Alzheimers Dement

INTRODUCTION: Inferring the timeline from mild cognitive impairment (MCI) to severe dementia is pivotal for patients, clinicians, and researchers. Literature is sparse and often contains few patients. We aim to determine the time spent in MCI, mild-, moderate-, severe dementia, and institutionalization until death. METHODS: Multistate modeling with Cox regression was used to obtain the sojourn time. Covariates were age at baseline, sex, amyloid status, and Alzheimer's disease (AD) or other dementia diagnosis. The sample included a register (SveDem) and memory clinics (Amsterdam Dementia Cohort and Memento). RESULTS: Using 80,543 patients, the sojourn time from clinically identified MCI to death across all patient groups ranged from 6.20 (95% confidence interval [CI]: 5.57-6.98) to 10.08 (8.94-12.18) years. DISCUSSION: Generally, sojourn time was inversely associated with older age at baseline, males, and AD diagnosis. The results provide key estimates for researchers and clinicians to estimate prognosis

Lower cerebral blood flow in subjects with Alzheimer's dementia, mild cognitive impairment, and subjective cognitive decline using two-dimensional phase-contrast magnetic resonance imaging

Introduction In this cross-sectional study, we aimed to detect differences in cerebral blood flow (CBF) between subjects with Alzheimer's disease (AD), mild cognitive impairment (MCI), and subjective cognitive decline (SCD), using two-dimensional phase-contrast magnetic resonance imaging. Methods We included 74 AD patients (67 years, 51% female), 36 MCI patients (66 years, 33% female), and 62 patients with SCD (60 years, 32% female) from the Amsterdam Dementia Cohort. Patients with SCD are those who visited the memory clinic with subjective cognitive complaints without objective cognitive impairment. Whole-brain CBF (mL/100 g/min) was calculated using total volume flow measured with two-dimensional phase-contrast magnetic resonance imaging and normalized for brain volume. Results Mean CBF values (SD) were lower in AD compared to SCD (age and sex adjusted 70 ± 26 vs. 82 ± 24 mL/100 g/min, P <.05). Mean CBF values of MCI were comparable to AD. Across clinical groups, lower CBF was associated with lower scores on the Mini–Mental State Examination (age and sex adjusted stβ = 0.19 per mL/100 g/min; P =.02). Discussion Lower whole-brain CBF is seen in AD patients compared to SCD patients and is associated with worse cognitive function

Steeper memory decline after COVID-19 lockdown measures

BACKGROUND: During COVID-19 lockdown measures, memory clinic patients reported worries for faster cognitive decline, due to loss of structure and feelings of loneliness and depression. We aimed to investigate the impact of the COVID-19 lockdown on rate of cognitive decline in a mixed memory clinic population, compared to matched historical controls. METHODS: We included patients who visited Alzheimer Center Amsterdam 6 months to 1 week before the first Dutch COVID-19 lockdown, and had a second visit 1 year later, after this lockdown period (n = 113; 66 ± 7 years old; 30% female; n = 55 dementia, n = 31 mild cognitive impairment (MCI), n = 18 subjective cognitive decline (SCD), n = 9 postponed diagnosis). Historical controls (visit in 2016/2017 and second visit 1 year later (n = 640)) were matched 1:1 to lockdown patients by optimal Mahalanobis distance matching (both groups n = 113). Groups were well matched. Differences between lockdown patients and historical controls over time in Mini-Mental State Examination, Trail Making Test part A and B, Rey-Auditory Verbal Learning Test (RAVLT) immediate and delayed recall, and category fluency scores were analyzed using linear mixed effect models with random intercepts. We examined differences in rate of cognitive decline between whole groups, and after stratification in SCD, MCI, and dementia separately. RESULTS: Lockdown patients had a faster rate of memory decline compared to controls on both RAVLT immediate [B(SE) =  - 2.62 (1.07), p = 0.015] and delayed recall [B(SE) =  - 1.07 (0.34), p = 0.002]. Stratification by syndrome diagnosis showed that this effect was largely attributable to non-demented participants, as we observed faster memory decline during lockdown in SCD and MCI (RAVLT immediate [SCD: B(SE) =  - 6.85 (2.97), p = 0.027; MCI: B(SE) =  - 6.14 (1.78), p = 0.001] and delayed recall [SCD: B(SE) =  - 2.45 (1.11), p = 0.035; MCI: B(SE) =  - 1.50 (0.51), p = 0.005]), but not in dementia. CONCLUSION: Memory clinic patients, specifically in pre-dementia stages, showed faster memory decline during COVID-19 lockdown, providing evidence that lockdown regulations had a deleterious effect on brain health. In individuals that may have been able to deal with accumulating, subclinical neuropathology under normal and structured circumstances, the additional stress of lockdown regulations may have acted as a "second hit," resulting in less beneficial disease trajectory

