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BACKGROUND: Whole genome sequencing is increasingly being used for the diagnosis of patients with rare diseases. However, the diagnostic yields of many studies, particularly those conducted in a healthcare setting, are often disappointingly low, at 25-30%. This is in part because although entire genomes are sequenced, analysis is often confined to in silico gene panels or coding regions of the genome. METHODS: We undertook WGS on a cohort of 122 unrelated rare disease patients and their relatives (300 genomes) who had been pre-screened by gene panels or arrays. Patients were recruited from a broad spectrum of clinical specialties. We applied a bioinformatics pipeline that would allow comprehensive analysis of all variant types. We combined established bioinformatics tools for phenotypic and genomic analysis with our novel algorithms (SVRare, ALTSPLICE and GREEN-DB) to detect and annotate structural, splice site and non-coding variants. RESULTS: Our diagnostic yield was 43/122 cases (35%), although 47/122 cases (39%) were considered solved when considering novel candidate genes with supporting functional data into account. Structural, splice site and deep intronic variants contributed to 20/47 (43%) of our solved cases. Five genes that are novel, or were novel at the time of discovery, were identified, whilst a further three genes are putative novel disease genes with evidence of causality. We identified variants of uncertain significance in a further fourteen candidate genes. The phenotypic spectrum associated with RMND1 was expanded to include polymicrogyria. Two patients with secondary findings in FBN1 and KCNQ1 were confirmed to have previously unidentified Marfan and long QT syndromes, respectively, and were referred for further clinical interventions. Clinical diagnoses were changed in six patients and treatment adjustments made for eight individuals, which for five patients was considered life-saving. CONCLUSIONS: Genome sequencing is increasingly being considered as a first-line genetic test in routine clinical settings and can make a substantial contribution to rapidly identifying a causal aetiology for many patients, shortening their diagnostic odyssey. We have demonstrated that structural, splice site and intronic variants make a significant contribution to diagnostic yield and that comprehensive analysis of the entire genome is essential to maximise the value of clinical genome sequencing.
\n \n\n \n \nOBJECTIVE: To describe, and explain the rationale for, the methods used and decisions made during development of the updated SPIRIT 2024 and CONSORT 2024 reporting guidelines. METHODS: We developed SPIRIT 2024 and CONSORT 2024 together to facilitate harmonisation of the two guidelines, and incorporated content from key extensions. We conducted a scoping review of comments suggesting changes to SPIRIT 2013 and CONSORT 2010, and compiled a list of other possible revisions based on existing SPIRIT and CONSORT extensions, other reporting guidelines and personal communications. From this, we generated a list of potential modifications or additions to SPIRIT and CONSORT, which we presented to stakeholders for feedback in an international online Delphi survey. The Delphi survey results were discussed at an online expert consensus meeting attended by 30 invited international participants. We then drafted the updated SPIRIT and CONSORT checklists and revised them based on further feedback from meeting attendees. RESULTS: We compiled 83 suggestions for revisions or additions to SPIRIT and/or CONSORT from the scoping review and 85 from other sources, from which we generated 33 potential changes to SPIRIT (n=5) or CONSORT (n=28). Of 465 participants invited to take part in the Delphi survey, 317 (68%) responded to Round 1, 303 (65%) to Round 2 and 290 (63%) to Round 3. Two additional potential checklist changes were added to the Delphi survey based on Round 1 comments. Overall, 14/35 (SPIRIT n=0; CONSORT n=14)) proposed changes reached the predefined consensus threshold (\u226580% agreement), and participants provided 3,580 free-text comments. The consensus meeting participants agreed with implementing 11/14 of the proposed changes that reached consensus in the Delphi and supported implementing a further 4/21 changes (SPIRIT n=2; CONSORT n=2) that had not reached the Delphi threshold. They also recommended further changes to refine key concepts and for clarity. CONCLUSION: The forthcoming SPIRIT 2024 and CONSORT 2024 Statements will provide updated, harmonised guidance for reporting randomised controlled trial protocols and results, respectively. The simultaneous development of the SPIRIT and CONSORT checklists has been informed by current empirical evidence and extensive input from stakeholders. We hope that this report of the methods used will be helpful for developers of future reporting guidelines.
