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.

Digital remote monitoring for screening and early detection of urinary tract infections.

Urinary Tract Infections (UTIs) are one of the most prevalent bacterial infections in older adults and a significant contributor to unplanned hospital admissions in People Living with Dementia (PLWD), with early detection being crucial due to the predicament of reporting symptoms and limited help-seeking behaviour. The most common diagnostic tool is urine sample analysis, which can be time-consuming and is only employed where UTI clinical suspicion exists. In this method development and proof-of-concept study, participants living with dementia were monitored via low-cost devices in the home that passively measure activity, sleep, and nocturnal physiology. Using 27828 person-days of remote monitoring data (from 117 participants), we engineered features representing symptoms used for diagnosing a UTI. We then evaluate explainable machine learning techniques in passively calculating UTI risk and perform stratification on scores to support clinical translation and allow control over the balance between alert rate and sensitivity and specificity. The proposed UTI algorithm achieves a sensitivity of 65.3% (95% Confidence Interval (CI) = 64.3-66.2) and specificity of 70.9% (68.6-73.1) when predicting UTIs on unseen participants and after risk stratification, a sensitivity of 74.7% (67.9-81.5) and specificity of 87.9% (85.0-90.9). In addition, feature importance methods reveal that the largest contributions to the predictions were bathroom visit statistics, night-time respiratory rate, and the number of previous UTI events, aligning with the literature. Our machine learning method alerts clinicians of UTI risk in subjects, enabling earlier detection and enhanced screening when considering treatment.

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).

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.

Amyloid PET imaging in clinical practice.

Amyloid positron emission tomography (PET) imaging enables in vivo detection of brain Aß deposition, one of the neuropathological hallmarks of Alzheimer's disease. There is increasing evidence to support its clinical utility, with major studies showing that amyloid PET imaging improves diagnostic accuracy, increases diagnostic certainty and results in therapeutic changes. The Amyloid Imaging Taskforce has developed appropriate use criteria to guide clinicians by predefining certain scenarios where amyloid PET would be justified. This review provides a practical guide on how and when to use amyloid PET, based on the available research and our own experience. We discuss its three main appropriate indications and illustrate these with clinical cases. We stress the importance of a multidisciplinary approach when deciding who might benefit from amyloid PET imaging. Finally, we highlight some practical points and common pitfalls in its interpretation.

Using amyloid PET imaging to diagnose Alzheimer's disease in patients with multiple sclerosis.

BACKGROUND: Cognitive dysfunction affects 40-60% of individuals with multiple sclerosis (MS). The neuropsychological profile commonly consists of a subcortical pattern of deficits, although a proportion of patients have a severe progressive cortical dementia. However, patients with MS can be affected by other neurodegenerative diseases, such as Alzheimer's disease (AD). Little is known about the co-existence of these two conditions but distinguishing dementia due to MS alone from a coexisting neurodegenerative disease is challenging. Amyloid PET imaging has allowed improved AD diagnosis, especially in patients with atypical presentations or multiple possible causes of cognitive impairment. Amyloid PET demonstrates increased cortical signal in AD, whereas reductions in subcortical uptake are associated with demyelination. To the authors knowledge, there are no reports of clinical Amyloid PET use in MS patients with dementia. METHODS: Here, three MS patients presenting to the Cognitive Neurology Clinic with progressive cognitive impairment are described. Due to lack of diagnostic clarity from standard investigations, they underwent Amyloid PET Imaging with 18F-florbetapir according to established appropriate use criteria and after review by a multidisciplinary team. RESULTS: Two patients were diagnosed with AD based on positive Amyloid PET imaging and were subsequently started on cholinesterase inhibitor treatment. The other patient had a negative scan, leading to further investigations and identification of another potential cause of worsening cognitive impairment. CONCLUSIONS: The experience from this case series suggests that Amyloid PET Imaging may be of diagnostic value in selected patients with MS and dementia. In these individuals, it may provide diagnostic clarity and assist with therapeutic decisions.

A comparative clinical study on five types of compression therapy in patients with venous leg ulcers.

