bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of magnetic resonance spectroscopy variability across metabolites and field strengths
Authors: Bracoud Luc , Port John D , Scott David , Conklin Chris , Suhy Joyce , Glaus Charles , Jacobsen Leslie 
Published: December 2020

AbstractBackgroundMagnetic Resonance Spectroscopy (MRS) is a non‐invasive technique assessing the concentration of various metabolites within the brain, both cross‐sectionally to characterize disease type and severity, and longitudinally to assess disease progression and potential treatment efficacy in the context of disease‐modifying interventions. In such context, the involvement of multiple imaging facilities inevitably introduces variability, whose amount must be known to inform on comparability between sites and sensitivity to change. Our objective is to study variability in the concentration of various brain metabolites using a dedicated MRS phantom and assess impact of field strength.Methods30 sites are being considered to participate in an on‐going clinical trial in metachromatic leukodystrophy. Site qualification mandates the scanning of a dedicated MRS phantom. 30 of these HD‐polyethylene spheres were simultaneously manufactured and filled with the same mixture of chemicals mimicking main metabolite concentrations. To date, 14 sites provided data (5 1.5T scanners and 9 3T). All sites implemented a standardized single‐voxel MRS sequence. MRS voxel was placed within the phantom and acquisition repeated 3 times. Spectra were centrally analyzed using LCModel v6.3 and quality controlled by Bioclinica. Repeat acquisitions were requested for parameter deviations, voxel positioning and/or shimming issues. Results only include passing datasets. Coefficient of Variation (CV) was calculated for NAA/Cr, Cho/Cr, mI/Cr, Glx/Cr and Lac/Cr ratios for each site and overall. LCModel quality metrics (FHWM and S/N) were also extracted to assess spectra quality. Comparison between field strengths was carried out using t‐tests.ResultsAverage CV by site was 2.0% for NAA/Cr (2.5% at 1.5T and 1.8% at 3T), 2.4% for Cho/Cr, 3.0% for mI/Cr, 4.5% for Glx/Cr and 6.1% for Lac/Cr. CVs were generally lower at 3T (except for Lac/Cr) although difference was not significant. As expected, Signal‐to‐Noise was higher at 3T (p=0.05). Overall CV by metabolite across scanners was much higher (ranging from 4.6% for Cho/Cr up to 12.1% for Lac/Cr).ConclusionMRS measures of metabolite concentrations have low variability at scanner‐level, insensitive to field strength. Nevertheless, variability across sites is much higher and would require, if possible, cross‐calibration. These phantom data make such calibration possible and will improve sensitivity of subject data analyses.
Use of wearable technology to assess activity in cognitively impaired populations: Inside care homes and the community
Authors: McArdle Ríona , Buckley Christopher , Din Silvia Del , Parsons John , Lord Sue , Galna Brook , Taylor Lynne , Thomas Alan J , Kerse Ngaire , Rochester Lynn 
Published: December 2020

AbstractBackgroundPreservation of mobility is a key mediator for maintaining functional abilities, preventing falls, and slowing cognitive decline in older adults with cognitive impairments, such as dementia. Community‐dwellers with dementia are less active than cognitively‐intact older adults, spending less time walking and taking less varied walking activities [Mc Ardle et al., 2019]. Care homes might further increase barriers to mobility for cognitively‐impaired residents due to organizational and environmental constraints [Benjamin et al., 2014]. However, there are limited objective studies characterising activity in care home residents with cognitive impairment. This study aims to investigate activity in care home residents compared to community‐dwellers with cognitive impairment.MethodData from the Staying UpRight study (University of Auckland, NZ) provided information about 37 care home residents with predominately mild‐moderate cognitive impairment, while the GaitDem study (University of Newcastle, UK) illustrated activity in 51 community‐dwellers with dementia. Both studies placed a tri‐axial accelerometer (Axivity, AX3) on participants’ lower backs, which continuously monitored their activity for 7 days on average. Activity measures included volume (time spent walking, steps and ambulatory bouts per day), pattern (mean bout length, proportion of short to long walking bouts) and variability (of bout length). Independent t‐tests compared activity measures between care home residents and community dwellers.ResultControlling for age and sex, care home residents (Age: 85±8, MOCA: 14±7, 74%female) spent less minutes walking (p<.001), took less steps (p<.001) and fewer ambulatory bouts (p<.001) compared to community‐dwellers with dementia (Age: 77±6, sMMSE: 22±4, 29%female). Their ambulatory bout lengths were also shorter (p=.032), and they spent proportionally more time in short bouts (p=.012).ConclusionThis study provides initial evidence that care home residents with cognitive impairment are objectively less active compared to community‐dwellers. Improving mobility in care homes is an important target for maintaining functional abilities, lowering falls risk and enhancing longevity. Future work should identify modifiable factors for activity preservation when residing in care homes. This analysis was limited by the synthesis of two discrete datasets with culturally‐diverse populations at different stages of cognitive impairment. This highlights the need for a comprehensive study to investigate the complexities of activity loss in care homes.
Mental representations of daily activities throughout the course of dementia
Authors: Ross Sabrina D. , Rodriguez Francisca S. 
Published: December 2020

