Enhancing cognitive performance prediction by white matter hyperintensity connectivity assessment.

White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating brain health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. Lesion network mapping (LNM) enables to infer if brain networks are connected to lesions and could be a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed LNM to test the following hypotheses: (1) LNM-informed markers surpass WMH volumes in predicting cognitive performance, and (2) WMH contributing to cognitive impairment map to specific brain networks. We analyzed cross-sectional data of 3,485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in 4 cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity to 480 atlas-based gray and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. We compared the capacity of total and regional WMH volumes and LNM scores in predicting cognitive function using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention/executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater connectivity to WMH, in gray and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance. Measures of WMH-related brain network connectivity significantly improve the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network integrity, particularly in attention-related brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders.

Benzodiazepine use in relation to long-term dementia risk and imaging markers of neurodegeneration: a population-based study.

BACKGROUND: Benzodiazepine use is common, particularly in older adults. Benzodiazepines have well-established acute adverse effects on cognition, but long-term effects on neurodegeneration and dementia risk remain uncertain. METHODS: We included 5443 cognitively healthy (MMSE ≥ 26) participants from the population-based Rotterdam Study (57.4% women, mean age 70.6 years). Benzodiazepine use from 1991 until baseline (2005-2008) was derived from pharmacy dispensing records, from which we determined drug type and cumulative dose. Benzodiazepine use was defined as prescription of anxiolytics (ATC-code: N05BA) or sedative-hypnotics (ATC-code: N05CD) between inception of pharmacy records and study baseline. Cumulative dose was calculated as the sum of the defined daily doses for all prescriptions. We determined the association with dementia risk until 2020 using Cox regression. Among 4836 participants with repeated brain MRI, we further determined the association of benzodiazepine use with changes in neuroimaging markers using linear mixed models. RESULTS: Of all 5443 participants, 2697 (49.5%) had used benzodiazepines at any time in the 15 years preceding baseline, of whom 1263 (46.8%) used anxiolytics, 530 (19.7%) sedative-hypnotics, and 904 (33.5%) used both; 345 (12.8%) participants were still using at baseline assessment. During a mean follow-up of 11.2 years, 726 participants (13.3%) developed dementia. Overall, use of benzodiazepines was not associated with dementia risk compared to never use (HR [95% CI]: 1.06 [0.90-1.25]), irrespective of cumulative dose. Risk estimates were somewhat higher for any use of anxiolytics than for sedative-hypnotics (HR 1.17 [0.96-1.41] vs 0.92 [0.70-1.21]), with strongest associations for high cumulative dose of anxiolytics (HR [95% CI] 1.33 [1.04-1.71]). In imaging analyses, current use of benzodiazepine was associated cross-sectionally with lower brain volumes of the hippocampus, amygdala, and thalamus and longitudinally with accelerated volume loss of the hippocampus and to a lesser extent amygdala. However, imaging findings did not differ by type of benzodiazepines or cumulative dose. CONCLUSIONS: In this population-based sample of cognitively healthy adults, overall use of benzodiazepines was not associated with increased dementia risk, but potential class-dependent adverse effects and associations with subclinical markers of neurodegeneration may warrant further investigation.

Depressive Symptoms and Plasma Markers of Alzheimer's Disease and Neurodegeneration: A Coordinated Meta-Analysis of 8 Cohort Studies.

BACKGROUND: Depressive symptoms are associated with an increased risk of Alzheimer's disease (AD). There has been a recent emergence in plasma biomarkers for AD pathophysiology, such as amyloid-beta (Aß) and phosphorylated tau (p-tau), as well as for axonal damage (neurofilament light, NfL) and astrocytic activation (glial fibrillary acidic protein, GFAP). Hypothesizing that depressive symptoms may occur along the AD process, we investigated associations between plasma biomarkers of AD with depressive symptoms in individuals without dementia. METHODS: A two-stage meta-analysis was performed on 2 clinic-based and 6 population-based cohorts (N = 7210) as part of the Netherlands Consortium of Dementia Cohorts. Plasma markers (Aß42/40, p-tau181, NfL, and GFAP) were measured using Single Molecular Array (Simoa; Quanterix) assays. Depressive symptoms were measured with validated questionnaires. We estimated the cross-sectional association of each standardized plasma marker (determinants) with standardized depressive symptoms (outcome) using linear regressions, correcting for age, sex, education, and APOE ε4 allele presence, as well as subgrouping by sex and APOE ε4 allele. Effect estimates were entered into a random-effects meta-analysis. RESULTS: Mean age of participants was 71 years. The prevalence of clinically relevant depressive symptoms ranged from 1% to 22%. None of the plasma markers were associated with depressive symptoms in the meta-analyses. However, NfL was associated with depressive symptoms only in APOE ε4 carriers (ß 0.11; 95% CI: 0.05-0.17). CONCLUSIONS: Late-life depressive symptoms did not show an association to plasma biomarkers of AD pathology. However, in APOE ε4 allele carriers, a more profound role of neurodegeneration was suggested with depressive symptoms.

