Forced residential mobility and social support: impacts on psychiatric disorders among Somali migrants

This study was funded by London Region NHS R&D Projectreference no: RCC01924; Prof Bhui is the PI

Vitamin D deficiency as a risk factor for infection, sepsis and mortality in the critically ill: systematic review and meta-analysis

INTRODUCTION: In Europe, vitamin D deficiency is highly prevalent varying between 40% and 60% in the healthy general adult population. The consequences of vitamin D deficiency for sepsis and outcome in critically ill patients remain controversial. We therefore systematically reviewed observational cohort studies on vitamin D deficiency in the intensive care unit.METHODS: Fourteen observational reports published from January 2000 to March 2014, retrieved from Pubmed and Embase, involving 9,715 critically ill patients and serum 25-hydroxyvitamin D3 (25 (OH)-D) concentrations, were meta-analysed.RESULTS: Levels of 25 (OH)-D less than 50 nmol/L were associated with increased rates of infection (risk ratio (RR) 1.49, 95% (confidence interval (CI) 1.12 to 1.99), P = 0.007), sepsis (RR 1.46, 95% (CI 1.27 to 1.68), P <0.001), 30-day mortality (RR 1.42, 95% (CI 1.00 to 2.02), P = 0.05), and in-hospital mortality (RR 1.79, 95% (CI 1.49 to 2.16), P <0.001). In a subgroup analysis of adjusted data including vitamin D deficiency as a risk factor for 30-day mortality the pooled RR was 1.76 (95% CI 1.37 to 2.26, P <0.001).CONCLUSIONS: This meta-analysis suggests that vitamin D deficiency increases susceptibility for severe infections and mortality of the critically ill

Impact of comorbidities by age on symptom presentation for suspected acute coronary syndromes in the emergency department

It is estimated half of acute coronary syndrome (ACS) patients have one or more associated comorbid conditions

Troubled Waters: Threats and Extinction Risk of the Sharks, Rays and Chimaeras of the Arabian Sea and Adjacent Waters

The extinction risk of sharks, rays and chimaeras is higher than that for most other vertebrates due to low intrinsic population growth rates of many species and the fishing intensity they face. The Arabian Sea and adjacent waters border some of the most important chondrichthyan fishing and trading nations globally, yet there has been no previous attempt to assess the conservation status of species occurring here. Using IUCN Red List of Threatened Species Categories and Criteria and their guidelines for application at the regional level, we present the first assessment of extinction risk for 153 species of sharks, rays and chimaeras. Results indicate that this region, home to 15% of described chondrichthyans including 30 endemic species, has some of the most threatened chondrichthyan populations in the world. Seventy-eight species (50.9%) were assessed as threatened (Critically Endangered, Endangered or Vulnerable), and 27 species (17.6%) as Near Threatened. Twenty-nine species (19%) were Data Deficient with insufficient information to assess their status. Chondrichthyan populations have significantly declined due to largely uncontrolled and unregulated fisheries combined with habitat degradation. Further, there is limited political will and national and regional capacities to assess, manage, conserve or rebuild stocks. Outside the few deepsea locations that are lightly exploited, the prognosis for the recovery of most species is poor in the near-absence of management. Concerted national and regional management measures are urgently needed to ensure extinctions are avoided, the sustainability of more productive species is secured, and to avoid the continued thinning of the regional food security portfolio

Intensity standardization of MRI prior to radiomic feature extraction for artificial intelligence research in glioma-a systematic review

Objectives Radiomics is a promising avenue in non-invasive characterisation of diffuse glioma. Clinical translation is hampered by lack of reproducibility across centres and difficulty in standardising image intensity in MRI datasets. The study aim was to perform a systematic review of different methods of MRI intensity standardisation prior to radiomic feature extraction. Methods MEDLINE, EMBASE, and SCOPUS were searched for articles meeting the following eligibility criteria: MRI radiomic studies where one method of intensity normalisation was compared with another or no normalisation, and original research concerning patients diagnosed with diffuse gliomas. Using PRISMA criteria, data were extracted from short-listed studies including number of patients, MRI sequences, validation status, radiomics software, method of segmentation, and intensity standardisation. QUADAS-2 was used for quality appraisal. Results After duplicate removal, 741 results were returned from database and reference searches and, from these, 12 papers were eligible. Due to a lack of common pre-processing and different analyses, a narrative synthesis was sought. Three different intensity standardisation techniques have been studied: histogram matching (5/12), limiting or rescaling signal intensity (8/12), and deep learning (1/12)—only two papers compared different methods. From these studies, histogram matching produced the more reliable features compared to other methods of altering MRI signal intensity. Conclusion Multiple methods of intensity standardisation have been described in the literature without clear consensus. Further research that directly compares different methods of intensity standardisation on glioma MRI datasets is required. Key Points • Intensity standardisation is a key pre-processing step in the development of robust radiomic signatures to evaluate diffuse glioma. • A minority of studies compared the impact of two or more methods. • Further research is required to directly compare multiple methods of MRI intensity standardisation on glioma datasets

A Polymorphic Microdeletion in the RGS9 Gene Suppresses PTB Binding and Associates with Obesity

