Calcium channel blockers, survival and ischaemic stroke in patients with dementia: a Swedish registry study.

BACKGROUND: The effect of calcium channel blockers (CCB) on mortality and ischaemic stroke risk in dementia patients is understudied. OBJECTIVES: To calculate the risk of death and ischaemic stroke in dementia patients treated with CCBs, considering individual agents and dose response. METHODS: Longitudinal cohort study with 18 906 hypertensive dementia patients from the Swedish Dementia Registry (SveDem), 2008-2014. Other Swedish national registries contributed information on comorbidities, dispensed medication and outcomes. Individual CCB agents and cumulative defined daily doses (cDDD) were considered. RESULTS: In patients with hypertension and dementia, nifedipine was associated with increased mortality risk (aHR 1.32; CI 1.01-1.73; P < 0.05) compared to non-CCB users. Patients diagnosed with Alzheimer's dementia (AD) or dementia with Lewy bodies/Parkinson's disease dementia (DLB-PDD) taking amlodipine had lower mortality risk (aHR, 0.89; CI, 0.80-0.98; P < 0.05 and aHR 0.58; CI, 0.38-0.86; P < 0.01, respectively), than those taking other CCBs. Amlodipine was associated with lower stroke risk in patients with Alzheimer's dementia compared to other CCBs (aHR 0.63; CI, 0.44-0.89; P < 0.05). Sensitivity analyses with propensity score-matched cohorts repeated the results for nifedipine (aHR 1.35; 95% CI, 1.02-1.78; P < 0.05) and amlodipine in AD (aHR, 0.87; CI, 0.78-0.97; P < 0.05) and DLB-PDD (aHR, 0.56, 95%CI, 0.37-0.85; P < 0.05). CONCLUSION: Amlodipine was associated with reduced mortality risk in dementia patients diagnosed with AD and DLB-PDD. AD patients using amlodipine had a lower risk of ischaemic stroke compared to other CCB users.

A European Academy of Neurology guideline on medical management issues in dementia.

BACKGROUND AND PURPOSE: Dementia is one of the most common disorders and is associated with increased morbidity, mortality and decreased quality of life. The present guideline addresses important medical management issues including systematic medical follow-up, vascular risk factors in dementia, pain in dementia, use of antipsychotics in dementia and epilepsy in dementia. METHODS: A systematic review of the literature was carried out. Based on the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) framework, we developed a guideline. Where recommendations based on GRADE were not possible, a good practice statement was formulated. RESULTS: Systematic management of vascular risk factors should be performed in patients with mild to moderate dementia as prevention of cerebrovascular pathology may impact on the progression of dementia (Good Practice statement). Individuals with dementia (without previous stroke) and atrial fibrillation should be treated with anticoagulants (weak recommendation). Discontinuation of opioids should be considered in certain individuals with dementia (e.g. for whom there are no signs or symptoms of pain or no clear indication, or suspicion of side effects; Good Practice statement). Behavioral symptoms in persons with dementia should not be treated with mild analgesics (weak recommendation). In all patients with dementia treated with opioids, assessment of the individual risk-benefit ratio should be performed at regular intervals. Regular, preplanned medical follow-up should be offered to all patients with dementia. The setting will depend on the organization of local health services and should, as a minimum, include general practitioners with easy access to dementia specialists (Good Practice statement). Individuals with dementia and agitation and/or aggression should be treated with atypical antipsychotics only after all non-pharmacological measures have been proven to be without benefit or in the case of severe self-harm or harm to others (weak recommendation). Antipsychotics should be discontinued after cessation of behavioral disturbances and in patients in whom there are side effects (Good Practice statement). For treatment of epilepsy in individuals with dementia, newer anticonvulsants should be considered as first-line therapy (Good Practice statement). CONCLUSION: This GRADE-based guideline offers recommendations on several important medical issues in patients with dementia, and thus adds important guidance for clinicians. For some issues, very little or no evidence was identified, highlighting the importance of further studies within these areas.

Connecting the brain cholesterol and renin-angiotensin systems: potential role of statins and RAS-modifying medications in dementia.