AbstractBackgroundSince dementia is a result of cognitive rather than physical impairment, cognitive functioning should also be considered when estimating the care of older people. This study investigated how the loss of cognitive functioning affects mental representations of daily activities and their performance throughout the course of dementia. A mixed‐model study was conducted to investigate how the content of the mental representations differs between stages of dementia.MethodIn order to gain a better insight into how changes of mental representations of daily activities get affected throughout the disease of dementia, we conducted the script generation task of daily activities (grocery shopping, doing laundry, going to the dentists) and the Montreal Cognitive Assessment (MoCa), from 25 people (age (mean: 67.64; SD: 23.625), sex (f: 14 (56%); m: 17 (68%)), cognitive status (healthy: n=6; mild demented: n=7; severe demented: n=12)) as well as a qualitative semi‐structured interview. In this mixed‐method design, the qualitative analysis was based on the Grounded Theory.ResultOverall, we found evidence that mental representations of daily activities loose in content and get inaccurate throughout the course of the disease, whereas not always a steady transition according to the assessed cognitive status was observed. However, mental representations on performing daily activities remained correct throughout the course of dementia, even though the ability to perform those activities decreased. We further observed a great variance in the content generated by severe demented people ranging from a complete reduction of actions to expansive script action generation. It was also shown that, in early stages of dementia, mental representations of daily activities are disrupted, which is predominantly shown in an incipient increase in sequencing errors and, in the further course of the disease, an increase in intrusions and personalizations.ConclusionThis study outlines how dementia affects mental representations and performance of daily activities throughout dementia. It turns out that script generation is hampered by decreasing cognitive functioning, the content of the generated actions for mental representations of daily activities reflect functional impairment. Further research is needed to gain a detailed understanding in how script generation gets affected along decreasing cognitive status.
Effect of trazodone on cognitive function in people with dementia: Cohort study using UK routinely collected data
Authors: Sommerlad Andrew , Werbeloff Nomi , Perera Gayan , Smith Tanya , Costello Harry , Mueller Christoph , Kormilitzin Andrey , Broadbent Matthew , Nevado‐Holgado Alejo J , Lovestone Simon , Stewart Robert , Livingston Gill 
Published: December 2020

