A systematic review published in BMCMedicine shows that Asian, Black and Mixed ethnic groups are either under-represented or incorrectly documented in UK COVID-19 randomized control trials.
). A protocol was registered in advance with the International Prospective Register of Systematic Reviews . Ethical approval was not required.A search strategy was developed to identify COVID-19 RCTs that were published in MEDLINE and Google Scholar . This deviated from the search strategy described in the protocol but was considered comprehensive following discussion with a subject librarian and the review team.
Our main outcome was percentage of each ethnic group at different trial stages, for the following: people approached for inclusion; people screened for inclusion; people determined eligible for inclusion; people determined ineligible for inclusion; people enrolled in the trial; people followed up at primary endpoint; people followed up at longest follow-up.
Search results were saved to Rayyan , a systematic review web-based application. Abstracts were independently screened for inclusion by four review authors . An online discussion was held between the authors to compare results and adjudicate any discrepancies. Where discrepancies could not be resolved by discussion, they were referred to a second review author.
The percentage of each ethnic group within each trial was calculated as a proportion and mapped against national population statistics using Office of National Statistics 2011 data for each outcome. We initially anticipated that heterogeneity in reporting would preclude statistical synthesis and had planned to only calculate percentage of each ethnic group in each trial and map this against national population statistics using forest plots, as reported in our protocol. However, after data extraction, we found more similarities and detailed reporting than we had anticipated, and hence conducted the following post hoc statistical analyses.
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Automatic disease prediction from human gut metagenomic data using boosting GraphSAGE - BMC BioinformaticsBackground The human microbiome plays a critical role in maintaining human health. Due to the recent advances in high-throughput sequencing technologies, the microbiome profiles present in the human body have become publicly available. Hence, many works have been done to analyze human microbiome profiles. These works have identified that different microbiome profiles are present in healthy and sick individuals for different diseases. Recently, several computational methods have utilized the microbiome profiles to automatically diagnose and classify the host phenotype. Results In this work, a novel deep learning framework based on boosting GraphSAGE is proposed for automatic prediction of diseases from metagenomic data. The proposed framework has two main components, (a). Metagenomic Disease graph (MD-graph) construction module, (b). Disease prediction Network (DP-Net) module. The graph construction module constructs a graph by considering each metagenomic sample as a node in the graph. The graph captures the relationship between the samples using a proximity measure. The DP-Net consists of a boosting GraphSAGE model which predicts the status of a sample as sick or healthy. The effectiveness of the proposed method is verified using real and synthetic datasets corresponding to diseases like inflammatory bowel disease and colorectal cancer. The proposed model achieved a highest AUC of 93%, Accuracy of 95%, F1-score of 95%, AUPRC of 95% for the real inflammatory bowel disease dataset and a best AUC of 90%, Accuracy of 91%, F1-score of 87% and AUPRC of 93% for the real colorectal cancer dataset. Conclusion The proposed framework outperforms other machine learning and deep learning models in terms of classification accuracy, AUC, F1-score and AUPRC for both synthetic and real metagenomic data.
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Meta-analysis of the relationship between bullying and depressive symptoms in children and adolescents - BMC PsychiatryChildhood and adolescence are critical periods for physical and mental development; thus, they are high-risk periods for the occurrence of mental disorders. The purpose of this study was to systematically evaluate the association between bullying and depressive symptoms in children and adolescents. We searched the PubMed, MEDLINE and other databases to identify studies related to bullying behavior and depressive symptoms in children and adolescents. A total of 31 studies were included, with a total sample size of 133,688 people. The results of the meta-analysis showed that the risk of depression in children and adolescents who were bullied was 2.77 times higher than that of those who were not bullied; the risk of depression in bullying individuals was 1.73 times higher than that in nonbullying individuals; and the risk of depression in individuals who bullied and experienced bullying was 3.19 times higher than that in nonbullying-bullied individuals. This study confirmed that depression in children and adolescents was significantly associated with being bullied, bullying, and bullying-bullied behavior. However, these findings are limited by the quantity and quality of the included studies and need to be confirmed by future studies.
