Cognitive and neuropsychiatric effects of noradrenergic treatment in Alzheimer's disease: systematic review and meta-analysis.

BACKGROUND: Dysfunction of the locus coeruleus-noradrenergic system occurs early in Alzheimer's disease, contributing to cognitive and neuropsychiatric symptoms in some patients. This system offers a potential therapeutic target, although noradrenergic treatments are not currently used in clinical practice. OBJECTIVE: To assess the efficacy of drugs with principally noradrenergic action in improving cognitive and neuropsychiatric symptoms in Alzheimer's disease. METHODS: The MEDLINE, Embase and ClinicalTrials.gov databases were searched from 1980 to December 2021. We generated pooled estimates using random effects meta-analyses. RESULTS: We included 19 randomised controlled trials (1811 patients), of which six were judged as 'good' quality, seven as 'fair' and six 'poor'. Meta-analysis of 10 of these studies (1300 patients) showed a significant small positive effect of noradrenergic drugs on global cognition, measured using the Mini-Mental State Examination or Alzheimer's Disease Assessment Scale-Cognitive Subscale (standardised mean difference (SMD): 0.14, 95% CI: 0.03 to 0.25, p=0.01; I2=0%). No significant effect was seen on measures of attention (SMD: 0.01, 95% CI: -0.17 to 0.19, p=0.91; I2=0). The apathy meta-analysis included eight trials (425 patients) and detected a large positive effect of noradrenergic drugs (SMD: 0.45, 95% CI: 0.16 to 0.73, p=0.002; I2=58%). This positive effect was still present following removal of outliers to account for heterogeneity across studies. DISCUSSION: Repurposing of established noradrenergic drugs is most likely to offer effective treatment in Alzheimer's disease for general cognition and apathy. However, several factors should be considered before designing future clinical trials. These include targeting of appropriate patient subgroups and understanding the dose effects of individual drugs and their interactions with other treatments to minimise risks and maximise therapeutic effects. PROSPERO REGISTERATION NUMBER: CRD42021277500.

Quantification of neurofilament light and glial fibrillary acidic protein in finger-prick blood.

An accurate diagnosis of neurodegenerative disease and traumatic brain injury is important for prognostication and treatment. Neurofilament light and glial fibrillary acidic protein (GFAP) are leading biomarkers for neurodegeneration and glial activation that are detectable in blood. Yet, current recommendations require rapid centrifugation and ultra-low temperature storage post-venepuncture. Here, we investigated if these markers can be accurately measured in finger-prick blood using dried plasma spot cards. Fifty patients (46 with dementia; 4 with traumatic brain injury) and 19 healthy volunteers underwent finger-prick and venous sampling using dried plasma spot cards and aligned plasma sampling. Neurofilament light and GFAP were quantified using a Single molecule array assay and correlations between plasma and dried plasma spot cards assessed. Biomarker concentrations in plasma and finger-prick dried plasma spot samples were significantly positively correlated (neurofilament light ρ = 0.57; GFAP ρ = 0.58, P < 0.001). Finger-prick neurofilament light and GFAP were significantly elevated after acute traumatic brain injury with non-significant group-level increases in dementia (91% having Alzheimer's disease dementia). In conclusion, we present preliminary evidence that quantifying GFAP and neurofilament light using finger-prick blood collection is viable, with samples stored at room temperature using dried plasma spot cards. This has potential to expand and promote equitable testing access, including in settings where trained personnel are unavailable to perform venepuncture.

Population incidence and associated mortality of urinary tract infection in people living with dementia.

OBJECTIVES: Urinary tract infections (UTIs) frequently cause hospitalisation and death in people living with dementia (PLWD). We examine UTI incidence and associated mortality among PLWD relative to matched controls and people with diabetes and investigate whether delayed or withheld treatment further impacts mortality. METHODS: Data were extracted for n = 2,449,814 people aged ≥ 50 in Wales from 2000-2021, with groups matched by age, sex, and multimorbidity. Poisson regression was used to estimate incidences of UTI and mortality. Cox regression was used to study the effects of treatment timing. RESULTS: UTIs in dementia (HR=2.18, 95 %CI [1.88-2.53], p < .0) and diabetes (1.21[1.01-1.45], p = .035) were associated with high mortality, with the highest risk in individuals with diabetes and dementia (both) (2.83[2.40-3.34], p < .0) compared to matched individuals with neither dementia nor diabetes. 5.4 % of untreated PLWD died within 60 days of GP diagnosis-increasing to 5.9 % in PLWD with diabetes. CONCLUSIONS: Incidences of UTI and associated mortality are high in PLWD, especially in those with diabetes and dementia. Delayed treatment for UTI is further associated with high mortality.