\n \n\n \n \nThe CONSORT 2010 statement provides minimum guidelines for reporting randomized trials. Its widespread use has been instrumental in ensuring transparency in the evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate impact on health outcomes. The CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trials evaluating interventions with an AI component. It was developed in parallel with its companion statement for clinical trial protocols: SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 29 candidate items, which were assessed by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a two-day consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The CONSORT-AI extension includes 14 new items that were considered sufficiently important for AI interventions that they should be routinely reported in addition to the core CONSORT 2010 items. CONSORT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention is integrated, the handling of inputs and outputs of the AI intervention, the human-AI interaction and provision of an analysis of error cases. CONSORT-AI will help promote transparency and completeness in reporting clinical trials for AI interventions. It will assist editors and peer reviewers, as well as the general readership, to understand, interpret and critically appraise the quality of clinical trial design and risk of bias in the reported outcomes.
\n \n\n \n \nThis document details the proposed statistical analysis and presentation of the results for the main paper reporting the findings from the NIHR funded Clinical Prediction Rule for Postoperative Atrial Fibrillation in Patients Undergoing Cardiac Surgery after Cardiac Surgery -the PARADISE Score. This plan is intended to establish the rules that will be followed, as closely as possible, when modelling and reporting the prediction model.\nThis analysis plan will be available on request after submitting the main papers for publication in a scientific journal. Any deviations from the statistical analysis plan will be described and justified in the final report of the study. An identified, appropriately qualified, and experienced statistician will conduct the analysis, as well as ensuring the integrity of the data during their processing. Examples of such procedures include quality control and evaluation procedures.
\n \n\n \n \nmRNA vaccine technologies introduced following the SARS-CoV-2 pandemic have highlighted the need to better understand the interaction of adjuvants and the early innate immune response. Type I interferon (IFN-I) is an integral part of this early innate response that primes several components of the adaptive immune response. Women are widely reported to respond better than men to tri- and quadrivalent influenza vaccines. Plasmacytoid dendritic cells (pDCs) are the primary cell type responsible for IFN-I production, and female pDCs produce more IFN-I than male pDCs since the upstream pattern recognition receptor Toll-like receptor 7 (TLR7) is encoded by X chromosome and is biallelically expressed by up to 30% of female immune cells. Additionally, the TLR7 promoter contains several putative androgen response elements, and androgens have been reported to suppress pDC IFN-I in vitro. Unexpectedly, therefore, we recently observed that male adolescents mount stronger antibody responses to the Pfizer BNT162b2 mRNA vaccine than female adolescents after controlling for natural SARS-CoV-2 infection. We here examined pDC behaviour in this same cohort to determine the impact of IFN-I on anti-spike and anti-receptor-binding domain IgG titres to BNT162b2. Through flow cytometry and least absolute shrinkage and selection operator (LASSO) modelling, we determined that serum-free testosterone was associated with reduced pDC IFN-I, but contrary to the well-described immunosuppressive role for androgens, the most bioactive androgen dihydrotestosterone was associated with increased IgG titres to BNT162b2. Also unexpectedly, we observed that co-vaccination with live attenuated influenza vaccine boosted the magnitude of IgG responses to BNT162b2. Together, these data support a model where systemic IFN-I increases vaccine-mediated immune responses, yet for vaccines with intracellular stages, modulation of the local IFN-I response may alter antigen longevity and consequently improve vaccine-driven immunity.
\n \n\n \n \nBACKGROUND: The evidence for whether ivermectin impacts recovery, hospital admissions, and longer-term outcomes in COVID-19 is contested. The WHO recommends its use only in the context of clinical trials. METHODS: In this multicentre, open-label, multi-arm, adaptive platform randomised controlled trial, we included participants aged \u226518 years in the community, with a positive SARS-CoV-2 test, and symptoms lasting \u226414 days. Participants were randomised to usual care, usual care plus ivermectin tablets (target 300-400 \u03bcg/kg per dose, once daily for 3 days), or usual care plus other interventions. Co-primary endpoints were time to first self-reported recovery, and COVID-19 related hospitalisation/death within 28 days, analysed using Bayesian models. Recovery at 6 months was the primary, longer term outcome. TRIAL REGISTRATION: ISRCTN86534580. FINDINGS: The primary analysis included 8811 SARS-CoV-2 positive participants (median symptom duration 5 days), randomised to ivermectin (n=2157), usual care (n=3256), and other treatments (n=3398) from June 23, 2021 to July 1, 2022. Time to self-reported recovery was shorter in the ivermectin group compared with usual care (hazard ratio 1\u00b715 [95% Bayesian credible interval, 1\u00b707 to 1\u00b723], median decrease 2.06 days [1\u00b700 to 3\u00b706]), probability of meaningful effect (pre-specified hazard ratio \u22651.2) 0\u00b7192). COVID-19-related hospitalisations/deaths (odds ratio 1\u00b702 [0\u00b763 to 1\u00b762]; estimated percentage difference 0% [-1% to 0\u00b76%]), serious adverse events (three and five respectively), and the proportion feeling fully recovered were similar in both groups at 6 months (74\u00b73% and 71\u00b72% respectively (RR = 1\u00b705, [1\u00b702 to 1\u00b708]) and also at 3 and 12 months.,. INTERPRETATION: Ivermectin for COVID-19 is unlikely to provide clinically meaningful improvement in recovery, hospital admissions, or longer-term outcomes. Further trials of ivermectin for SARS-Cov-2 infection in vaccinated community populations appear unwarranted. FUNDING: UKRI / National Institute of Health Research (MC_PC_19079).
