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Search: WFRF:(Peters S) > Örebro University

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2.
  • Janssen, O., et al. (author)
  • Characteristics of subjective cognitive decline associated with amyloid positivity
  • 2022
  • In: Alzheimers & Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 18:10, s. 1832-1845
  • Journal article (peer-reviewed)abstract
    • Introduction The evidence for characteristics of persons with subjective cognitive decline (SCD) associated with amyloid positivity is limited. Methods In 1640 persons with SCD from 20 Amyloid Biomarker Study cohort, we investigated the associations of SCD-specific characteristics (informant confirmation, domain-specific complaints, concerns, feelings of worse performance) demographics, setting, apolipoprotein E gene (APOE) epsilon 4 carriership, and neuropsychiatric symptoms with amyloid positivity. Results Between cohorts, amyloid positivity in 70-year-olds varied from 10% to 76%. Only older age, clinical setting, and APOE epsilon 4 carriership showed univariate associations with increased amyloid positivity. After adjusting for these, lower education was also associated with increased amyloid positivity. Only within a research setting, informant-confirmed complaints, memory complaints, attention/concentration complaints, and no depressive symptoms were associated with increased amyloid positivity. Feelings of worse performance were associated with less amyloid positivity at younger ages and more at older ages. Discussion Next to age, setting, and APOE epsilon 4 carriership, SCD-specific characteristics may facilitate the identification of amyloid-positive individuals.
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3.
  • Klonoff, D. C., et al. (author)
  • A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings
  • 2022
  • In: Journal of Diabetes Science and Technology. - : SAGE Publications. - 1932-2968.
  • Journal article (peer-reviewed)abstract
    • Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low–glucose and low-glucose hypoglycemia; very high–glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.
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4.
  • Jansen, Willemijn J, et al. (author)
  • Association of Cerebral Amyloid-β Aggregation With Cognitive Functioning in Persons Without Dementia.
  • 2018
  • In: JAMA psychiatry. - : American Medical Association (AMA). - 2168-6238 .- 2168-622X. ; 75:1, s. 84-95
  • Journal article (peer-reviewed)abstract
    • Cerebral amyloid-β aggregation is an early event in Alzheimer disease (AD). Understanding the association between amyloid aggregation and cognitive manifestation in persons without dementia is important for a better understanding of the course of AD and for the design of prevention trials.To investigate whether amyloid-β aggregation is associated with cognitive functioning in persons without dementia.This cross-sectional study included 2908 participants with normal cognition and 4133 with mild cognitive impairment (MCI) from 53 studies in the multicenter Amyloid Biomarker Study. Normal cognition was defined as having no cognitive concerns for which medical help was sought and scores within the normal range on cognitive tests. Mild cognitive impairment was diagnosed according to published criteria. Study inclusion began in 2013 and is ongoing. Data analysis was performed in January 2017.Global cognitive performance as assessed by the Mini-Mental State Examination (MMSE) and episodic memory performance as assessed by a verbal word learning test. Amyloid aggregation was measured with positron emission tomography or cerebrospinal fluid biomarkers and dichotomized as negative (normal) or positive (abnormal) according to study-specific cutoffs. Generalized estimating equations were used to examine the association between amyloid aggregation and low cognitive scores (MMSE score ≤27 or memory z score≤-1.28) and to assess whether this association was moderated by age, sex, educational level, or apolipoprotein E genotype.Among 2908 persons with normal cognition (mean [SD] age, 67.4 [12.8] years), amyloid positivity was associated with low memory scores after age 70 years (mean difference in amyloid positive vs negative, 4% [95% CI, 0%-7%] at 72 years and 21% [95% CI, 10%-33%] at 90 years) but was not associated with low MMSE scores (mean difference, 3% [95% CI, -1% to 6%], P = .16). Among 4133 patients with MCI (mean [SD] age, 70.2 [8.5] years), amyloid positivity was associated with low memory (mean difference, 16% [95% CI, 12%-20%], P < .001) and low MMSE (mean difference, 14% [95% CI, 12%-17%], P < .001) scores, and this association decreased with age. Low cognitive scores had limited utility for screening of amyloid positivity in persons with normal cognition and those with MCI. In persons with normal cognition, the age-related increase in low memory score paralleled the age-related increase in amyloid positivity with an intervening period of 10 to 15 years.Although low memory scores are an early marker of amyloid positivity, their value as a screening measure for early AD among persons without dementia is limited.
