Found 9278 matches for
Associations between body-mass index and COVID-19 severity in 6·9 million people in England: a prospective, community-based, cohort study.
BACKGROUND: Obesity is a major risk factor for adverse outcomes after infection with SARS-CoV-2. We aimed to examine this association, including interactions with demographic and behavioural characteristics, type 2 diabetes, and other health conditions. METHODS: In this prospective, community-based, cohort study, we used de-identified patient-level data from the QResearch database of general practices in England, UK. We extracted data for patients aged 20 years and older who were registered at a practice eligible for inclusion in the QResearch database between Jan 24, 2020 (date of the first recorded infection in the UK) and April 30, 2020, and with available data on BMI. Data extracted included demographic, clinical, clinical values linked with Public Health England's database of positive SARS-CoV-2 test results, and death certificates from the Office of National Statistics. Outcomes, as a proxy measure of severe COVID-19, were admission to hospital, admission to an intensive care unit (ICU), and death due to COVID-19. We used Cox proportional hazard models to estimate the risk of severe COVID-19, sequentially adjusting for demographic characteristics, behavioural factors, and comorbidities. FINDINGS: Among 6 910 695 eligible individuals (mean BMI 26·78 kg/m2 [SD 5·59]), 13 503 (0·20%) were admitted to hospital, 1601 (0·02%) to an ICU, and 5479 (0·08%) died after a positive test for SARS-CoV-2. We found J-shaped associations between BMI and admission to hospital due to COVID-19 (adjusted hazard ratio [HR] per kg/m2 from the nadir at BMI of 23 kg/m2 of 1·05 [95% CI 1·05-1·05]) and death (1·04 [1·04-1·05]), and a linear association across the whole BMI range with ICU admission (1·10 [1·09-1·10]). We found a significant interaction between BMI and age and ethnicity, with higher HR per kg/m2 above BMI 23 kg/m2 for younger people (adjusted HR per kg/m2 above BMI 23 kg/m2 for hospital admission 1·09 [95% CI 1·08-1·10] in 20-39 years age group vs 80-100 years group 1·01 [1·00-1·02]) and Black people than White people (1·07 [1·06-1·08] vs 1·04 [1·04-1·05]). The risk of admission to hospital and ICU due to COVID-19 associated with unit increase in BMI was slightly lower in people with type 2 diabetes, hypertension, and cardiovascular disease than in those without these morbidities. INTERPRETATION: At a BMI of more than 23 kg/m2, we found a linear increase in risk of severe COVID-19 leading to admission to hospital and death, and a linear increase in admission to an ICU across the whole BMI range, which is not attributable to excess risks of related diseases. The relative risk due to increasing BMI is particularly notable people younger than 40 years and of Black ethnicity. FUNDING: NIHR Oxford Biomedical Research Centre.
Sales of over-the-counter products containing codeine in 31 countries, 2013-2019: a retrospective observational study
<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Opioid prescribing trends have been well investigated in many countries. However, the patterns of opioids purchased over-the-counter (OTC) without a prescription are mostly unknown. Codeine is an opioid that is widely available OTC in many countries. We aimed to assess national sales and public expenditure of OTC codeine-containing products purchased in 31 countries between 2013 and 2019.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We conducted a retrospective observational study using electronic point-of-sale data from IQVIA. Countries included Argentina, Belgium, Brazil, Bulgaria, Canada, Croatia, Estonia, Finland, France, Germany, Greece, Ireland, Italy, Japan, Latvia, Lithuania, Mexico, The Netherlands, Poland, Portugal, Romania, Russia, Serbia, Slovakia, Slovenia, South Africa, Spain, Switzerland, Thailand, the UK, and the USA. We calculated the annual mean volume of sales per 1000 of the population and public expenditure (GBP, £ per 1000) between April 2013 and March 2019. We quantified changes over time and the types of products sold.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>31.5 billion units of codeine, costing £2.55 billion, were sold OTC in 31 countries between April 2013 and March 2019. Total sales increased by 3% (3025 units/1000 in 2013 to 3111 in 2019) and public expenditure doubled (£196/1000 in 2013 to £301 in 2019). Sales were not equally distributed across the 31 countries. South Africa accounted for the largest mean volume of sales (31 units/person), followed by Ireland (24 units/person), France (16 units/person), Latvia (15 units/person), and the UK (11 units/person). The types of products (n=569) and formulations (n=12) varied.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>In many parts of the world, a substantial number of people may be purchasing and consuming codeine from OTC products. Clinicians should ask patients about their use of OTC products. Public health measures are required to identify and prevent codeine misuse and abuse, increase awareness and education about the harms of codeine, and review medicines legislation to improve the collection of such data.</jats:p></jats:sec><jats:sec><jats:title>Pre-registration</jats:title><jats:p><jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://doi.org/10.17605/OSF.IO/AY4MC">https://doi.org/10.17605/OSF.IO/AY4MC</jats:ext-link></jats:p></jats:sec>
Group-Personalized Regression Models for Predicting Mental Health Scores From Objective Mobile Phone Data Streams: Observational Study