AbstractBackgroundThe antidepressant trazodone has been found in recent evidence from mouse neurodegenerative disease models to be neuroprotective, leading to interest in whether trazodone could be repurposed to improve cognition in people with dementia. We aimed to examine trazodone’s effect using routinely collected clinical data, by comparing cognitive decline of people with dementia taking trazodone with those taking other antidepressants.MethodWe conducted three identical naturalistic pharmaco‐epidemiological cohort studies using large secondary mental healthcare databases in North London, South London, and Oxford, covering around 2% of the UK’s population. We included all people with dementia who were recorded between 2008‐16 taking trazodone, citalopram or mirtazapine for at least 6 weeks and had cognition assessed by mini‐mental state examination (MMSE). Linear mixed models examined age, time and sex‐adjusted MMSE change in people with all‐cause dementia taking trazodone compared with those taking citalopram and mirtazapine. Sensitivity analyses examined those with non‐vascular dementia; mild dementia; and adjusted results for neuropsychiatric symptoms. Results from the three study sites were combined using random‐effects meta‐analysis.ResultWe included 2,199 people with dementia, including 406 taking trazodone, with mean 2.2 years follow‐up. There was no difference in adjusted cognitive decline in people with all‐cause or non‐vascular dementia taking trazodone, citalopram or mirtazapine in any of the three study sites. Meta‐analysed results from the three sites indicated greater mean MMSE decline in people with all‐cause dementia taking trazodone compared to those taking citalopram (0.26 points per successive MMSE measurement, 95% CI 0.03 to 0.49; p=0.03). Pooled MMSE change was not different for those taking trazodone v mirtazapine. The main limitation of our study design was the potential for confounding by indication, but results in sensitivity analyses adjusting for neuropsychiatric symptoms and analysing only those with mild dementia were consistent with the primary analysis, suggesting that confounding by indication did not explain results.ConclusionThere was no evidence of cognitive benefit from taking trazodone compared to citalopram or mirtazapine in people with established dementia in these three separate naturalistic cohort studies or when results were combined. Despite the preclinical evidence, trazodone should not be advocated for cognition in dementia.
Mild cognitive impairment with Lewy bodies: Clinical characteristics and risk factors for progression
Authors: van de Beek Marleen , van Steenoven Inger , van der Zande Jessica J. , Barkhof Frederik , Teunissen Charlotte E. , van Der Flier Wiesje , Lemstra Evelien 
Published: December 2020

AbstractBackgroundLittle is known about the clinical presentation and prognosis of patients with mild cognitive impairment with Lewy Bodies (MCI‐LB). We aimed to describe clinical characteristics, cognitive decline and risk factors for progression to dementia in MCI‐LB and compare these to MCI due to Alzheimer’s disease (MCI‐AD).MethodWe included 194 MCI patients from the Amsterdam Dementia Cohort. MCI‐LB (n=73, 68±6yrs, 12%F, MMSE:27±2) was defined as MCI + (1)two or more core clinical features (hallucinations, parkinsonism, fluctuations, RBD), or (2)one core clinical feature and abnormal DAT‐SPECT and/or (3)probable Dementia with Lewy Bodies (DLB) at follow‐up. MCI‐AD (n=124, 68±7yrs, 48%F, MMSE:27±2) was defined as having MCI + abnormal CSF AD biomarkers. Cross‐sectional analyses included neuropsychiatric symptoms (GDS, NPI), caregiver burden (ZARIT), MRI, CSF biomarkers (tau/Ab1‐42 ratio) and APOE‐genotype. Annual follow‐up was available for 61 MCI‐LB patients and all MCI‐AD patients(3±2yrs). Linear mixed models(LMM) analyzed decline in MMSE and cognitive domains over time (memory, attention, executive and visuospatial functioning). Cox proportional‐hazards analyses identified risk factors for progression to dementia.ResultParkinsonism was the most frequently reported feature in MCI‐LB (70%). In MCI‐LB, 33% had a CSF AD biomarker profile and 47% were APOE‐ɛ4 carrier. MCI‐LB patients scored higher on NPI, GDS and ZARIT than MCI‐AD. There were no differences in MRI characteristics(Table 1). MCI‐LB had lower baseline attention, executive and visuospatial functioning, while MCI‐AD had lower baseline memory scores. MCI‐LB declined faster over time on attention, whereas MCI‐AD had faster decline on MMSE and memory (Table 2, Figure 1). In MCI‐DLB, 53% progressed to DLB after 3±2 years. Posterior cortical atrophy(HR=3.0[1.5–5.8]) and lower attention(HR=1.6[1.1–2.3]) predicted shorter time to DLB(Figure 2). In MCI‐AD, 69% progressed to dementia after 3±2 years and lower executive functions(HR=1.3[1.0–1.6]) and memory(HR=1.1[1.0–1.2]) predicted faster progression to AD.ConclusionMCI‐LB patients had more non‐cognitive symptoms, a distinct cognitive profile with prominent attentional decline and higher caregiver burden, compared to MCI‐AD. Attention impairment and posterior atrophy are potential risk factors for progression towards DLB. Our results underline the need for early diagnosis, since several of these symptoms already have impact in this disease stage and could be treated.
Validation and calibration of machine‐learning predictive models aimed to identify dementia‐related neuropsychiatric symptoms on real‐world data (RWD)
Authors: Mar Javier , Gorostiza Ania , Ibarrondo Oliver , Cernuda Carlos , Alberdi Ane , Iruin Álvaro , Tainta Mikel 
Published: December 2020

