuropsychological assessment methods for culturally different and low-educated or illiterate populations. Therefore, adapted neuropsychological test batteries were developed by neuropsychologists at Erasmus MC for non-Western immigrants, in order to assess dementia. The aim of this study was to examine the validity and to investigate the relation and importance of these adapted neuropsychological tests. . Methods. This study consisted of patients with cognitive decline (n = 29) and cognitively healthy controls (n = 23), with a non-Western immigration background. Patients were referred to the Alzheimer Centre of the Erasmus MC, whereas controls were recruited through social networks and were assessed by a neuropsychologist in training. The RUDAS, verbal fluency tests and literacy screening were used as screeners, after which a number of adapted neuropsychological tests, such as Clock Reading Test and Recall of Pictures Test were administered. Results. As expected, controls showed significantly better performance on most tests in the battery than patients. Against expectations, education level of the patients and controls appeared to be associated with performance on a large part of the battery. Education level was found to be highly associated with participants’ literacy. Tests measuring similar cognitive functions were found to be significantly related. . . Conclusion. This study indicates that various adapted test batteries form a foundation to discriminate dementia between non-Western immigrants with cognitive decline and cognitively intact non-Western immigrants, in the Netherlands on group level. Although these results should be interpreted with caution, as the samples were small and not homogeneous, this study has an important clinical relevance. Future research is needed to obtain more generalizable results.Show less
Background: Psychotic like experiences (PLE) play a role in the development of psychotic disorders. However, less is known about the clinicopathological significance of PLE for the development of...Show moreBackground: Psychotic like experiences (PLE) play a role in the development of psychotic disorders. However, less is known about the clinicopathological significance of PLE for the development of nonpsychotic disorders. The current study examined the association of PLE with non-psychotic disorders in adolescents. Secondly, I proposed that this association between PLE and non-psychotic disorders would be moderated by intelligence. The aim of this study is to gain a broader understanding of the development of disorders and to give foundation for interventions concerned with early detection and prevention. Methods: A sample (N=430) of Dutch adolescents aged 13- to 18-year-olds were recruited as part of the iBerry prospective cohort study. The current study is a cross-sectional observational study based on its baseline data. Participants completed a self-report questionnaire (PQ-16) regarding PLE and were subjected to an intelligence test (SON) and a structured interview (MINI) to assess psychiatric disorders. Using logistic regression analysis and moderation analysis I investigated associations between PLE, the presence of non-psychotic disorders and intelligence. Results: The logistic regression model was statistically significant (χ2 (8) = 25.337, p = .001) and explained 15.3% of the variance in non-psychotic disorders. The control variables age, gender and educational level were also taken into account in the analysis. PLE was the only significant predictor (p < .001) and provided an odds ratio of 5.00 (95% CI = 2.16 - 11.56). Because of this wide confidence interval this effect can be considered small to big. The proposed moderating effect of intelligence on the association between PLE and non-psychotic disorders could not be found (p = .179) in the current sample. Conclusions: The results support a model of psychological vulnerability in which subclinical psychiatric symptoms could be indicative for non-specific psychiatric disorders. Further research is indicated to better understand the underlying mechanisms and clinical relevance of PLE in relation to transition to clearly defined psychiatric disorders. Research is also indicated to explore the possible protective role of intelligence in this transition.Show less
Objective: Cancer-related fatigue is defined as a persistent, subjective sense of tiredness related to cancer and cancer treatment that interferes with usual functioning. In addition to confirming...Show moreObjective: Cancer-related fatigue is defined as a persistent, subjective sense of tiredness related to cancer and cancer treatment that interferes with usual functioning. In addition to confirming the well-known presence of fatigue in patients with low-grade glioma (LGG), this study investigated whether patients suffered from cognitive impairment, and whether this cognitive impairment was related to the experienced fatigue. Method: Due to the exploratory nature of this study many outcome measures were investigated in order to map the possible factors related to experienced levels of fatigue. We therefore chose to perform descriptive statistical analyses. Fatigue and different subscales of fatigue (mental fatigue, physical fatigue, decreased motivation, decreased activity and general fatigue) were measured with the self-report Multidimensional Fatigue Inventory. In order to measure neuropsychological functioning all patients completed a battery of standardized neuropsychological tests selected to cover a broad range of cognitive functions, including attention and concentration, executive functioning, and memory. Mann-Whitney tests were used to compare severely fatigued patients to non-severely fatigued patients in order to analyse whether their performance on neuropsychological testing differed. In addition, we also examined whether severely fatigued patients differed from non-severely fatigued patients in characteristics, time post diagnosis, tumor location and treatment. These analyses were only performed for mental and physical fatigue. Results: Thirty-one adult patients (mean age, 44 years; 21 males [68%]) with a confirmed LGG and a mean time post diagnosis of 2.5 years were included in this study. Severe mental fatigue prevalence rates were reported by 17/31 (55%) patients, whereas 9/31 (29%) patients reported severe physical fatigue. Sixteen percent of the patients reported both severe mental and physical fatigue. Cognitive impairments (t-score < 40) were predominantly observed in the domain of attention and concentration (21.9%), and to a lesser extent in the domains of memory (15.8%) and executive functioning (10.3%). Significant differences (p < .05) between severely mental fatigued patients and non-severely mental fatigued patients were found on 4/14 (29%) cognitive tests. Concerning the physical fatigued patients and non-severely physical fatigued patients, significant differences (p < .05) were found on 2/14 (14%) cognitive tests. Conclusion: Our data demonstrated that LGG patients showed high levels of experienced fatigue, especially in the domain of mental fatigue, when compared to healthy individuals, which might partially be explained by impairment in cognitive functions, which where predominantly observed in the domain of attention and concentration. Additional research is needed to identify what other factors might cause increased levels of experienced fatigue in patients with LGG.Show less
