Correction to Thermochemistry of Racemic and Enantiopure Organic Crystals for Predicting Enantiomer Separation

Correction to Thermochemistry of Racemic and Enantiopure Organic Crystals for Predicting Enantiomer Separatio

Reliability of Addenbrooke's Cognitive Examination III in differentiating between dementia, mild cognitive impairment and older adults who have not reported cognitive problems.

Diagnosing dementia can be challenging for clinicians, given the array of factors that contribute to changes in cognitive function. The Addenbrooke’s Cognitive Examination III (ACE-III) is commonly used in dementia assessments, covering the domains of attention, memory, fluency, visuospatial and language. This study aims to (1) assess the reliability of ACE-III to differentiate between dementia, mild cognitive impairment (MCI) and controls and (2) establish whether the ACE-III is useful for diagnosing dementia subtypes. Client records from the Northern Health and Social Care Trust (NHSCT) Memory Service (n = 2,331, 2013–2019) were used in the analysis including people diagnosed with Alzheimer’s disease (n = 637), vascular dementia (n = 252), mixed dementia (n = 490), MCI (n = 920) and controls (n = 32). There were significant differences in total ACE-III and subdomain scores between people with dementia, MCI and controls (p  73%) and thus the differences are not clinically relevant. The results suggest that ACE-III is a useful tool for discriminating between dementia, MCI and controls, but it is not reliable for discriminating between dementia subtypes. Nonetheless, the ACE-III is still a reliable tool for clinicians that can assist in making a dementia diagnosis in combination with other factors at assessment

IgG antibody production and persistence to 6 months following SARS-CoV-2 vaccination: a Northern Ireland observational study

BACKGROUND: This study evaluates spike protein IgG antibody response following Oxford-AstraZeneca COVID-19 vaccination using the AbC-19™ lateral flow device. METHODS: Plasma samples were collected from n=111 individuals from Northern Ireland. The majority were >50 years old and/or clinically vulnerable. Samples were taken at five timepoints from pre-vaccination until 6-months post-first dose. RESULTS: 20.3% of participants had detectable IgG responses pre-vaccination, indicating prior COVID-19. Antibodies were detected in 86.9% of participants three weeks after the first vaccine dose, falling to 74.7% immediately prior to the second dose, and rising to 99% three weeks post-second vaccine. At 6-months post-first dose, this decreased to 90.5%. At all timepoints, previously infected participants had significantly higher antibody levels than those not previously infected. CONCLUSION: This study demonstrates that strong anti-spike protein antibody responses are evoked in almost all individuals that receive two doses of Oxford-AstraZeneca vaccine, and largely persist beyond six months after first vaccination

User experience analysis of AbC-19 Rapid Test via lateral flow immunoassays for self-administrated SARS-CoV-2 antibody testing

Abstract Lateral flow immunoassays are low cost, rapid and highly efficacious point-of-care devices, which have been used for SARS-CoV-2 antibody testing by professionals. However, there is a lack of understanding about how self-administered tests are used by the general public for mass testing in different environmental settings. The purpose of this study was to assess the user experience (UX) (including usability) of a self-testing kit to identify COVID-19 antibodies used by a representative sample of the public in their cars, which included 1544 participants in Northern Ireland. The results based on 5-point Likert ratings from a post-test questionnaire achieved an average UX score of 96.03% [95% confidence interval (CI) 95.05–97.01%], suggesting a good degree of user experience. The results of the Wilcoxon rank sum tests suggest that UX scores were independent of the user’s age and education level although the confidence in this conclusion could be strengthened by including more participants aged younger than 18 and those with only primary or secondary education. The agreement between the test result as interpreted by the participant and the researcher was 95.85% [95% CI 94.85–96.85%], Kappa score 0.75 [95% CI 0.69–0.81] (indicating substantial agreement). Text analysis via the latent Dirichlet allocation model for the free text responses in the survey suggest that the user experience could be improved for blood-sample collection, by modifying the method of sample transfer to the test device and giving clearer instructions on how to interpret the test results. The overall findings provide an insight into the opportunities for improving the design of SARS-CoV-2 antibody testing kits to be used by the general public and therefore inform protocols for future user experience studies of point-of-care tests

CLEAR-AI: empowering people living with dementia and their carers to understand and reduce distress

People living with dementia sometimes present with behaviours that carers find difficult to understand and manage. These include aggression, pacing, vocalising, exit-seeking and sexually inappropriate behaviour. They can be present in up to 70% of people living with dementia and often present because of misunderstanding or because of the distress the person experiences trying to cope with the daily challenges of living with their illness. These behaviours increase the risk that a person will move from their home to a care home. CLEAR Dementia Care© helps carers to understand behaviour in the context of the person and their environment, identify unmet needs and respond in ways to reduce distress. We present the pilot of “CLEAR-AI”, an artificial intelligence (AI) powered platform that interprets data from a range of connected smart sensors, apps and devices to model the person with dementia’s daily routines. Analysis of the data and training the AI model enables the platform to identify the triggers that precede distress episodes and to recognise when episodes occur in the context of previous activities in the day. Using these models, and with CLEAR’s assessment as baseline, we can initiate interventions into daily schedules that reduce or mitigate distress where it is likely to arise. The goal is to reduce carer burden and enable the person to live at home with as much independence as possible for as long as possible. Our consortium brings together people living with dementia and their carers, commissioners of digital social care, specialists in dementia care, AI and digital solutions. The co-design approach ensures that we are led by stakeholders’ needs to improve quality of life