Family history of dementia and brain health in childhood and middle age: a prospective community-based study.

We aimed to determine the association of family history of dementia with structural brain measures and cognitive performance in childhood and mid-life adulthood. We studied 1,259 parents (mean age: 47.3 years, range 31.9-67.4) and 866 of their children (mean age [range] at brain MRI: 9.9 years [8.8-11.9], and for cognition: 13.5 years [12.6-15.8]) of the population-based Generation R Study. Parents filled in a questionnaire on family history, and both parents and children underwent cognitive assessment and neuroimaging. Of all participants, 109 parents (8.6%) reported a parental family history of dementia and 73 children (8.4%) had a grandparental history of dementia with mean age of dementia diagnosis in those affected 75 years (± 7.3). We observed no associations of dementia family history with cognitive ability in either parents or their children, except for worse Purdue pegboard in parents with a parental history of dementia, compared to those without (mean difference [95%CI]: -1.23 [-2.15; -0.31], test range: 21-52). In parents and children, neuroimaging measures did not differ significantly by family history. Results did not depend on age, sex, and APOE genotype. Family history of dementia was associated with worse manual dexterity in mid-life adulthood, but not with any other measures of cognitive ability or subclinical brain health in childhood and mid-life. These findings suggest that the association of family history with dementia risk is due chiefly to neurodegenerative rather than neurodevelopmental processes, and might first present with reduced motor skills.

Data harmonization and federated learning for multi-cohort dementia research using the OMOP common data model: A Netherlands consortium of dementia cohorts case study.

BACKGROUND: Establishing collaborations between cohort studies has been fundamental for progress in health research. However, such collaborations are hampered by heterogeneous data representations across cohorts and legal constraints to data sharing. The first arises from a lack of consensus in standards of data collection and representation across cohort studies and is usually tackled by applying data harmonization processes. The second is increasingly important due to raised awareness for privacy protection and stricter regulations, such as the GDPR. Federated learning has emerged as a privacy-preserving alternative to transferring data between institutions through analyzing data in a decentralized manner. METHODS: In this study, we set up a federated learning infrastructure for a consortium of nine Dutch cohorts with appropriate data available to the etiology of dementia, including an extract, transform, and load (ETL) pipeline for data harmonization. Additionally, we assessed the challenges of transforming and standardizing cohort data using the Observational Medical Outcomes Partnership (OMOP) common data model (CDM) and evaluated our tool in one of the cohorts employing federated algorithms. RESULTS: We successfully applied our ETL tool and observed a complete coverage of the cohorts' data by the OMOP CDM. The OMOP CDM facilitated the data representation and standardization, but we identified limitations for cohort-specific data fields and in the scope of the vocabularies available. Specific challenges arise in a multi-cohort federated collaboration due to technical constraints in local environments, data heterogeneity, and lack of direct access to the data. CONCLUSION: In this article, we describe the solutions to these challenges and limitations encountered in our study. Our study shows the potential of federated learning as a privacy-preserving solution for multi-cohort studies that enhance reproducibility and reuse of both data and analyses.

Potential impact of unblinding on observed treatment effects in Alzheimer's disease trials.

INTRODUCTION: Adverse effects of monoclonal antibodies against amyloid beta are common, and may affect validity of randomized controlled trials (RCTs) through unblinding of participants. METHODS: We used observations from published phase 3 RCTs in Alzheimer's disease to calculate the magnitude of unblinding effects on cognition that would be required to explain observed cognitive benefits in RCTs. RESULTS: In trials of lecanemab, aducanumab, and donanemab, incidence of amyloid-related imaging abnormalities with active treatment ranged from 22% to 44%, the vast majority of which presumably led to unblinding. Effects of unblinding on the Clinical Dementia Rating Sum of Boxes required to fully explain observed drug effects ranged from 1.1 point (95% confidence interval: 0.2-2.0) with aducanumab, to 3.3 points (2.1-4.4) with donanemab and 3.7 points (2.0-5.6) with lecanemab. Infusion-related reactions were common, with potential unblinding effects particularly for lecanemab. Similar patterns were observed for the Alzheimer's Disease Assessment Scale Cognitive subscale. DISCUSSION: Psychological treatment effects due to unblinding may explain a substantial share of observed treatment effects in RCTs.

