Cognitive, behavioural and psychological barriers to the prevention of severe hypoglycaemia: A qualitative study of adults with type 1 diabetes

Objectives: Severe hypoglycaemia affects approximately one in three people with type 1 diabetes and is the most serious side effect of insulin therapy. Our aim was to explore individualistic drivers of severe hypoglycaemia events. Methods: In-depth semi-structured interviews were conducted with a purposive sample of 17 adults with type 1 diabetes and a history of recurrent severe hypoglycaemia, to elicit experiences of hypoglycaemia (symptoms/awareness, progression from mild to severe and strategies for prevention/treatment). Interviews were analysed using an adapted grounded theory approach. Results: Three main themes emerged: hypoglycaemia-induced cognitive impairment, behavioural factors and psychological factors. Despite experiencing early hypoglycaemic symptoms, individuals often delayed intervention due to impaired/distracted attention, inaccurate risk assessment, embarrassment, worry about rebound hyperglycaemia or unavailability of preferred glucose source. Delay coupled with use of a slow-acting glucose source compromised prevention of severe hypoglycaemia. Conclusion: Our qualitative data highlight the multifaceted, idiosyncratic nature of severe hypoglycaemia and confirm that individuals with a history of recurrent severe hypoglycaemia may have specific thought and behaviour risk profiles. Individualised prevention plans are required, emphasising both the need to attend actively to mild hypoglycaemic symptoms and to intervene promptly with an appropriate, patient-preferred glucose source to prevent progression to severe hypoglycaemia

Localization of 102 exons to a 2.5 Mb region involved in Down syndrome

Exon amplification has been applied to a 2.5 Mb region of chromosome 21 that has been associated with some features of Down syndrome (DS). Identification of the majority of genes from this region will facilitate the correlation of the over-expression of particular genes with specific phenotypes of DS. Over 100 gene fragments have been isolated from this 2.5 Mb segment. The exons have been characterized by sequence analysis, comparison with public databases and expansion to cDNA clones. Localization of the exons to chromosome 21 has been determined by hybridization to genomic Southern blots and to YAC and cosmid clones representing the region. This has resulted in a higher resolution physical map with a marker approximately every 25 kb. This integrated physical and transcript map will be valuable for fine mapping of DNA from individuals with partial aneuploidy of chromosome 21 as well as for assessing and ultimately generating a complete gene map of this segment of the genom

Risk of major cardiovascular events in patients with psoriasis receiving biologic therapies: a prospective cohort study

Background: The cardiovascular safety profile of biologic therapies used for psoriasis is unclear. Objectives: To compare the risk of major cardiovascular events (CVEs; acute coronary syndrome, unstable angina, myocardial infarction and stroke) in patients with chronic plaque psoriasis treated with adalimumab, etanercept or ustekinumab in a large prospective cohort. Methods: Prospective cohort study examining the comparative risk of major CVEs was conducted using the British Association of Dermatologists Biologics and Immunomodulators Register. The main analysis compared adults with chronic plaque psoriasis receiving ustekinumab with tumour necrosis‐α inhibitors (TNFi: etanercept and adalimumab), whilst the secondary analyses compared ustekinumab, etanercept or methotrexate against adalimumab. Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using overlap weights by propensity score to balance baseline covariates among comparison groups. Results: We included 5468 biologic‐naïve patients subsequently exposed (951 ustekinumab; 1313 etanercept; and 3204 adalimumab) in the main analysis. The secondary analyses also included 2189 patients receiving methotrexate. The median (p25–p75) follow‐up times for patients using ustekinumab, TNFi, adalimumab, etanercept and methotrexate were as follows: 2.01 (1.16–3.21), 1.93 (1.05–3.34), 1.94 (1.09–3.32), 1.92 (0.93–3.45) and 1.43 (0.84–2.53) years, respectively. Ustekinumab, TNFi, adalimumab, etanercept and methotrexate groups had 7, 29, 23, 6 and 9 patients experiencing major CVEs, respectively. No differences in the risk of major CVEs were observed between biologic therapies [adjusted HR for ustekinumab vs. TNFi: 0.96 (95% CI 0.41–2.22); ustekinumab vs. adalimumab: 0.81 (0.30–2.17); etanercept vs. adalimumab: 0.81 (0.28–2.30)] and methotrexate against adalimumab [1.05 (0.34–3.28)]. Conclusions: In this large prospective cohort study, we found no significant differences in the risk of major CVEs between three different biologic therapies and methotrexate. Additional studies, with longer term follow‐up, are needed to investigate the potential effects of biologic therapies on incidence of major CVEs