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Ethnic terminology bedevils Taiwan-China relationsA former Taiwanese president’s use of it raises hackles on the island
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Do low-income neighbourhoods have the least green space? A cross-sectional study of Australia’s most populous cities - BMC Public HealthBackground An inequitable distribution of parks and other ‘green spaces’ could exacerbate health inequalities if people on lower incomes, who are already at greater risk of preventable diseases, have poorer access. Methods The availability of green space within 1 kilometre of a Statistical Area 1 (SA1) was linked to data from the 2011 Australian census for Sydney (n = 4.6 M residents); Melbourne (n = 4.2 M); Brisbane (n = 2.2 M); Perth (n = 1.8 M); and Adelaide (n = 1.3 M). Socioeconomic circumstances were measured via the percentage population of each SA1 living on | $21,000 per annum. Negative binomial and logit regression models were used to investigate association between the availability of green space in relation to neighbourhood socioeconomic circumstances, adjusting for city and population density. Results Green space availability was substantively lower in SA1s with a higher percentage of low income residents (e.g. an incidence rate ratio of 0.82 (95% confidence interval (95% CI) 0.75, 0.89) was observed for SA1s containing ≥20% versus 0-1% low income residents). This association varied between cities (p | 0.001). Adelaide reported the least equitable distribution of green space, with approximately 20% greenery in the most affluent areas versus 12% availability in the least affluent. Although Melbourne had a smaller proportion of SA1s in the top quintile of green space availability (13.8%), the distribution of greenery was the most equitable of all the cities, with only a 0.5% difference in the availability of green space between SA1s containing 0-1% low income households versus those with ≥20%. Inequity of access, however, was reported across all cities when using logit regression to examine the availability of at least 20% (odds ratio 0.74, 95% CI 0.59, 0.93) or 40% (0.45, 0.29, 0.69) green space availability in the more disadvantaged versus affluent neighbourhoods. Conclusion Affirmative action on green space planning is required to redress the socioecon
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The association between psychosocial factors and mental health symptoms in cervical spine pain with or without radiculopathy on health outcomes: a systematic review - BMC Musculoskeletal DisordersBackground Neck pain, with or without radiculopathy, can have significant negative effects on physical and mental wellbeing. Mental health symptoms are known to worsen prognosis across a range of musculoskeletal conditions. Understanding the association between mental health symptoms and health outcomes in this population has not been established. Our aim was to systematically review the association between psychosocial factors and/or mental health symptoms on health outcomes in adults with neck pain, with or without radiculopathy. Methods A systematic review of published and unpublished literature databases was completed. Studies reporting mental health symptoms and health outcomes in adults with neck pain with or without radiculopathy were included. Due to significant clinical heterogeneity, a narrative synthesis was completed. Each outcome was assessed using GRADE. Results Twenty-three studies were included (N = 21,968 participants). Sixteen studies assessed neck pain only (N = 17,604 participants); seven studies assessed neck pain with radiculopathy (N = 4,364 participants). Depressive symptoms were associated with poorer health outcomes in people with neck pain and neck pain with radiculopathy. These findings were from seven low-quality studies, and an additional six studies reported no association. Low-quality evidence reported that distress and anxiety symptoms were associated with poorer health outcomes in people with neck pain and radiculopathy and very low-quality evidence showed this in people with neck pain only. Stress and higher job strain were negatively associated with poorer health outcomes measured by the presence of pain in two studies of very low quality. Conclusions Across a small number of highly heterogenous, low quality studies mental health symptoms are negatively associated with health outcomes in people with neck pain with radiculopathy and neck pain without radiculopathy. Clinicians should continue to utilise robust clinical reasoning whe
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Rapid antigen-based and rapid molecular tests for the detection of SARS-CoV-2: a rapid review with network meta-analysis of diagnostic test accuracy studies - BMC MedicineBackground The global spread of COVID-19 created an explosion in rapid tests with results in | 1 hour, but their relative performance characteristics are not fully understood yet. Our aim was to determine the most sensitive and specific rapid test for the diagnosis of SARS-CoV-2. Methods Design: Rapid review and diagnostic test accuracy network meta-analysis (DTA-NMA). Eligibility criteria: Randomized controlled trials (RCTs) and observational studies assessing rapid antigen and/or rapid molecular test(s) to detect SARS-CoV-2 in participants of any age, suspected or not with SARS-CoV-2 infection. Information sources: Embase, MEDLINE, and Cochrane Central Register of Controlled Trials, up to September 12, 2021. Outcome measures: Sensitivity and specificity of rapid antigen and molecular tests suitable for detecting SARS-CoV-2. Data extraction and risk of bias assessment: Screening of literature search results was conducted by one reviewer; data abstraction was completed by one reviewer and independently verified by a second reviewer. Risk of bias was not assessed in the included studies. Data synthesis: Random-effects meta-analysis and DTA-NMA. Results We included 93 studies (reported in 88 articles) relating to 36 rapid antigen tests in 104,961 participants and 23 rapid molecular tests in 10,449 participants. Overall, rapid antigen tests had a sensitivity of 0.75 (95% confidence interval 0.70–0.79) and specificity of 0.99 (0.98–0.99). Rapid antigen test sensitivity was higher when nasal or combined samples (e.g., combinations of nose, throat, mouth, or saliva samples) were used, but lower when nasopharyngeal samples were used, and in those classified as asymptomatic at the time of testing. Rapid molecular tests may result in fewer false negatives than rapid antigen tests (sensitivity: 0.93, 0.88–0.96; specificity: 0.98, 0.97–0.99). The tests with the highest sensitivity and specificity estimates were the Xpert Xpress rapid molecular test by Cepheid (sensitivity: 0.9
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