Antidepressant use in relation to dementia risk, cognitive decline, and brain atrophy.

INTRODUCTION: We aimed to assess the effect of antidepressant use on dementia risk, cognitive decline, and brain atrophy. METHODS: In this prospective cohort study, we included 5511 dementia-free participants (Mini-Mental State Examination [MMSE] > 25) of the Rotterdam study (57.5% women, mean age 70.6 years). Antidepressant use was extracted from pharmacy records from 1991 until baseline (2002-2008). Incident dementia was monitored from baseline until 2018, with repeated cognitive assessment and magnetic resonance imaging (MRI) every 4 years. RESULTS: Compared to never use, any antidepressant use was not associated with dementia risk (hazard ratio [HR] 1.14, 95% confidence interval [CI] 0.92-1.41), or with accelerated cognitive decline or atrophy of white and gray matter. Compared to never use, dementia risk was somewhat higher with tricyclic antidepressants (HR 1.36, 95% CI 1.01-1.83) than with selective serotonin reuptake inhibitors (HR 1.12, 95% CI 0.81-1.54), but without dose-response relationships, accelerated cognitive decline, or atrophy in either group. DISCUSSION: Antidepressant medication in adults without indication of cognitive impairment was not consistently associated with long-term adverse cognitive effects. HIGHLIGHTS: Antidepressant medications are frequently prescribed, especially among older adults. In this study, antidepressant use was not associated with long-term dementia risk. Antidepressant use was not associated with cognitive decline or brain atrophy. Our results support safe prescription in an older, cognitively healthy population.

Intracranial arteriosclerosis and the risk of dementia: A population-based cohort study.

BACKGROUND: The impact of intracranial arteriosclerosis on dementia remains largely unclear. METHODS: In 2339 stroke-free and dementia-free participants (52.2% women, mean age 69.5 years) from the general population, we assessed intracranial carotid artery calcification (ICAC) and vertebrobasilar artery calcification (VBAC) as proxy for arteriosclerosis. Associations with dementia were assessed using Cox models. In addition, indirect effects through cerebral small vessel disease (cSVD) and subcortical brain structure volumes were assessed using causal mediation analyses. RESULTS: During a median of 13.4 years (25th-75th percentiles 9.9-14.5) of follow-up, 282 participants developed dementia. Both ICAC presence (hazard ratio [HR]: 1.53, 95% confidence interval [CI]: 1.00-2.32]) and volume (HR per standard deviation: 1.19, 95% CI: 1.01-1.40) increased dementia risk. For VBAC, severe calcifications increased dementia risk (HR for third vs first volume tertile: 1.89, 95% CI: 1.00-3.59). These effects were mediated partly through increased cSVD (percentage mediated for ICAC: 13% and VBAC: 24%). DISCUSSION: Intracranial arteriosclerosis increases the risk of dementia.

Clearance of interstitial fluid (ISF) and CSF (CLIC) group-part of Vascular Professional Interest Area (PIA), updates in 2022-2023. Cerebrovascular disease and the failure of elimination of Amyloid-ß from the brain and retina with age and Alzheimer's disease: Opportunities for therapy.

This editorial summarizes advances from the Clearance of Interstitial Fluid and Cerebrospinal Fluid (CLIC) group, within the Vascular Professional Interest Area (PIA) of the Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment (ISTAART). The overarching objectives of the CLIC group are to: (1) understand the age-related physiology changes that underlie impaired clearance of interstitial fluid (ISF) and cerebrospinal fluid (CSF) (CLIC); (2) understand the cellular and molecular mechanisms underlying intramural periarterial drainage (IPAD) in the brain; (3) establish novel diagnostic tests for Alzheimer's disease (AD), cerebral amyloid angiopathy (CAA), retinal amyloid vasculopathy, amyloid-related imaging abnormalities (ARIA) of spontaneous and iatrogenic CAA-related inflammation (CAA-ri), and vasomotion; and (4) establish novel therapies that facilitate IPAD to eliminate amyloid ß (Aß) from the aging brain and retina, to prevent or reduce AD and CAA pathology and ARIA side events associated with AD immunotherapy.