Objective: RGS9 is a member of the family of Regulators of G-Protein Signaling (RGS) proteins defined by the presence of an RGS domain which can accelerate the GTPase-activity of G protein Gα subunits. An insertion/deletion (I/D) polymorphism of the nucleotide sequence TTTCT (rs3215227) has been identified in the human RGS9 gene, which matches the consensus high affinity binding motif for the ubiquitously expressed RNA binding Polypyrimidine Tract Binding Protein (PTB). In this study, we evaluate the genetic association and functional relevance of this polymorphism in type 2 diabetes and obesity. Subjects and methods: We genotyped a larger population of 9272 Chinese and Malaysian individuals for the RGS9 I/D polymorphism using TaqMan allelic discrimination protocols. We found that the D allele of the RGS9 polymorphism was associated with a decreased prevalence of obesity in women (P=0.003, OR=0.753 95%CI 0.625-0.906) and girls (P=0.002, OR=0.604 95%CI 0.437-0.835). The association was moderate in boys (P=0.038, OR=0.724 95%CI 0.533-0.983) and not significant in men. Furthermore, we found that the transcript deletion variant exhibited a 10-fold reduction in PTB binding in vitro and that the splicing of the deletion variant was less affected by PTB co-expression. Conclusions: We provide genetic and biochemical data to support a genetic role of RGS9 in obesity but unlikely in T2D. The RGS9 I/D polymorphism influence the post-transcriptional processing of the gene through an altered affinity for the splicing factor PTB and are associated with obesity

Investigating socio-economic-demographic determinants of tobacco use in Rawalpindi, Pakistan

<p>Abstract</p> <p>Background</p> <p>To investigate the socio-economic and demographic determinants of tobacco use in Rawalpindi, Pakistan.</p> <p>Methods</p> <p>Cross sectional survey of households (population based) with 2018 respondent (1038 Rural; 980 Urban) was carried out in Rawalpindi (Pakistan) and included males and females 18–65 years of age. Main outcome measure was self reported daily tobacco use.</p> <p>Results</p> <p>Overall 16.5% of the study population (33% men and 4.7% women) used tobacco on a daily basis. Modes of tobacco use included cigarette smoking (68.5%), oral tobacco(13.5%), hukka (12%) and cigarette smoking plus oral tobacco (6%). Among those not using tobacco products, 56% were exposed to Environmental tobacco smoke.</p> <p>The adjusted odds ratio of tobacco use for rural residence compared to urban residence was 1.49 (95% CI 1.1 2.0, p value 0.01) and being male as compared to female 12.6 (8.8 18.0, p value 0.001). Illiteracy was significantly associated with tobacco use. Population attributable percentage of tobacco use increases steadily as the gap between no formal Education and level of education widens.</p> <p>Conclusion</p> <p>There was a positive association between tobacco use and rural area of residence, male gender and low education levels. Low education could be a proxy for low awareness and consumer information on tobacco products. As Public health practitioners we should inform the general public especially the illiterate about the adverse health consequences of tobacco use. Counter advertisement for tobacco use, through mass media particularly radio and television, emphasizing the harmful effects of tobacco on human health is very much needed.</p

Reported Adverse Effects and Attitudes among Arab Populations Following COVID-19 Vaccination: A Large-Scale Multinational Study Implementing Machine Learning Tools in Predicting Post-Vaccination Adverse Effects Based on Predisposing Factors

Background: The unprecedented global spread of coronavirus disease 2019 (COVID-19) has imposed huge challenges on the healthcare facilities, and impacted every aspect of life. This has led to the development of several vaccines against COVID-19 within one year. This study aimed to assess the attitudes and the side effects among Arab communities after receiving a COVID-19 vaccine and use of machine learning (ML) tools to predict post-vaccination side effects based on predisposing factors. Methods: An online-based multinational survey was carried out via social media platforms from June 14 to 31 August 2021, targeting individuals who received at least one dose of a COVID-19 vaccine from 22 Arab countries. Descriptive statistics, correlation, and chi-square tests were used to analyze the data. Moreover, extensive ML tools were utilized to predict 30 post vaccination adverse effects and their severity based on 15 predisposing factors. The importance of distinct predisposing factors in predicting particular side effects was determined using global feature importance employing gradient boost as AutoML. Results: A total of 10,064 participants from 19 Arab countries were included in this study. Around 56% were female and 59% were aged from 20 to 39 years old. A high rate of vaccine hesitancy (51%) was reported among participants. Almost 88% of the participants were vaccinated with one of three COVID-19 vaccines, including Pfizer BioNTech (52.8%), AstraZeneca (20.7%), and Sinopharm (14.2%). About 72% of participants experienced post-vaccination side effects. This study reports statistically significant associations (p < 0.01) between various predisposing factors and post-vaccinations side effects. In terms of predicting post-vaccination side effects, gradient boost, random forest, and XGBoost outperformed other ML methods. The most important predisposing factors for predicting certain side effects (i.e., tiredness, fever, headache, injection site pain and swelling, myalgia, and sleepiness and laziness) were revealed to be the number of doses, gender, type of vaccine, age, and hesitancy to receive a COVID-19 vaccine. Conclusions: The reported side effects following COVID-19 vaccination among Arab populations are usually non-life-threatening; flu-like symptoms and injection site pain. Certain predisposing factors have greater weight and importance as input data in predicting post-vaccination side effects. Based on the most significant input data, ML can also be used to predict these side effects; people with certain predicted side effects may require additional medical attention, or possibly hospitalization