Background: Objective behavioral markers of mental illness, often recorded through smartphones or wearable devices, have the potential to transform how mental health services are delivered and to help users monitor their own health. Linking objective markers to illness is commonly performed using population-level models, which assume that everyone is the same. The reality is that there are large levels of natural interindividual variability, both in terms of response to illness and in usual behavioral patterns, as well as intraindividual variability that these models do not consider. Objective: The objective of this study was to demonstrate the utility of splitting the population into subsets of individuals that exhibit similar relationships between their objective markers and their mental states. Using these subsets, “group-personalized” models can be built for individuals based on other individuals to whom they are most similar. Methods: We collected geolocation data from 59 participants who were part of the Automated Monitoring of Symptom Severity study at the University of Oxford. This was an observational data collection study. Participants were diagnosed with bipolar disorder (n=20); borderline personality disorder (n=17); or were healthy controls (n=22). Geolocation data were collected using a custom Android app installed on participants’ smartphones, and participants weekly reported their symptoms of depression using the 16-item quick inventory of depressive symptomatology questionnaire. Population-level models were built to estimate levels of depression using features derived from the geolocation data recorded from participants, and it was hypothesized that results could be improved by splitting individuals into subgroups with similar relationships between their behavioral features and depressive symptoms. We developed a new model using a Dirichlet process prior for splitting individuals into groups, with a Bayesian Lasso model in each group to link behavioral features with mental illness. The result is a model for each individual that incorporates information from other similar individuals to augment the limited training data available. Results: The new group-personalized regression model showed a significant improvement over population-level models in predicting mental health severity (P
Recruitment, Retainment, and Biomarkers of Response; A Pilot Trial of Lithium in Humans With Mild Cognitive Impairment.
Lithium has been used for decades to treat Bipolar Disorder. Some of its therapeutic benefits may be through inhibition of Glycogen Synthase Kinase (GSK)-3. Enhanced GSK3 activity associates with development of Alzheimer's disease (AD), therefore lithium is a currently used therapeutic with potential to be repurposed for prevention of Dementia. An important step toward a clinical trial for AD prevention using lithium is to establish the dose of lithium that blocks GSK3 in Mild Cognitive Impairment (MCI), a high-risk condition for progression to AD. We investigated volunteer recruitment, retention, and tolerance in this population, and assessed biomarkers of GSK3 in MCI compared to control and after lithium treatment. Recruitment was close to target, with higher than anticipated interest. Drop out was not related to lithium blood concentration. Indeed, 33% of the withdrawals were in the first week of very low dose lithium. Most made it through to the highest dose of lithium with no adverse events. We analyzed 18 potential biomarkers of GSK3 biology in rat PBMCs, but only four of these gave a robust reproducible baseline signal. The only biomarker that was modified by acute lithium injection in the rat was the inhibitory phosphorylation of Ser9 of GSK3beta (enhanced in PBMCs) and this associated with reduced activity of GSK3beta. In contrast to the rat PBMC preparations the protein quality of the human PBMC preparations was extremely variable. There was no difference between GSK3 biomarkers in MCI and control PBMC preparations and no significant effect of chronic lithium on the robust GSK3 biomarkers, indicating that the dose reached may not be sufficient to modify these markers. In summary, the high interest from the MCI population, and the lack of any adverse events, suggest that it would be relatively straightforward and safe to recruit to a larger clinical trial within this dosing regimen. However, it is clear that we will need an improved PBMC isolation process along with more robust, sensitive, and validated biomarkers of GSK3 function, in order to use GSK3 pathway regulation in human PBMC preparations as a biomarker of GSK3 inhibitor efficacy, within a clinical trial setting.
There are 12 billion injections given worldwide every year. For many injections, the intramuscular route is favoured over the subcutaneous route due to the increased vascularity of muscle tissue and the corresponding increase in the bioavailability of drugs when administered intramuscularly. This paper is a review of the variables that affect the success of intramuscular injections and the implications that these success rates have in psychiatry and general medicine. Studies have shown that the success rates of intended intramuscular injections vary between 32 and 52%, with the rest potentially resulting in inadvertent subcutaneous drug deposition. These rates are found to be even lower for certain at-risk populations, such as obese patients and those on antipsychotic medications. The variables associated with an increased risk of injection failure include female sex, obesity, site of injection, and subcutaneous fat depth. New guidelines and methods are needed in order to address this challenge and ensure that patients receive optimum care. Looking forward, the best way to improve the delivery of intramuscular injections worldwide is to develop uniform algorithms or innovative medical devices to confirm or guarantee successful delivery at the bedside.