Biomarkers of endothelial dysfunction and cognition: A two-step IPD meta-analysis.

INTRODUCTION: This study assessed the association of plasma biomarkers of endothelial dysfunction with cognitive performance and decline. METHODS: Data from 9414 individuals from eight Dutch cohorts were included (Ø  age-range: 57-93 years). Plasma biomarkers of endothelial dysfunction (soluble intercellular adhesion molecule-1 (sICAM-1), soluble vascular cell adhesion molecule-1 (sVCAM-1), soluble E-selectin) were combined into a standardized composite score. Cognitive outcomes included executive function, processing speed, immediate and delayed memory, attention, and language. Linear regressions and linear mixed models were run in the individual cohorts and standardized coefficients were subsequently pooled using random-effects meta-analyses. RESULTS: A higher endothelial dysfunction composite score was cross-sectionally associated with worse performance on executive function, processing speed, delayed memory, and attention, but not immediate memory or language (pooled ß-range: -0.04, -0.02). We found no association with change in cognition over time. DISCUSSION: This comprehensive two-step, individual participant data (IPD) meta-analysis showed a small, consistent cross-sectional association between endothelial dysfunction and worse cognitive performance across multiple domains but no support for a longitudinal association. HIGHLIGHTS: Prior evidence on endothelial dysfunction (ED) biomarkers and cognition is conflicting. This two-step, individual participant data (IPD) meta-analysis used data from eight Dutch cohorts. ED was consistently associated with concurrent cognition. ED was not associated with a change in cognition over time. The association of ED with current cognition may be generic.

Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities: A multicenter study in 3132 memory clinic patients.

INTRODUCTION: White matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-ß1-42 (Aß42)-positive status. METHODS: Individual patient data (n = 3,132; mean age 71.5 ± 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and Aß42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume. RESULTS: VRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p < 0.001), external capsule (B = 0.052, p < 0.001), and middle cerebellar peduncle (B = 0.067, p < 0.001), and Aß42-positive status with WMH in posterior thalamic radiation (B = 0.097, p < 0.001) and splenium (B = 0.103, p < 0.001). DISCUSSION: Vascular risk factors and Aß42 pathology have distinct signature WMH patterns. This regional vulnerability may incite future studies into how arteriolosclerosis and Aß42 pathology affect the brain's white matter. HIGHLIGHTS: Key dementia etiologies may be associated with specific patterns of white matter hyperintensities (WMH). We related WMH locations to vascular risk and cerebral Aß42 status in 11 memory clinic cohorts. Aß42 positive status was associated with posterior WMH in splenium and posterior thalamic radiation. Vascular risk was associated with anterior and infratentorial WMH. Amyloid pathology and vascular risk have distinct signature WMH patterns.

Cognitive Impairment in Patients With Cardiac Disease: Implications for Clinical Practice.

Cognitive impairment is common in patients with cardiovascular disease. One in 3 patients presenting at cardiology clinics have some degree of cognitive impairment, depending on the cardiac condition, comorbidities, and age. In up to half of these cases cognitive impairment may go unrecognized; however, it may affect self-management and treatment adherence. The high prevalence of cognitive impairment in patients with cardiac disease is likely due to shared risk factors, as well as direct consequences of cardiac dysfunction on the brain. Moreover, cardiac interventions may have beneficial as well as adverse effects on cognitive functioning. In this review, we describe prevalence and risk factors for cognitive impairment in patients with several common cardiac conditions: heart failure, coronary artery disease, and aortic valve stenosis. We discuss the potential effects of guideline-based treatments on cognition and identify open questions and unmet needs. Given the high prevalence of unrecognized cognitive impairment in cardiac patients, we recommend a stepwise approach to improve detection and management of cognitive impairment.

Effects of Eligibility Criteria on Patient Selection and Treatment Implications from 10 Multidomain Dementia Prevention Trials: A Population-Based Study.