ABIDE Delphi study: Topics to discuss in diagnostic consultations in memory clinics

Background: Information given to patients and caregivers during the clinician-patient encounter varies considerably between memory clinic professionals. Patients and caregivers express a clear desire for more information. It is unclear what information patients and caregivers value most during the diagnostic process and whether this is concordant with professionals' opinion. We aimed to identify a topic list on which health care professionals, patients, and caregivers agree that these should be discussed during diagnostic consultations in memory clinics. Further, we aimed to establish the optimal moment for each topic to be discussed during the diagnostic process. Methods: We performed a three-round Delphi consensus study. Professionals (N = 80), patients (N = 66), and caregivers (N = 76) rated the importance of 44 informative topics through an online questionnaire. Consensus was defined as a topic rating of 6 or 7 on a 7-point Likert scale by ≥ 75% of each panel. In round 2 and 3, a survey was added to identify the optimal moment during the diagnostic process to discuss each topic. Results: By round 3, consensus was achieved on 17 topics divided into four categories, information about (1) diagnostic testing, (2) test results, (3) diagnosis, and (4) practical implications. Eight additional topics showed significant differences between panels. Most notable panel differences regard the risk for developing dementia and the distinction between Alzheimer's disease and dementia, which patients and caregivers evaluated as more important compared to professionals. The optimal moment to discuss topics during the diagnostic process was identified for the 17 core topics, and the eight topics with significant differences. Conclusions: We present a core list of informative topics, which professionals, patients, and caregivers agree they should be discussed during the diagnostic process in a memory clinic. The topic list can support professionals and empower patients and caregivers during diagnostic physician-patient consultations

A more precise diagnosis by means of amyloid PET contributes to delayed institutionalization, lower mortality, and reduced care costs in a tertiary memory clinic setting

Introduction: We aim to study the effect of a more precise diagnosis, by means of amyloid positron emission tomography (PET), on institutionalization, mortality, and health-care costs. Methods: Between October 27, 2014 and December 31, 2016, we offered amyloid PET to all patients as part of their diagnostic work-up. Patients who accepted to undergo amyloid PET (n = 449) were propensity score matched with patients without amyloid PET (n = 571, i.e., no PET). Matched groups (both n = 444) were compared on rate of institutionalization, mortality, and health-care costs in the years after diagnosis. Results: Amyloid PET patients had a lower risk of institutionalization (10% [n = 45] vs. 21% [n = 92]; hazard ratio [HR] = 0.48 [0.33–0.70]) and mortality rate (11% [n = 49] vs. 18% [n = 81]; HR = 0.51 [0.36–0.73]) and lower health-care costs in the years after diagnosis compared to matched no-PET patients (β = −4573.49 [−6524.76 to −2523.74], P-value < 0.001). Discussion: A more precise diagnosis in tertiary memory clinic patients positively influenced the endpoints of institutionalization, death, and health-care costs

