A novel computerized test for detecting and monitoring visual attentional deficits and delirium in the ICU

Objectives: Delirium in the ICU is associated with poor outcomes but is under-detected. Here we evaluated performance of a novel, graded test for objectively detecting inattention in delirium, implemented on a custom-built computerized device (Edinburgh Delirium Test Box–ICU). Design: A pilot study was conducted, followed by a prospective case-control study. Setting: Royal Infirmary of Edinburgh General ICU. Patients: A pilot study was conducted in an opportunistic sample of 20 patients. This was followed by a validation study in 30 selected patients with and without delirium (median age, 63 yr; range, 23–84) who were assessed with the Edinburgh Delirium Test Box–ICU on up to 5 separate days. Presence of delirium was assessed using the Confusion Assessment Method for the ICU. Measurements and Main Results: The Edinburgh Delirium Test Box–ICU involves a behavioral assessment and a computerized test of attention, requiring patients to count slowly presented lights. Thirty patients were assessed a total of 79 times (n = 31, 23, 15, 8, and 2 for subsequent assessments; 38% delirious). Edinburgh Delirium Test Box–ICU scores (range, 0–11) were lower for patients with delirium than those without at the first (median, 0 vs 9.5), second (median, 3.5 vs 9), and third (median, 0 vs 10.5) assessments (all p < 0.001). An Edinburgh Delirium Test Box–ICU score less than or equal to 5 was 100% sensitive and 92% specific to delirium across assessments. Longitudinally, participants’ Edinburgh Delirium Test Box–ICU performance was associated with delirium status. Conclusions: These findings suggest that the Edinburgh Delirium Test Box–ICU has diagnostic utility in detecting ICU delirium in patients with Richmond Agitation and Sedation Scale Score greater than –3. The Edinburgh Delirium Test Box–ICU has potential additional value in longitudinally tracking attentional deficits because it provides a range of scores and is sensitive to change

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Digitalizacja i deponowanie archiwalnych zeszytów RPEiS sfinansowane przez MNiSW w ramach realizacji umowy nr 541/P-DUN/201

Automatic method for the estimation of li-ion degradation test sample sizes required to understand cell-to-cell variability

This project was funded by an industry-academia collaborative grant EPSRC EP/R511687/1 awarded by Engineering and Physical Sciences Research Council (EPSRC) & University of Edinburgh United Kingdom program Impact Acceleration Account (IAA). P. Dechent was supported by Bundesministerium für Bildung und Forschung Germany ( BMBF 03XP0302C ). Publisher Copyright: © 2022 The Author(s)The testing of battery cells is a long and expensive process, and hence understanding how large a test set needs to be is very useful. This work proposes an automated methodology to estimate the smallest sample size of cells required to capture the cell-to-cell variability seen in a larger population. We define cell-to-cell variation based on the slopes of a linear regression model applied to capacity fade curves. Our methodology determines a sample size which estimates this variability within user specified requirements on precision and confidence. The sample size is found using the distributional properties of the slopes under a normality assumption, and an implementation of the approach is available on GitHub. For the five datasets in the study, we find that a sample size of 8–10 cells (at a prespecified precision and confidence) captures the cell-to-cell variability of the larger datasets. We show that prior testing knowledge can be leveraged with machine learning models to operationally optimise the design of new cell-testing, leading up to a 75% reduction in experimental costs.publishersversionpublishe

Cognitive function trajectories and their determinants in older people:8 years of follow-up in the English Longitudinal Study of Ageing

BACKGROUND: Maintaining cognitive function is an important aspect of healthy ageing. In this study, we examined age trajectories of cognitive decline in a large nationally representative sample of older people in England. We explored the factors that influence such decline and whether these differed by gender. METHODS: Latent growth curve modelling was used to explore age-specific changes, and influences on them, in an 8-year period in memory, executive function, processing speed and global cognitive function among 10 626 participants in the English Longitudinal Study of Ageing. We run gender-specific models with the following exposures: age, education, wealth, childhood socioeconomic status, cardiovascular disease, diabetes, physical function, body mass index, physical activity, alcohol, smoking, depression and dementia. RESULTS: After adjustment, women had significantly less decline than men in memory (0.011, SE 0.006), executive function (0.012, SE 0.006) and global cognitive function (0.016, SE 0.004). Increasing age and dementia predicted faster rates of decline in all cognitive function domains. Depression and alcohol consumption predicted decline in some cognitive function domains in men only. Poor physical function, physical inactivity and smoking were associated with faster rates of decline in specific cognitive domains in both men and women. For example, relative to study members who were physically active, the sedentary experienced greater declines in memory (women −0.018, SE 0.009) and global cognitive function (men −0.015, SE 0.007 and women −0.016, SE 0.007). CONCLUSIONS: The potential determinants of cognitive decline identified in this study, in particular modifiable risk factors, should be tested in the context of randomised controlled trials

Longitudinal associations between hearing loss and general cognitive ability:The Lothian Birth Cohort 1936

Hearing impairment is associated with poorer cognitive function in later life. We tested for the potential contribution of childhood cognitive ability to this relationship. Childhood cognitive ability is strongly related to cognitive function in older age, and may be related to auditory function through its association with hearing impairment risk factors. Using data from the Lothian Birth Cohort 1936, we tested whether childhood cognitive ability predicted later-life hearing ability then whether this association was mediated by demographic or health differences. We found that childhood cognitive ability was negatively associated with hearing impairment risk at age 76 (odds ratio = .834, p = .042). However, this association was non-significant following subsequent adjustment for potentially mediating demographic and health factors. Next, we tested whether associations observed in older age between hearing impairment and general cognitive ability level or change were accounted for by childhood cognitive ability. At age 76, in the minimally adjusted model, hearing impairment was associated with poorer general cognitive ability level (β = -.119, p = .030) but was not related to decline in general cognitive ability. The former association became non-significant following additional adjustment for childhood cognitive ability (β = -.068; p = .426) suggesting that childhood cognitive ability contributes (potentially via demographic and health differences) to the association between levels of hearing and cognitive function in older age. Further work is needed to test whether early-life cognitive ability also contributes to the association (documented in previous studies) between older-age hearing impairment and cognitive decline