Millions of people worldwide receive agents targeting the renin-angiotensin system (RAS) to treat hypertension or statins to lower cholesterol. The RAS and cholesterol metabolic pathways in the brain are autonomous from their systemic counterparts and are interrelated through the cholesterol metabolite 27-hydroxycholesterol (27-OHC). These systems contribute to memory and dementia pathogenesis through interference in the amyloid-beta cascade, vascular mechanisms, glucose metabolism, apoptosis, neuroinflammation and oxidative stress. Previous studies examining the relationship between these treatments and cognition and dementia risk have produced inconsistent results. Defining the blood-brain barrier penetration of these medications has been challenging, and the mechanisms of action on cognition are not clearly established. Potential biases are apparent in epidemiological and clinical studies, such as reverse epidemiology, indication bias, problems defining medication exposure, uncertain and changing doses, and inappropriate grouping of outcomes and medications. This review summarizes current knowledge of the brain cholesterol and RAS metabolism and the mechanisms by which these pathways affect neurodegeneration. The putative mechanisms of action of statins and medications inhibiting the RAS will be examined, together with prior clinical and animal studies on their effects on cognition. We review prior epidemiological studies, analysing their strengths and biases, and identify areas for future research. Understanding the pathophysiology of the brain cholesterol system and RAS and their links to neurodegeneration has enormous potential. In future, well-designed epidemiological studies could identify potential treatments for Alzheimer's disease (AD) amongst medications that are already in use for other indications.

Biochemical markers in vascular cognitive impairment associated with subcortical small vessel disease - A consensus report.

BACKGROUND: Vascular cognitive impairment (VCI) is a heterogeneous entity with multiple aetiologies, all linked to underlying vascular disease. Among these, VCI related to subcortical small vessel disease (SSVD) is emerging as a major homogeneous subtype. Its progressive course raises the need for biomarker identification and/or development for adequate therapeutic interventions to be tested. In order to shed light in the current status on biochemical markers for VCI-SSVD, experts in field reviewed the recent evidence and literature data. METHOD: The group conducted a comprehensive search on Medline, PubMed and Embase databases for studies published until 15.01.2017. The proposal on current status of biochemical markers in VCI-SSVD was reviewed by all co-authors and the draft was repeatedly circulated and discussed before it was finalized. RESULTS: This review identifies a large number of biochemical markers derived from CSF and blood. There is a considerable overlap of VCI-SSVD clinical symptoms with those of Alzheimer's disease (AD). Although most of the published studies are small and their findings remain to be replicated in larger cohorts, several biomarkers have shown promise in separating VCI-SSVD from AD. These promising biomarkers are closely linked to underlying SSVD pathophysiology, namely disruption of blood-CSF and blood-brain barriers (BCB-BBB) and breakdown of white matter myelinated fibres and extracellular matrix, as well as blood and brain inflammation. The leading biomarker candidates are: elevated CSF/blood albumin ratio, which reflects BCB/BBB disruption; altered CSF matrix metalloproteinases, reflecting extracellular matrix breakdown; CSF neurofilment as a marker of axonal damage, and possibly blood inflammatory cytokines and adhesion molecules. The suggested SSVD biomarker deviations contrasts the characteristic CSF profile in AD, i.e. depletion of amyloid beta peptide and increased phosphorylated and total tau. CONCLUSIONS: Combining SSVD and AD biomarkers may provide a powerful tool to identify with greater precision appropriate patients for clinical trials of more homogeneous dementia populations. Thereby, biomarkers might promote therapeutic progress not only in VCI-SSVD, but also in AD.

Management of acute ischaemic stroke in patients with dementia.

An estimated 10% of stroke patients have an underlying dementia. As a consequence, health professionals often face the challenge of managing patients with dementia presenting with an acute stroke. Patients with dementia are less likely to receive thrombolysis (0.56-10% vs. 1-16% thrombolysis rates in the general population), be admitted to a stroke unit or receive some types of care. Anticoagulation for secondary stroke prevention is sometimes withheld, despite dementia not being listed as an exclusion criterion in current guidelines. Studies in this population are scarce, and results have been contradictory. Three observational studies have examined intravenous thrombolysis for treatment of acute ischaemic stroke in patients with dementia. In the two largest matched case-control studies, there were no significant differences between patients with and without dementia in the risks of intracerebral haemorrhage or mortality. The risk of intracerebral haemorrhage ranged between 14% and 19% for patients with dementia. Studies of other interventions for stroke are lacking for this population. Patients with dementia are less likely to be discharged home compared with controls (19% vs. 41%) and more likely to be disabled (64% vs. 59%) or die during hospitalization (22% vs. 11%). The aim of this review was to summarize current knowledge about the management of ischaemic stroke in patients with pre-existing dementia, including organizational aspects of stroke care, intravenous thrombolysis, access to stroke unit care and use of supportive treatment. Evidence to support anticoagulation for secondary prevention of stroke in patients with atrial fibrillation and antiplatelet therapy in nonembolic stroke will be discussed, as well as rehabilitation and how these factors influence patient outcomes. Finally, ethical issues, knowledge gaps and pathways for future research will be considered.

MMSE and MoCA in Parkinson's disease and dementia with Lewy bodies: a multicenter 1-year follow-up study.

The Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) are the most commonly used scales to test cognitive impairment in Lewy body disease (LBD), but there is no consensus on which is best suited to assess cognition in clinical practice and most sensitive to cognitive decline. Retrospective cohort study of 265 LBD patients [Parkinson's disease (PD) without dementia (PDnD, N = 197), PD with dementia (PDD, N = 40), and dementia with Lewy bodies (DLB, N = 28)] from an international consortium who completed both the MMSE and MoCA at baseline and 1-year follow-up (N = 153). Percentage of relative standard deviation (RSD%) at baseline was the measure of inter-individual variance, and estimation of change (Cohen's d) over time was calculated. RSD% for the MoCA (21 %) was greater than for the MMSE (13 %) (p = 0.03) in the whole group. This difference was significant only in PDnD (11 vs. 5 %, p < 0.01), but not in PDD (30 vs. 19 %, p = 0.37) or DLB (15 vs. 14 %, p = 0.78). In contrast, the 1-year estimation of change did not differ between the two tests in any of the groups (Cohen's effect <0.20 in each group). MMSE and MoCA are equal in measuring the rate of cognitive changes over time in LBD. However, in PDnD, the MoCA is a better measure of cognitive status as it lacks both ceiling and floor effects.

Random Forest ensembles for detection and prediction of Alzheimer's disease with a good between-cohort robustness.

Computer-aided diagnosis of Alzheimer's disease (AD) is a rapidly developing field of neuroimaging with strong potential to be used in practice. In this context, assessment of models' robustness to noise and imaging protocol differences together with post-processing and tuning strategies are key tasks to be addressed in order to move towards successful clinical applications. In this study, we investigated the efficacy of Random Forest classifiers trained using different structural MRI measures, with and without neuroanatomical constraints in the detection and prediction of AD in terms of accuracy and between-cohort robustness. From The ADNI database, 185 AD, and 225 healthy controls (HC) were randomly split into training and testing datasets. 165 subjects with mild cognitive impairment (MCI) were distributed according to the month of conversion to dementia (4-year follow-up). Structural 1.5-T MRI-scans were processed using Freesurfer segmentation and cortical reconstruction. Using the resulting output, AD/HC classifiers were trained. Training included model tuning and performance assessment using out-of-bag estimation. Subsequently the classifiers were validated on the AD/HC test set and for the ability to predict MCI-to-AD conversion. Models' between-cohort robustness was additionally assessed using the AddNeuroMed dataset acquired with harmonized clinical and imaging protocols. In the ADNI set, the best AD/HC sensitivity/specificity (88.6%/92.0% - test set) was achieved by combining cortical thickness and volumetric measures. The Random Forest model resulted in significantly higher accuracy compared to the reference classifier (linear Support Vector Machine). The models trained using parcelled and high-dimensional (HD) input demonstrated equivalent performance, but the former was more effective in terms of computation/memory and time costs. The sensitivity/specificity for detecting MCI-to-AD conversion (but not AD/HC classification performance) was further improved from 79.5%/75%-83.3%/81.3% by a combination of morphometric measurements with ApoE-genotype and demographics (age, sex, education). When applied to the independent AddNeuroMed cohort, the best ADNI models produced equivalent performance without substantial accuracy drop, suggesting good robustness sufficient for future clinical implementation.

Multivariate classification of patients with Alzheimer's and dementia with Lewy bodies using high-dimensional cortical thickness measurements: an MRI surface-based morphometric study.

CONTEXT: Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) are the most common neurodegenerative dementia types. It is important to differentiate between them because of the differences in prognosis and treatment approaches. OBJECTIVE: Investigate if sparse partial least squares (SPLS) classification of cortical thickness measurements could differentiate between AD and DLB. METHODS: Two independent cohorts without MR-protocol alignment in Norway and Slovenia with 97 AD and DLB subjects were enrolled. Cortical thickness measurements acquired with Freesurfer were used in subsequent SPLS classification runs. The cohorts were analyzed separately and afterwards combined. The models were trained with leave-one-out cross validation and test datasets where used when available. To study the impact of MR-protocol alignment, the classifiers were additionally tested on sets drawn exclusively from the independent cohorts. RESULTS: The obtained sensitivity/specificity/AUC values were 94.4/88.89/0.978 and 88.2/94.1/0.969 in the Norwegian and Slovenian cohorts, respectively. Both cohorts showed AD-associated pattern of thinning in mid-anterior temporal, occipital and subgenual cingulate cortex, whereas the pattern supportive for DLB included thinning in dorsal cingulate, posterior temporal and lateral orbitofrontal regions. When combining the cohorts, sensitivity/specificity/AUC were 82.1/85.7/0.948 for the training and 77.8/75/0.731 for the testing datasets with the same pattern-of-difference. The models tested on datasets drawn exclusively from the independent cohorts did not produce adequate accuracy. CONCLUSION: SPLS classification of cortical thickness is a good method for differentiating between AD and DLB, relatively stable even for mixed data, but not when tested on completely independent data drawn from different cohorts (without MR-protocol alignment).