A more precise diagnosis by means of amyloid PET contributes to delayed institutionalization, lower mortality, and reduced care costs in a tertiary memory clinic setting

INTRODUCTION: We aim to study the effect of a more precise diagnosis, by means of amyloid positron emission tomography (PET), on institutionalization, mortality, and health-care costs. METHODS: Between October 27, 2014 and December 31, 2016, we offered amyloid PET to all patients as part of their diagnostic work-up. Patients who accepted to undergo amyloid PET (n = 449) were propensity score matched with patients without amyloid PET (n = 571, i.e., no PET). Matched groups (both n = 444) were compared on rate of institutionalization, mortality, and health-care costs in the years after diagnosis. RESULTS: Amyloid PET patients had a lower risk of institutionalization (10% [n = 45] vs. 21% [n = 92]; hazard ratio [HR] = 0.48 [0.33-0.70]) and mortality rate (11% [n = 49] vs. 18% [n = 81]; HR = 0.51 [0.36-0.73]) and lower health-care costs in the years after diagnosis compared to matched no-PET patients (β = -4573.49 [-6524.76 to -2523.74], P-value < 0.001). DISCUSSION: A more precise diagnosis in tertiary memory clinic patients positively influenced the endpoints of institutionalization, death, and health-care costs

Psychosocial Effects of Corona Measures on Patients With Dementia, Mild Cognitive Impairment and Subjective Cognitive Decline

Background: The recent COVID-19 pandemic is not only a major healthcare problem in itself, but also poses enormous social challenges. Though nursing homes increasingly receive attention, the majority of people with cognitive decline and dementia live at home. We aimed to explore the psychosocial effects of corona measures in memory clinic (pre-)dementia patients and their caregivers. Methods: Between April 28th and July 13th 2020, n = 389 patients of Alzheimer center Amsterdam [n = 121 symptomatic (age = 69 ± 6, 33%F, MMSE = 23 ± 5), n = 268 cognitively normal (age = 66 ± 8, 40% F, MMSE = 29 ± 1)] completed a survey on psychosocial effects of the corona measures. Questions related to social isolation, worries for faster cognitive decline, behavioral problems and discontinuation of care. In addition, n = 147 caregivers of symptomatic patients completed a similar survey with additional questions on caregiver burden. Results: Social isolation was experienced by n = 42 (35%) symptomatic and n = 67 (25%) cognitively normal patients and two third of patients [n = 129 (66%); n = 58 (75%) symptomatic, n = 71 (61%) cognitively normal] reported that care was discontinued. Worries for faster cognitive decline were existed in symptomatic patients [n = 44 (44%)] and caregivers [n = 73 (53%)], but were also reported by a subgroup of cognitively normal patients [n = 27 (14%)]. Both patients [n = 56 (46%) symptomatic, n = 102 (38%) cognitively normal] and caregivers [n = 72 (48%)] reported an increase in psychological symptoms. More than three quarter of caregivers [n = 111(76%)] reported an increase in patients' behavioral problems. A higher caregiver burden was experienced by n = 69 (56%) of caregivers and n = 43 (29%) of them reported that a need for more support. Discontinuation of care (OR = 3.3 [1.3–7.9]), psychological (OR = 4.0 [1.6–9.9]) and behavioral problems (OR = 3.0 [1.0–9.0]) strongly related to experiencing a higher caregiver burden. Lastly, social isolation (OR = 3.2 [1.2–8.1]) and psychological symptoms (OR = 8.1 [2.8–23.7]) were red flags for worries for faster cognitive decline. Conclusion: Not only symptomatic patients, but also cognitively normal patients express worries for faster cognitive decline and psychological symptoms. Moreover, we identified patients who are at risk of adverse outcomes of the corona measures, i.e., discontinued care, social isolation, psychological and behavioral problems. This underlines the need for health care professionals to provide ways to warrant the continuation of care and support (informal) networks surrounding patients and caregivers to mitigate the higher risk of negative psychosocial effects