AbstractBackground8% of currently under evaluation new drugs for Alzheimer’s disease are intended to treat neuropsychiatric symptoms (NPS). But, the lack of their presence in codded format in clinical records registries determines that their population impact is underestimated. Validation studies are required in order to systematically use real‐world data (RWD) as a source of epidemiological information for dementia. The objective of this study was to build and validate predictive models to identify the presence of both behavioral or psychotic and depressive symptoms in dementia‐diagnosed patients from administrative and clinical databases.MethodWe searched the Electronic Health Recordings (EHR) of 4,003 patients with dementia looking for mood and psychotic symptoms. First, codded diagnoses, drugs prescriptions and other clinical variables were used to identify the dementia cases in the Basque Service corporate database. Second, Random Forests algorithms were applied to build predictive models by using the training sample (N=3,003) to select the best models separately for mood and behavioral symptoms. Third, we measured calibration and discrimination in the remaining testing sample (N= 1000) separately for each model.ResultNeuropsychiatric Symptoms (NPS) were identified in 58% of the sample. The model predicting psychotic symptoms achieved 80% of AUC when depressive model only achieved 74%. Kappa index and accuracy also showed better discrimination in the psychotic symptoms model. As displayed by the calibration plot, the models made worse predictions when the probability of the cases was lower than 25%. The most relevant variables in the psychotic symptoms model were the highest sedation level achieved followed by the use of quetiapine and risperidone and the number of different antipsychotic treatments. In the depressive symptoms model, the most relevant variable is the number of antidepressant treatments followed by the use of escitalopram, sedation level and age. Calibration was poorer when the probability was low.ConclusionGiven the good performance, the resulting models can be applied to estimate the prevalence of NPS in population databases (RWD). Our work showed how machine learning tools can be used to predict complex clinical conditions like NPS and possess the capacity to convert RWD into smart data.
Odorant‐induced brain activation as a function of normal aging and Alzheimer’s disease
Authors: Motter Jeffrey N. , Steffener Jason , Tabert Matthias H. , Devanand Davangere P. 
Published: December 2020

AbstractBackgroundOlfactory dysfunction consistently occurs in patients with Alzheimer’s disease (AD), beyond the mild and gradual decline in olfactory ability found in normal aging. This dysfunction begins early in the disease course, typically before clinical diagnosis, and progresses with disease severity. While odor identification and detection deficits clearly differentiate AD from controls, there remains uncertainty as to whether these are determined by olfactory threshold. The primary purpose of the current fMRI study was to examine the neural correlates of olfactory processing in healthy young and old adults and compare them with AD patients.MethodHealth young adults (n=10), healthy old adults (n=10), and AD patients (n=12) participated in psychophysical olfactory testing and an fMRI odorant detection paradigm. We analyzed the interplay between age and disease‐related psychophysical olfactory declines and odorant‐induced brain activation. This tested whether odor threshold deficits reflect disease progression and explain group differences in detection, identification and brain activity.ResultAD patients had decreased odor detection task‐related signal in all regions of the primary olfactory cortex, with activity in the entorhinal cortex best differentiating the groups. Within the secondary olfactory regions, AD patients showed decreased activity in orbitofrontal cortex compared to healthy age matched individuals. Moderated‐mediation analyses on neuro‐psychophysical relationships found that increased brain activation in the entorhinal cortex moderated the negative effect of disease‐related threshold decline on olfactory detection.ConclusionEven in the face of declining olfactory thresholds, older adults compensated for this effect with increased brain activation in a primary olfactory brain region. This was the case for odor detection but not odor identification. fMRI activation induced by an olfactory identification task may eventually be useful in improving early detection of AD and may, eventually, facilitate early treatment interventions in subjects at risk for AD.
Clinical factors associated with progression to dementia in people with late‐life depression: A cohort study of patients in secondary care
Authors: Mueller Christoph , Peakman Georgia , Karunatilake Nishshanka , Seynaeve Mathieu , Perera Gayan , Aarsland Dag , Stewart Robert 
Published: December 2020