INTRODUCTION: Dementia prevention trials have so far shown little benefit of multidomain interventions against cognitive decline. Recruitment strategies in these trials often centre around dementia risk or cardiovascular risk profile, but it is uncertain whether this leads to inclusion of individuals who may benefit most from the intervention. We determined the effects of eligibility criteria on the recruitment of potential trial participants in the general population. METHODS: In a systematic search until January 1, 2022, we identified all published and ongoing large (≥500 participants), phase-3 multidomain trials for the prevention of cognitive decline or dementia. We applied trial eligibility criteria to 5,381 participants of the population-based Rotterdam Study (mean age: 72 years, 58% women), to compare participant characteristics, predicted risk of cardiovascular disease, and dementia risk, between trial eligible and ineligible persons. RESULTS: We identified 10 trials, of which 5 had been published (DR's EXTRA, FINGER, preDIVA, MAPT, and HATICE) and 5 are ongoing (US-POINTER, MIND-CHINA, MYB, AgeWell.de, and J-Mint). Among all Rotterdam Study participants, eligibility across published trials ranged from 48% for MAPT to 87% for preDIVA, in line with original trial reports. Variability in eligibility was wider for ongoing trials, from 1% for US-POINTER to over 94% for MYB trial. Over 70% of trial eligible individuals are recommended preventive intervention in routine care based on their cardiovascular risk, similar for lipid-lowering (71%) and blood pressure-lowering treatment (73%). Ten-year risks of dementia were similar for eligible compared to ineligible individuals (12 vs. 11%). CONCLUSION: Multidomain dementia prevention trials fail to preferentially include those at the highest risk of dementia and mostly include individuals who qualify for interventions already on the basis of cardiovascular prevention guidelines. These findings call for better targeted enrolment of individuals for whom trial results can improve clinical decision-making.

Social Health and Change in Cognitive Capability among Older Adults: Findings from Four European Longitudinal Studies.

INTRODUCTION: In this study, we examine whether social health markers measured at baseline are associated with differences in cognitive capability and the rate of cognitive decline over an 11-to-18-year period among older adults and compare results across studies. METHODS: We applied an integrated data analysis approach to 16,858 participants (mean age 65 years; 56% female) from the National Survey for Health and Development (NSHD), the English Longitudinal Study of Aging (ELSA), the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K), and the Rotterdam Study. We used multilevel models to examine social health in relation to cognitive capability and the rate of cognitive decline. RESULTS: Pooled estimates show distinct relationships between markers of social health and cognitive domains, e.g., a large network size (≥6 people vs. none) was associated with higher executive function (0.17 standard deviation [SD] [95% CI: 0.00, 0.34], I2 = 27%) but not with memory (0.08 SD [95% CI: -0.02, 0.18], I2 = 19%). We also observed pooled associations between being married or cohabiting, having a large network size, and participating in social activities with slower decline in cognitive capability. However, estimates were close to zero, e.g., 0.01 SD/year (95% CI: 0.01, 0.02) I2 = 19% for marital status and executive function. There were clear study-specific differences: results for average processing speed were the most homogenous, and results for average memory were the most heterogeneous. CONCLUSION: Overall, markers of good social health have a positive association with cognitive capability. However, we found differential associations between specific markers of social health and cognitive domains and differences between studies. These findings highlight the importance of examining between-study differences and considering the context specificity of findings in developing and deploying interventions.

Projections of costs and quality adjusted life years lost due to dementia from 2020 to 2050: A population-based microsimulation study.

INTRODUCTION: Efficient healthcare planning requires reliable projections of the future increase in costs and quality-adjusted life years (QALYs) lost due to dementia. METHODS: We used the microsimulation model MISCAN-Dementia to simulate life histories and dementia occurrence using population-based Rotterdam Study data and nationwide birth cohort demographics. We estimated costs and QALYs lost in the Netherlands from 2020 to 2050, incorporating literature estimates of cost and utility for patients and caregivers by dementia severity and care setting. RESULTS: Societal costs and QALYs lost due to dementia are estimated to double between 2020 and 2050. Costs are incurred predominantly through institutional (34%), formal home (31%), and informal home care (20%). Lost QALYs are mostly due to shortened life expectancy (67%) and, to a lesser extent, quality of life with severe dementia (14%). DISCUSSION: To limit healthcare costs and quality of life losses due to dementia, interventions are needed that slow symptom progression and reduce care dependency.

Strategic white matter hyperintensity locations for cognitive impairment: A multicenter lesion-symptom mapping study in 3525 memory clinic patients.