The aim of this study was to compare five types of compression therapy in venous leg ulcers (intermittent pneumatic vs. stockings vs. multi layer vs. two layer short stretch bandages vs. Unna boots). Primary study endpoints were analysis of changes of the total ulcer surface area, volume and linear dimensions inside observed groups. The secondary end points were comparisons between all groups the number of completely healed wounds (ulcer healing rates), Gilman index and percentage change of ulcer surface area. In total, 147 patients with unilateral venous leg ulcers were included to this study. Participants were randomly allocated to the groups: A, B, C, D and E. After two months the healing rate was the highest in group A (intermittent pneumatic compression) - 57.14%, 16/28 patients, B (ulcer stocking system) - 56.66%, 17/30 patients and C (multi layer short stretch bandage) - 58.62%, 17/29 patients. Significantly much worse rate found in group D (two layer short stretch bandages) - only 16.66%, 5/30 patients and E (Unna boots) - 20%, 6/30 patients. The analysis of changes of the percentage of Gilman index and wound total surface area confirmed that intermittent pneumatic compression, stockings and multi layer bandages are the most efficient. The two layer short - stretch bandages and Unna boots appeared again much less effective.

A randomized, controlled clinical pilot study comparing three types of compression therapy to treat venous leg ulcers in patients with superficial and/or segmental deep venous reflux .

Compression therapy--including inelastic, elastic, and intermittent pneumatic compression--is the standard of care for venous ulcers (VLUs) and chronic venous insufficiency, but there is no consensus in the literature regarding the most effective type of compression therapy. A prospective, randomized, clinical pilot study was conducted among 70 patients with unilateral VLUs treated in a hospital dermatology department in Poland to compare three types of compression therapy (intermittent pneumatic compression, stockings, and short-stretch bandages) in persons with superficial deep venous reflux alone or combined with the segmental variety. Study endpoints were change in ulcer dimensions and proportions healed. Patients with superficial or combined superficial and deep vein insufficiency were randomly allocated to receive one of the three therapies (one of each vein type for each treatment option, six groups total). All patients received saline-soaked gauze dressings along with micronized purified flavonoid fraction, diosmin, hesperidin, and Daflon 500 once daily. Compression treatments were changed or pneumatic compression provided daily for 15 days. Wound size reduction and percentage of wounds healed were significantly higher in groups receiving intermittent pneumatic compression or stockings than in groups using short-stretch bandages (for percentage change of ulcer surface area, P = 0.02; for healing rates P = 0.01). These results warrant additional randomized controlled clinical studies with a larger sample size and longer patient follow-up.

Microbleed detection using automated segmentation (MIDAS): a new method applicable to standard clinical MR images.

BACKGROUND: Cerebral microbleeds, visible on gradient-recalled echo (GRE) T2* MRI, have generated increasing interest as an imaging marker of small vessel diseases, with relevance for intracerebral bleeding risk or brain dysfunction. METHODOLOGY/PRINCIPAL FINDINGS: Manual rating methods have limited reliability and are time-consuming. We developed a new method for microbleed detection using automated segmentation (MIDAS) and compared it with a validated visual rating system. In thirty consecutive stroke service patients, standard GRE T2* images were acquired and manually rated for microbleeds by a trained observer. After spatially normalizing each patient's GRE T2* images into a standard stereotaxic space, the automated microbleed detection algorithm (MIDAS) identified cerebral microbleeds by explicitly incorporating an "extra" tissue class for abnormal voxels within a unified segmentation-normalization model. The agreement between manual and automated methods was assessed using the intraclass correlation coefficient (ICC) and Kappa statistic. We found that MIDAS had generally moderate to good agreement with the manual reference method for the presence of lobar microbleeds (Kappa = 0.43, improved to 0.65 after manual exclusion of obvious artefacts). Agreement for the number of microbleeds was very good for lobar regions: (ICC = 0.71, improved to ICC = 0.87). MIDAS successfully detected all patients with multiple (≥2) lobar microbleeds. CONCLUSIONS/SIGNIFICANCE: MIDAS can identify microbleeds on standard MR datasets, and with an additional rapid editing step shows good agreement with a validated visual rating system. MIDAS may be useful in screening for multiple lobar microbleeds.