Development of multivariable prediction models for institutionalization and mortality in the full spectrum of Alzheimer's disease

International audienceBACKGROUND: Patients and caregivers express a desire for accurate prognostic information about time to institutionalization and mortality. Previous studies predicting institutionalization and mortality focused on the dementia stage. However, Alzheimer's disease (AD) is characterized by a long pre-dementia stage. Therefore, we developed prediction models to predict institutionalization and mortality along the AD continuum of cognitively normal to dementia.METHODS: This study included SCD/MCI patients (subjective cognitive decline (SCD) or mild cognitive impairment (MCI)) and patients with AD dementia from the Amsterdam Dementia Cohort. We developed internally and externally validated prediction models with biomarkers and without biomarkers, stratified by dementia status. Determinants were selected using backward selection (p<0.10). All models included age and sex. Discriminative performance of the models was assessed with Harrell's C statistics.RESULTS: We included n=1418 SCD/MCI patients (n=123 died, n=74 were institutionalized) and n=1179 patients with AD dementia (n=413 died, n=453 were institutionalized). For both SCD/MCI and dementia stages, the models for institutionalization and mortality included after backward selection clinical characteristics, imaging, and cerebrospinal fluid (CSF) biomarkers. In SCD/MCI, the Harrell's C-statistics of the models were 0.81 (model without biomarkers: 0.76) for institutionalization and 0.79 (model without biomarker: 0.76) for mortality. In AD-dementia, the Harrell's C-statistics of the models were 0.68 (model without biomarkers: 0.67) for institutionalization and 0.65 (model without biomarker: 0.65) for mortality. Models based on data from amyloid-positive patients only had similar discrimination.CONCLUSIONS: We constructed prediction models to predict institutionalization and mortality with good accuracy for SCD/MCI patients and moderate accuracy for patients with AD dementia. The developed prediction models can be used to provide patients and their caregivers with prognostic information on time to institutionalization and mortality along the cognitive continuum of AD

Development of multivariable prediction models for institutionalization and mortality in the full spectrum of Alzheimer's disease

Background: Patients and caregivers express a desire for accurate prognostic information about time to institutionalization and mortality. Previous studies predicting institutionalization and mortality focused on the dementia stage. However, Alzheimer’s disease (AD) is characterized by a long pre-dementia stage. Therefore, we developed prediction models to predict institutionalization and mortality along the AD continuum of cognitively normal to dementia. Methods: This study included SCD/MCI patients (subjective cognitive decline (SCD) or mild cognitive impairment (MCI)) and patients with AD dementia from the Amsterdam Dementia Cohort. We developed internally and externally validated prediction models with biomarkers and without biomarkers, stratified by dementia status. Determinants were selected using backward selection (p<0.10). All models included age and sex. Discriminative performance of the models was assessed with Harrell’s C statistics. Results: We included n=1418 SCD/MCI patients (n=123 died, n=74 were institutionalized) and n=1179 patients with AD dementia (n=413 died, n=453 were institutionalized). For both SCD/MCI and dementia stages, the models for institutionalization and mortality included after backward selection clinical characteristics, imaging, and cerebrospinal fluid (CSF) biomarkers. In SCD/MCI, the Harrell’s C-statistics of the models were 0.81 (model without biomarkers: 0.76) for institutionalization and 0.79 (model without biomarker: 0.76) for mortality. In AD-dementia, the Harrell’s C-statistics of the models were 0.68 (model without biomarkers: 0.67) for institutionalization and 0.65 (model without biomarker: 0.65) for mortality. Models based on data from amyloid-positive patients only had similar discrimination. Conclusions: We constructed prediction models to predict institutionalization and mortality with good accuracy for SCD/MCI patients and moderate accuracy for patients with AD dementia. The developed prediction models can be used to provide patients and their caregivers with prognostic information on time to institutionalization and mortality along the cognitive continuum of AD