INTRODUCTION: Impact of white matter hyperintensities (WMH) on cognition likely depends on lesion location, but a comprehensive map of strategic locations is lacking. We aimed to identify these locations in a large multicenter study. METHODS: Individual patient data (n = 3525) from 11 memory clinic cohorts were harmonized. We determined the association of WMH location with attention and executive functioning, information processing speed, language, and verbal memory performance using voxel-based and region of interest tract-based analyses. RESULTS: WMH in the left and right anterior thalamic radiation, forceps major, and left inferior fronto-occipital fasciculus were significantly related to domain-specific impairment, independent of total WMH volume and atrophy. A strategic WMH score based on these tracts inversely correlated with performance in all domains. DISCUSSION: The data show that the impact of WMH on cognition is location-dependent, primarily involving four strategic white matter tracts. Evaluation of WMH location may support diagnosing vascular cognitive impairment. HIGHLIGHTS: We analyzed white matter hyperintensities (WMH) in 3525 memory clinic patients from 11 cohorts The impact of WMH on cognition depends on location We identified four strategic white matter tracts A single strategic WMH score was derived from these four strategic tracts The strategic WMH score was an independent determinant of four cognitive domains.

Validity of stroke severity assessment using medical records in a population-based cohort.

OBJECTIVES: Stroke severity is an important prognostic indicator of morbidity and mortality, but often not recorded outside of specialised stroke centres. We aimed to develop a scoring rule and validate standardised assessment of the National Institutes of Health Stroke Scale (NIHSS) from medical records. METHODS: We developed a standardised assessment of the NIHSS from medical records. Four trained raters independently assessed the charts of 100 patients with first-ever stroke, randomly selected from the population-based Rotterdam Study cohort. Interrater agreement was determined using the intraclass correlation coefficient (ICC), and Fleiss' kappa for major versus minor stroke. We validated the scoring method against 29 prospective, clinical NIHSS ratings, using Kendall's tau and Cohen's kappa. RESULTS: Of 100 included patients with stroke (mean age 80 years, 62% women), 71 (71%) were admitted to hospital and 9 (9%) were seen in outpatient clinic, whereas 20 (20%) were treated exclusively by their general practitioner or nursing home physician. Interrater agreement for retrospective, chart-based NIHSS ratings was excellent when assessed continuously (ICC: 0.90), and for minor versus major stroke (for NIHSS>3: κ=0.79, NIHSS>5: κ=0.78). Interrater agreement was good both for hospital-based and out-of-hospital settings (ICC: 0.97 and 0.75 respectively). Overall, assessment from medical records was in excellent agreement with prospective NIHSS ratings (τ=0.83; NIHSS>3: κ=0.93, and NIHSS>5: κ=0.93). However, for severe stroke (NIHSS>10) retrospective assessment tended to underestimate severity by 1-3 points on the NIHSS, which was accompanied by a somewhat lower interrater agreement for those more severe cases (NIHSS>10: κ=0.62). CONCLUSIONS: Assessment of stroke severity according to the NIHSS on the basis of medical records is feasible and reliable in population-based cohorts of patients with stroke. These findings facilitate more individualised risk estimates in observational studies that lack prospective ascertainment of stroke severity.

Risk factors, neuroimaging correlates and prognosis of the motoric cognitive risk syndrome: A population-based comparison with mild cognitive impairment.

BACKGROUND AND PURPOSE: This study was undertaken to compare risk factors, neuroimaging characteristics and prognosis between two clinical prodromes of dementia, namely, the motoric cognitive risk syndrome (MCRS) and mild cognitive impairment (MCI). METHODS: Between 2009 and 2015, dementia-free participants of the population-based Rotterdam Study were classified with a dementia prodrome if they had subjective cognitive complaints and scored >1 SD below the population mean of gait speed (MCRS) or >1.5 SD below the population mean of cognitive test scores (MCI). Using multinomial logistic regression models, we determined cross-sectional associations of risk factors and structural neuroimaging markers with MCRS and MCI, followed by subdistribution hazard models, to determine risk of incident dementia until 2016. RESULTS: Of 3025 included participants (mean age = 70.4 years, 54.7% women), 231 had MCRS (7.6%), 132 had MCI (4.4%), and 62 (2.0%) fulfilled criteria for both. Although many risk factors were shared, a higher body mass index predisposed to MCRS, whereas male sex and hypercholesterolemia were associated with MCI only. Gray matter volumes, hippocampal volumes, white matter hyperintensities, and structural white matter integrity were worse in both MCRS and MCI. During a mean follow-up of 3.9 years, 71 individuals developed dementia and 200 died. Five-year cumulative risk of dementia was 7.0% (2.5%-11.5%) for individuals with MCRS, versus 13.3% (5.8%-20.8%) with MCI and only 2.3% (1.5%-3.1%) in unaffected individuals. CONCLUSIONS: MCRS is associated with imaging markers of neurodegeneration and risk of dementia, even in the absence of MCI, highlighting the potential of motor function assessment in early risk stratification for dementia.