"Older Adults with ASD: The Consequences of Aging." Insights from a series of special interest group meetings held at the International Society for Autism Research 2016-2017

A special interest group (SIG) entitled "Older Adults with ASD: The Consequences of Aging" was held at the International Society for Autism Research (INSAR) annual meetings in 2016 and 2017. The SIG and subsequent meetings brought together, for the first time, international delegates who were members of the autistic community, researchers, practitioners and service providers. Based on aging autism research that is already underway in UK, Europe, Australia and North America, discussions focussed on conceptualising the parameters of aging when referring to autism, and the measures that are appropriate to use with older adults when considering diagnostic assessment, cognitive factors and quality of life in older age. Thus, the aim of this SIG was to progress the research agenda on current and future directions for autism research in the context of aging. A global issue on how to define 'aging' when referring to ASD was at the forefront of discussions. The ‘aging’ concept can in principle refer to all developmental transitions. However, in this paper we focus on the cognitive and physical changes that take place from mid-life onwards. Accordingly, it was agreed that aging and ASD research should focus on adults over the age of 50 years, given the high rates of co-occurring physical and mental health concerns and increased risk of premature death in some individuals. Moreover, very little is known about the cognitive change, care needs and outcomes of autistic adults beyond this age. Discussions on the topics of diagnostic and cognitive assessments, and of quality of life and well-being were explored through shared knowledge about which measures are currently being used and which background questions should be asked to obtain comprehensive and informative developmental and medical histories. Accordingly, a survey was completed by SIG delegates who were representatives of international research groups across four continents, and who are currently conducting studies with older autistic adults. Considerable overlap was identified across different research groups in measures of both autism and quality of life, which pointed to combining data and shared learnings as the logical next step. Regarding the background questions that were asked, the different research groups covered similar topics but the groups differed in the way these questions were formulated when working with autistic adults across a range of cognitive abilities. It became clear that continued input from individuals on the autism spectrum is important to ensure that questionnaires used in ongoing and future are accessible and understandable for people across the whole autistic spectrum, including those with limited verbal abilities

Replication and cross-validation of type 2 diabetes subtypes based on clinical variables: an IMI-RHAPSODY study

Aims/hypothesis Five clusters based on clinical characteristics have been suggested as diabetes subtypes: one autoimmune and four subtypes of type 2 diabetes. In the current study we replicate and cross-validate these type 2 diabetes clusters in three large cohorts using variables readily measured in the clinic.Methods In three independent cohorts, in total 15,940 individuals were clustered based on age, BMI, HbA(1c), random or fasting C-peptide, and HDL-cholesterol. Clusters were cross-validated against the original clusters based on HOMA measures. In addition, between cohorts, clusters were cross-validated by re-assigning people based on each cohort's cluster centres. Finally, we compared the time to insulin requirement for each cluster.Results Five distinct type 2 diabetes clusters were identified and mapped back to the original four All New Diabetics in Scania (ANDIS) clusters. Using C-peptide and HDL-cholesterol instead of HOMA2-B and HOMA2-IR, three of the clusters mapped with high sensitivity (80.6-90.7%) to the previously identified severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD) and mild obesity-related diabetes (MOD) clusters. The previously described ANDIS mild age-related diabetes (MARD) cluster could be mapped to the two milder groups in our study: one characterised by high HDL-cholesterol (mild diabetes with high HDL-cholesterol [MDH] cluster), and the other not having any extreme characteristic (mild diabetes [MD]). When these two milder groups were combined, they mapped well to the previously labelled MARD cluster (sensitivity 79.1%). In the cross-validation between cohorts, particularly the SIDD and MDH clusters cross-validated well, with sensitivities ranging from 73.3% to 97.1%. SIRD and MD showed a lower sensitivity, ranging from 36.1% to 92.3%, where individuals shifted from SIRD to MD and vice versa. People belonging to the SIDD cluster showed the fastest progression towards insulin requirement, while the MDH cluster showed the slowest progression.Conclusions/interpretation Clusters based on C-peptide instead of HOMA2 measures resemble those based on HOMA2 measures, especially for SIDD, SIRD and MOD. By adding HDL-cholesterol, the MARD cluster based upon HOMA2 measures resulted in the current clustering into two clusters, with one cluster having high HDL levels. Cross-validation between cohorts showed generally a good resemblance between cohorts. Together, our results show that the clustering based on clinical variables readily measured in the clinic (age, HbA(1c), HDL-cholesterol, BMI and C-peptide) results in informative clusters that are representative of the original ANDIS clusters and stable across cohorts. Adding HDL-cholesterol to the clustering resulted in the identification of a cluster with very slow glycaemic deterioration.Molecular Epidemiolog