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5.
  • Jansen, Willemijn J, et al. (author)
  • Prevalence of cerebral amyloid pathology in persons without dementia: a meta-analysis.
  • 2015
  • In: JAMA. - : American Medical Association (AMA). - 1538-3598 .- 0098-7484. ; 313:19, s. 1924-38
  • Journal article (peer-reviewed)abstract
    • Cerebral amyloid-β aggregation is an early pathological event in Alzheimer disease (AD), starting decades before dementia onset. Estimates of the prevalence of amyloid pathology in persons without dementia are needed to understand the development of AD and to design prevention studies.
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6.
  • Mattsson, Niklas, et al. (author)
  • Prevalence of the apolipoprotein E ε4 allele in amyloid β positive subjects across the spectrum of Alzheimer's disease
  • 2018
  • In: Alzheimer's and Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 14:7, s. 913-924
  • Journal article (peer-reviewed)abstract
    • Introduction: Apolipoprotein E (APOE) ε4 is the major genetic risk factor for Alzheimer's disease (AD), but its prevalence is unclear because earlier studies did not require biomarker evidence of amyloid β (Aβ) pathology. Methods: We included 3451 Aβ+ subjects (853 AD-type dementia, 1810 mild cognitive impairment, and 788 cognitively normal). Generalized estimating equation models were used to assess APOE ε4 prevalence in relation to age, sex, education, and geographical location. Results: The APOE ε4 prevalence was 66% in AD-type dementia, 64% in mild cognitive impairment, and 51% in cognitively normal, and it decreased with advancing age in Aβ+ cognitively normal and Aβ+ mild cognitive impairment (P <.05) but not in Aβ+ AD dementia (P =.66). The prevalence was highest in Northern Europe but did not vary by sex or education. Discussion: The APOE ε4 prevalence in AD was higher than that in previous studies, which did not require presence of Aβ pathology. Furthermore, our results highlight disease heterogeneity related to age and geographical location.
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7.
  • Flink, Ida, 1980-, et al. (author)
  • Pain psychology in the 21st century : lessons learned and moving forward
  • 2020
  • In: Scandinavian Journal of Pain. - : Elsevier. - 1877-8860 .- 1877-8879. ; 20:2, s. 229-238
  • Journal article (peer-reviewed)abstract
    • Background and aims: In the spring of 2019, Professor Steven J. Linton, the founder of the Center for Health and Medical Psychology (CHAMP) at Örebro University, Sweden, formally retired. As a tribute to his scholarly work covering decades of influence and inspiration to the field of pain psychology, the research center organized a topical conference titled "Pain in the 21st century: Where do we come from and where are we going?", which resulted in this state-of the-art synthesis. The aim of this declaration is to highlight lessons learned but not in the least is meant to inspire and guide our continued journey forward, developing pain psychology into the 21st century.Methods: Several collaborators of Professor Linton have summarized and reflected on the current state-of-the-art of pain psychology from the perspective of his input to the field, as well as on developments from the last years of advancements in pain psychology.Results: The topics have been divided into six themed sections covering the fear avoidance model, transdiagnostics, secondary prevention, risk- and protective factors, communication and contextual factors. The sections cover a broad spectrum, from basic experimental studies, integrating emotion and motivational theories into current theoretical models, to applied research on the effect of early interventions as well as sophisticated emotion-focused treatment models for pain patients with concurrent emotional ill-health.Conclusions: There have been major advancements within pain psychology research during the last decades, moving the field towards a more comprehensive picture, taking emotional and motivational aspects into account to understand pain sufferers. Although psychologically informed interventions in general mainly focus on the individual, it has been put forward that pain management is highly influenced by the surrounding environment, including communication with health care providers, and the occupational and social context.Implications: Professor Steven J. Linton has been at the forefront of pain psychology research during the last decades, and inspired by his work this journey will continue into the 21st century, with the ultimate goal of enhancing the understanding and treatment for all people suffering from persistent and disabling pain.