Projected prevalence and incidence of dementia accounting for secular trends and birth cohort effects: a population-based microsimulation study.

There is need for accurate projections of the future dementia burden to prepare healthcare systems and policymakers. Existing projections only account for population ageing, not for observed declines in age-specific dementia incidence of 13% per decade. We developed a dementia microsimulation model that synthesizes population-based data from the Rotterdam Study with changes in demographics between birth cohorts from the early 1900s onwards. We determined dementia prevalence and incidence until 2050 for three different dementia incidence trend scenarios: (1) stable age-specific incidence, (2) linear decline by 13% per decade, (3) nonlinear declines averaging 13% per decade. Assuming a stable age-specific incidence resulted in a 130% increase in incidence and 118% in prevalence between 2020 and 2050. By contrast, the linearly declining trend resulted in substantially smaller increases of 58% in incidence (95%CI: 29-87%), and 43% in prevalence (95%CI: 13-66%), corresponding to 39% lower incidence and 36% lower prevalence by 2050 than in the stable-incidence scenario. Results for various non-linear declines fell between the stable and linear trend. The future burden of dementia is highly susceptible to achievable changes in age-specific incidence. Extension of previously established secular trends globally would reduce widely upheld projections of new dementia cases until 2050 by 39%.

Prevalence and determinants of healthcare avoidance during the COVID-19 pandemic: A population-based cross-sectional study.

BACKGROUND: During the Coronavirus Disease 2019 (COVID-19) pandemic, the number of consultations and diagnoses in primary care and referrals to specialist care declined substantially compared to prepandemic levels. Beyond deferral of elective non-COVID-19 care by healthcare providers, it is unclear to what extent healthcare avoidance by community-dwelling individuals contributed to this decline in routine healthcare utilisation. Moreover, it is uncertain which specific symptoms were left unheeded by patients and which determinants predispose to healthcare avoidance in the general population. In this cross-sectional study, we assessed prevalence of healthcare avoidance during the pandemic from a patient perspective, including symptoms that were left unheeded, as well as determinants of healthcare avoidance. METHODS AND FINDINGS: On April 20, 2020, a paper COVID-19 survey addressing healthcare utilisation, socioeconomic factors, mental and physical health, medication use, and COVID-19-specific symptoms was sent out to 8,732 participants from the population-based Rotterdam Study (response rate 73%). All questionnaires were returned before July 10, 2020. By hand, prevalence of healthcare avoidance was subsequently verified through free text analysis of medical records of general practitioners. Odds ratios (ORs) for avoidance were determined using logistic regression models, adjusted for age, sex, and history of chronic diseases. We found that 1,142 of 5,656 included participants (20.2%) reported having avoided healthcare. Of those, 414 participants (36.3%) reported symptoms that potentially warranted urgent evaluation, including limb weakness (13.6%), palpitations (10.8%), and chest pain (10.2%). Determinants related to avoidance were older age (adjusted OR 1.14 [95% confidence interval (CI) 1.08 to 1.21]), female sex (1.58 [1.38 to 1.82]), low educational level (primary education versus higher vocational/university 1.21 [1.01 to 1.46), poor self-appreciated health (per level decrease 2.00 [1.80 to 2.22]), unemployment (versus employed 2.29 [1.54 to 3.39]), smoking (1.34 [1.08 to 1.65]), concern about contracting COVID-19 (per level increase 1.28 [1.19 to 1.38]) and symptoms of depression (per point increase 1.13 [1.11 to 1.14]) and anxiety (per point increase 1.16 [1.14 to 1.18]). Study limitations included uncertainty about (perceived) severity of the reported symptoms and potentially limited generalisability given the ethnically homogeneous study population. CONCLUSIONS: In this population-based cross-sectional study, 1 in 5 individuals avoided healthcare during lockdown in the COVID-19 pandemic, often for potentially urgent symptoms. Healthcare avoidance was strongly associated with female sex, fragile self-appreciated health, and high levels of depression and anxiety. These results emphasise the need for targeted public education urging these vulnerable patients to timely seek medical care for their symptoms to mitigate major health consequences.