European Network of Bipolar Research Expert Centre (ENBREC): a network to foster research and promote innovative care.
Bipolar disorders rank as one of the most disabling illnesses in working age adults worldwide. Despite this, the quality of care offered to patients with this disorder is suboptimal, largely due to limitations in our understanding of the pathology. Improving this scenario requires the development of a critical mass of expertise and multicentre collaborative projects. Within the framework of the European FP7 programme, we developed a European Network of Bipolar Research Expert Centres (ENBREC) designed specifically to facilitate EU-wide studies. ENBREC provides an integrated support structure facilitating research on disease mechanisms and clinical outcomes across six European countries (France, Germany, Italy, Norway, Spain and the UK). The centres are adopting a standardised clinical assessment that explores multiple aspects of bipolar disorder through a structured evaluation designed to inform clinical decision-making as well as being applicable to research. Reliable, established measures have been prioritised, and instruments have been translated and validated when necessary. An electronic healthcare record and monitoring system (e-ENBREC©) has been developed to collate the data. Protocols to conduct multicentre clinical observational studies and joint studies on cognitive function, biomarkers, genetics, and neuroimaging are in progress; a pilot study has been completed on strategies for routine implementation of psycho-education. The network demonstrates 'proof of principle' that expert centres across Europe can collaborate on a wide range of basic science and clinical programmes using shared protocols. This paper is to describe the network and how it aims to improve the quality and effectiveness of research in a neglected priority area.
Comparative economic evaluation of quetiapine plus lamotrigine combination vs quetiapine monotherapy (and folic acid vs placebo) in patients with bipolar depression (CEQUEL).
OBJECTIVES: Although not licensed for acute bipolar depression, lamotrigine has evidence for efficacy in trials and its use is recommended in guidelines. So far there had been no prospective health economic evaluation of its use. METHODS: Cost-utility analysis of the CEQUEL trial comparing quetiapine plus lamotrigine vs quetiapine monotherapy (and folic acid vs placebo in an add-on factorial design) for patients with bipolar depression (n = 201) from the health and social care perspective. Differences in costs together with quality-adjusted life years (QALYs) between the groups were assessed over 52 weeks using a regression-based approach. RESULTS: Health-related quality of life improved substantially for all randomization groups during follow-up with no significant difference in QALYs between any of the comparisons (mean adjusted QALY difference: lamotrigine vs placebo -0.001 (95% CI: -0.05 to 0.05), folic acid vs placebo 0.002 (95% CI: -0.05 to 0.05)). While medication costs in the lamotrigine group were higher than in the placebo group (£647, P
This Review discusses crucial areas related to the identification, clinical presentation, course, and therapeutic management of bipolar disorder, a major psychiatric illness. Bipolar disorder is often misdiagnosed, leading to inappropriate, inadequate, or delayed treatment. Even when bipolar disorder is successfully diagnosed, its clinical management presents several major challenges, including how best to optimise treatment for an individual patient, and how to balance the benefits and risks of polypharmacy. We discuss the major unmet needs in the diagnosis and management of bipolar disorder in this Review, including improvement of adequate recognition and intervention in at-risk and early-disease stages, identification of reliable warning signs and prevention of relapses in unstable and rapid cycling patients, treatment of refractory depression, and prevention of suicide. Taken together, there are several promising opportunities for improving treatment of bipolar disorder to deliver medical care that is more personalised.
Comparative Efficacy and Acceptability of 21 Antidepressant Drugs for the Acute Treatment of Adults With Major Depressive Disorder: A Systematic Review and Network Meta-Analysis.
(Reprinted with permission from Lancet 2018; 391:1357-66).
A systematic review and meta-analysis of clinical predictors of lithium response in bipolar disorder.
OBJECTIVE: To determine clinical predictors of lithium response in bipolar disorder. METHODS: Systematic review of studies examining clinical predictors of lithium response was conducted. Meta-analyses were performed when ≥2 studies examined the same potential predictor. RESULTS: A total of 71 studies, including over 12 000 patients, identified six predictors of good response: mania-depression-interval sequence [odds ratio (OR): 4.27; 95% CI: 2.61, 6.97; P