Remote Monitoring of Physiology in People Living With Dementia: An Observational Cohort Study.

BACKGROUND: Internet of Things (IoT) technology enables physiological measurements to be recorded at home from people living with dementia and monitored remotely. However, measurements from people with dementia in this context have not been previously studied. We report on the distribution of physiological measurements from 82 people with dementia over approximately 2 years. OBJECTIVE: Our objective was to characterize the physiology of people with dementia when measured in the context of their own homes. We also wanted to explore the possible use of an alerts-based system for detecting health deterioration and discuss the potential applications and limitations of this kind of system. METHODS: We performed a longitudinal community-based cohort study of people with dementia using "Minder," our IoT remote monitoring platform. All people with dementia received a blood pressure machine for systolic and diastolic blood pressure, a pulse oximeter measuring oxygen saturation and heart rate, body weight scales, and a thermometer, and were asked to use each device once a day at any time. Timings, distributions, and abnormalities in measurements were examined, including the rate of significant abnormalities ("alerts") defined by various standardized criteria. We used our own study criteria for alerts and compared them with the National Early Warning Score 2 criteria. RESULTS: A total of 82 people with dementia, with a mean age of 80.4 (SD 7.8) years, recorded 147,203 measurements over 958,000 participant-hours. The median percentage of days when any participant took any measurements (ie, any device) was 56.2% (IQR 33.2%-83.7%, range 2.3%-100%). Reassuringly, engagement of people with dementia with the system did not wane with time, reflected in there being no change in the weekly number of measurements with respect to time (1-sample t-test on slopes of linear fit, P=.45). A total of 45% of people with dementia met criteria for hypertension. People with dementia with α-synuclein-related dementia had lower systolic blood pressure; 30% had clinically significant weight loss. Depending on the criteria used, 3.03%-9.46% of measurements generated alerts, at 0.066-0.233 per day per person with dementia. We also report 4 case studies, highlighting the potential benefits and challenges of remote physiological monitoring in people with dementia. These include case studies of people with dementia developing acute infections and one of a person with dementia developing symptomatic bradycardia while taking donepezil. CONCLUSIONS: We present findings from a study of the physiology of people with dementia recorded remotely on a large scale. People with dementia and their carers showed acceptable compliance throughout, supporting the feasibility of the system. Our findings inform the development of technologies, care pathways, and policies for IoT-based remote monitoring. We show how IoT-based monitoring could improve the management of acute and chronic comorbidities in this clinically vulnerable group. Future randomized trials are required to establish if a system like this has measurable long-term benefits on health and quality of life outcomes.

Computerised cognitive assessment in patients with traumatic brain injury: an observational study of feasibility and sensitivity relative to established clinical scales.

Background: Online technology could potentially revolutionise how patients are cognitively assessed and monitored. However, it remains unclear whether assessments conducted remotely can match established pen-and-paper neuropsychological tests in terms of sensitivity and specificity. Methods: This observational study aimed to optimise an online cognitive assessment for use in traumatic brain injury (TBI) clinics. The tertiary referral clinic in which this tool has been clinically implemented typically sees patients a minimum of 6 months post-injury in the chronic phase. Between March and August 2019, we conducted a cross-group, cross-device and factor analyses at the St. Mary's Hospital TBI clinic and major trauma wards at Imperial College NHS trust and St. George's Hospital in London (UK), to identify a battery of tasks that assess aspects of cognition affected by TBI. Between September 2019 and February 2020, we evaluated the online battery against standard face-to-face neuropsychological tests at the Imperial College London research centre. Canonical Correlation Analysis (CCA) determined the shared variance between the online battery and standard neuropsychological tests. Finally, between October 2020 and December 2021, the tests were integrated into a framework that automatically generates a results report where patients' performance is compared to a large normative dataset. We piloted this as a practical tool to be used under supervised and unsupervised conditions at the St. Mary's Hospital TBI clinic in London (UK). Findings: The online assessment discriminated processing-speed, visual-attention, working-memory, and executive-function deficits in TBI. CCA identified two significant modes indicating shared variance with standard neuropsychological tests (r = 0.86, p < 0.001 and r = 0.81, p = 0.02). Sensitivity to cognitive deficits after TBI was evident in the TBI clinic setting under supervised and unsupervised conditions (F (15,555) = 3.99; p < 0.001). Interpretation: Online cognitive assessment of TBI patients is feasible, sensitive, and efficient. When combined with normative sociodemographic models and autogenerated reports, it has the potential to transform cognitive assessment in the healthcare setting. Funding: This work was funded by a National Institute for Health Research (NIHR) Invention for Innovation (i4i) grant awarded to DJS and AH (II-LB-0715-20006).