AbstractBackgroundDepression in later life is increasingly being recognised as a prodrome for the development of dementia. We aimed to investigate which clinical factors are associated with more rapid conversion from depression to dementia.MethodThe South London and Maudsley NHS Foundation Trust (SLaM) Clinical Record Interactive Search (CRIS) was used to retrieve anonymised data on patients who were aged 65 years or older and received a diagnosis of depression in mental health services, followed by a diagnosis of dementia >3 months later. Predictors of accelerated dementia development were investigated including demographic factors, health status rated on the Health of the National Outcome scale for older people (HoNOS65+), depression recurrence, and treatments including psychotropic drugs and cognitive behavioural therapy (CBT).ResultIn 806 patients with late‐life depression who later received a diagnosis of dementia, significant predictors of shorter time to dementia diagnosis in fully adjusted models were older age, male gender, higher deprivation, and HoNOS65+ subscales measuring depressed mood and cognitive problems. A diagnosis of recurrent depressive disorder was independently associated with a longer time to dementia diagnosis. Antipsychotic drugs and CBT were significantly associated with longer times to dementia diagnosis when adjusted for demographic factors and severity of mood and cognitive difficulties, but not in fully adjusted models.ConclusionIn older adults with depression and subsequent dementia diagnosed by mental health services, faster progression to a diagnosis of dementia was predicted by age and gender, new onset depression, and severity of depressive and cognitive symptoms.
A phase I single ascending dose safety study of NTRX‐07 in normal volunteers
Authors: Foss Joseph , Naguib Mohamed , Giordano Tony 
Published: December 2020

AbstractBackgroundNTRX‐07 is a selective cannabinoid receptor type 2 (CB2) agonist that has been shown in animal models to be effective for the treatment of Alzheimer’s disease (AD). CB2 agonists have been shown to be neuroprotective in preclinical models and the lack the psychotropic adverse effects normally seen with CB1 agonists1‐4. NTRX‐07 has acceptable drug metabolism, pharmacokinetic and preclinical safety profiles.MethodThis is a double‐blind, placebo controlled single ascending dose study with 6 cohorts of normal volunteers 18‐65 years of age (n=∼48). The primary outcome is the safety and tolerability of NTRX‐07. Each cohort is randomized with 6 subjects receiving active drug and 2 placebo. Doses range from 0.3 to 8 mg/kg of NTRX‐07 in a HPMCAS‐MG excipient administered orally. Subjects are admitted to the site the night before dosing, and are observed for 24 hours post‐dose, with a safety visit 7 days later. Subjects are observed for changes in physical exam or symptoms (including questionnaires of drug effect), vitals, laboratory values and adverse events (AEs). Blood samples are obtained to determine the pharmacokinetics of NTRX‐07 in humans.ResultAt submission three cohorts have completed dosing and all cohorts will be completed for final poster submission. No treatment related AEs have been observed. Plasma levels have been higher than predicted based on preclinical studies suggesting differences in absorption or metabolism compared to animal models. Pharmacokinetics (PK) have demonstrated dose linearity and support feasibility in clinical use.ConclusionThere are currently no commercially available CB2 agonists. NTRX‐07 would represent the first‐in‐class of a new therapeutic agent to treat microglial‐mediated neuroinflammation in a variety of diseases where the CB2 receptor has been shown to be active such as AD, ALS and FTD. The next study will be a 28 day repeat dose of NTRX‐07, in patients with MCI or early AD, for safety, PK and exploratory biomarkers. References: 1 Naguib, M. et al. Br. J. Pharmacol. 155, 1104‐1116 (2008). 2 Diaz, P. et al. ChemMedChem 4, 1615‐1629 (2009). 3 Wu, J. et al. Neurobiol. Aging 34, 791‐804 (2013). 4 Wu, J., et al. Eur. J. Pharmacol. 811, 12‐20, (2017).