Effects of sleep disturbance on dyspnoea and impaired lung function following hospital admission due to COVID-19 in the UK: a prospective multicentre cohort study

Background: Sleep disturbance is common following hospital admission both for COVID-19 and other causes. The clinical associations of this for recovery after hospital admission are poorly understood despite sleep disturbance contributing to morbidity in other scenarios. We aimed to investigate the prevalence and nature of sleep disturbance after discharge following hospital admission for COVID-19 and to assess whether this was associated with dyspnoea. Methods: CircCOVID was a prospective multicentre cohort substudy designed to investigate the effects of circadian disruption and sleep disturbance on recovery after COVID-19 in a cohort of participants aged 18 years or older, admitted to hospital for COVID-19 in the UK, and discharged between March, 2020, and October, 2021. Participants were recruited from the Post-hospitalisation COVID-19 study (PHOSP-COVID). Follow-up data were collected at two timepoints: an early time point 2–7 months after hospital discharge and a later time point 10–14 months after hospital discharge. Sleep quality was assessed subjectively using the Pittsburgh Sleep Quality Index questionnaire and a numerical rating scale. Sleep quality was also assessed with an accelerometer worn on the wrist (actigraphy) for 14 days. Participants were also clinically phenotyped, including assessment of symptoms (ie, anxiety [Generalised Anxiety Disorder 7-item scale questionnaire], muscle function [SARC-F questionnaire], dyspnoea [Dyspnoea-12 questionnaire] and measurement of lung function), at the early timepoint after discharge. Actigraphy results were also compared to a matched UK Biobank cohort (non-hospitalised individuals and recently hospitalised individuals). Multivariable linear regression was used to define associations of sleep disturbance with the primary outcome of breathlessness and the other clinical symptoms. PHOSP-COVID is registered on the ISRCTN Registry (ISRCTN10980107). Findings: 2320 of 2468 participants in the PHOSP-COVID study attended an early timepoint research visit a median of 5 months (IQR 4–6) following discharge from 83 hospitals in the UK. Data for sleep quality were assessed by subjective measures (the Pittsburgh Sleep Quality Index questionnaire and the numerical rating scale) for 638 participants at the early time point. Sleep quality was also assessed using device-based measures (actigraphy) a median of 7 months (IQR 5–8 months) after discharge from hospital for 729 participants. After discharge from hospital, the majority (396 [62%] of 638) of participants who had been admitted to hospital for COVID-19 reported poor sleep quality in response to the Pittsburgh Sleep Quality Index questionnaire. A comparable proportion (338 [53%] of 638) of participants felt their sleep quality had deteriorated following discharge after COVID-19 admission, as assessed by the numerical rating scale. Device-based measurements were compared to an age-matched, sex-matched, BMI-matched, and time from discharge-matched UK Biobank cohort who had recently been admitted to hospital. Compared to the recently hospitalised matched UK Biobank cohort, participants in our study slept on average 65 min (95% CI 59 to 71) longer, had a lower sleep regularity index (–19%; 95% CI –20 to –16), and a lower sleep efficiency (3·83 percentage points; 95% CI 3·40 to 4·26). Similar results were obtained when comparisons were made with the non-hospitalised UK Biobank cohort. Overall sleep quality (unadjusted effect estimate 3·94; 95% CI 2·78 to 5·10), deterioration in sleep quality following hospital admission (3·00; 1·82 to 4·28), and sleep regularity (4·38; 2·10 to 6·65) were associated with higher dyspnoea scores. Poor sleep quality, deterioration in sleep quality, and sleep regularity were also associated with impaired lung function, as assessed by forced vital capacity. Depending on the sleep metric, anxiety mediated 18–39% of the effect of sleep disturbance on dyspnoea, while muscle weakness mediated 27–41% of this effect. Interpretation: Sleep disturbance following hospital admission for COVID-19 is associated with dyspnoea, anxiety, and muscle weakness. Due to the association with multiple symptoms, targeting sleep disturbance might be beneficial in treating the post-COVID-19 condition. Funding: UK Research and Innovation, National Institute for Health Research, and Engineering and Physical Sciences Research Council