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8.
  • Jansen, Willemijn J, et al. (author)
  • Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum.
  • 2022
  • In: JAMA neurology. - : American Medical Association (AMA). - 2168-6157 .- 2168-6149. ; 79:3, s. 228-243
  • Journal article (peer-reviewed)abstract
    • One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design.To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates.This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria.Alzheimer disease biomarkers detected on PET or in CSF.Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations.Among the 19 097 participants (mean [SD] age, 69.1 [9.8] years; 10 148 women [53.1%]) included, 10 139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P = .04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P = .004), subjective cognitive decline (9%; 95% CI, 3%-15%; P = .005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P = .004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P = .18).This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies.
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9.
  • van Maurik, Ingrid S., et al. (author)
  • Biomarker-based prognosis for people with mild cognitive impairment (ABIDE) : a modelling study
  • 2019
  • In: Lancet Neurology. - : The Lancet Publishing Group. - 1474-4422 .- 1474-4465. ; 18:11, s. 1034-1044
  • Journal article (peer-reviewed)abstract
    • BACKGROUND: Biomarker-based risk predictions of dementia in people with mild cognitive impairment are highly relevant for care planning and to select patients for treatment when disease-modifying drugs become available. We aimed to establish robust prediction models of disease progression in people at risk of dementia.METHODS: In this modelling study, we included people with mild cognitive impairment (MCI) from single-centre and multicentre cohorts in Europe and North America: the European Medical Information Framework for Alzheimer's Disease (EMIF-AD; n=883), Alzheimer's Disease Neuroimaging Initiative (ADNI; n=829), Amsterdam Dementia Cohort (ADC; n=666), and the Swedish BioFINDER study (n=233). Inclusion criteria were a baseline diagnosis of MCI, at least 6 months of follow-up, and availability of a baseline Mini-Mental State Examination (MMSE) and MRI or CSF biomarker assessment. The primary endpoint was clinical progression to any type of dementia. We evaluated performance of previously developed risk prediction models-a demographics model, a hippocampal volume model, and a CSF biomarkers model-by evaluating them across cohorts, incorporating different biomarker measurement methods, and determining prognostic performance with Harrell's C statistic. We then updated the models by re-estimating parameters with and without centre-specific effects and evaluated model calibration by comparing observed and expected survival. Finally, we constructed a model combining markers for amyloid deposition, tauopathy, and neurodegeneration (ATN), in accordance with the National Institute on Aging and Alzheimer's Association research framework.FINDINGS: We included all 2611 individuals with MCI in the four cohorts, 1007 (39%) of whom progressed to dementia. The validated demographics model (Harrell's C 0·62, 95% CI 0·59-0·65), validated hippocampal volume model (0·67, 0·62-0·72), and updated CSF biomarkers model (0·72, 0·68-0·74) had adequate prognostic performance across cohorts and were well calibrated. The newly constructed ATN model had the highest performance (0·74, 0·71-0·76).INTERPRETATION: We generated risk models that are robust across cohorts, which adds to their potential clinical applicability. The models could aid clinicians in the interpretation of CSF biomarker and hippocampal volume results in individuals with MCI, and help research and clinical settings to prepare for a future of precision medicine in Alzheimer's disease. Future research should focus on the clinical utility of the models, particularly if their use affects participants' understanding, emotional wellbeing, and behaviour.
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