\n \n\n \n \nBACKGROUND: Multisystem inflammatory syndrome in children (MIS-C) is a rare but serious hyperinflammatory complication following infection with severe acute respiratory syndrome coronavirus 2. The mechanisms underpinning the pathophysiology of MIS-C are poorly understood. Moreover, clinically distinguishing MIS-C from other childhood infectious and inflammatory conditions, such as Kawasaki disease or severe bacterial and viral infections, is challenging due to overlapping clinical and laboratory features. We aimed to determine a set of plasma protein biomarkers that could discriminate MIS-C from those other diseases. METHODS: Seven candidate protein biomarkers for MIS-C were selected based on literature and from whole blood RNA sequencing data from patients with MIS-C and other diseases. Plasma concentrations of ARG1, CCL20, CD163, CORIN, CXCL9, PCSK9 and ADAMTS2 were quantified in MIS-C (n = 22), Kawasaki disease (n = 23), definite bacterial (n = 28) and viral (n = 27) disease and healthy controls (n = 8). Logistic regression models were used to determine the discriminatory ability of individual proteins and protein combinations to identify MIS-C and association with severity of illness. RESULTS: Plasma levels of CD163, CXCL9 and PCSK9 were significantly elevated in MIS-C with a combined area under the receiver operating characteristic curve of 85.7% (95% confidence interval: 76.6%-94.8%) for discriminating MIS-C from other childhood diseases. Lower ARG1 and CORIN plasma levels were significantly associated with severe MIS-C cases requiring inotropes, pediatric intensive care unit admission or with shock. CONCLUSION: Our findings demonstrate the feasibility of a host protein biomarker signature for MIS-C and may provide new insight into its pathophysiology.
\n \n\n \n \nBackground: Immigrants are exposed to numerous risk factors that may contribute to the development of chronic musculoskeletal pain. Recent political and environmental crises in North Africa and the Middle East have led to an increase in immigration to Europe that has challenged the healthcare system and especially the management of chronic conditions. Objective: The aims of this scoping review are to investigate the burden, prevalence, and associated factors of chronic musculoskeletal pain in immigrants from North Africa and the Middle East in Europe during the last decade. The intentions of the review are to inform healthcare policymakers, to identify gaps in the literature, and aid the planning of future research. Design: Online databases Medline, Embase, PubMed and Web of Science were used to identify epidemiological studies published from2012\u20132022 examining chronic pain in populations from North Africa and the Middle East with a migration background residing in Europe. Results: In total eleven studies were identified conducted in Norway (n = 3), Denmark (n = 3), Germany (n = 1), Austria (n = 1), Sweden (n = 1), and Switzerland (n = 1). Among the identified studies, eight studies were cross-sectional (n = 8), two were prospective cohort studies (n = 2) and one was a retrospective cohort study (n = 1). Data suggested that chronic pain is more prevalent, more widespread, and more severe in people with than without a migration background. Furthermore, immigrants who have resided in the destination country for a longer period experience a higher prevalence of chronic pain compared to those in the early phases of migration. The following factors were found to be associated with chronic pain in this population: female gender, lower education, financial hardship, being underweight or obese, time in transit during migration, experience of trauma, immigration status, anxiety, depression, and post-traumatic stress disorder. Conclusion: Several gaps in the literature were identified. Research is limited in terms of quantity and quality, does not reflect actual immigration trends, and does not account for immigration factors. Prospective cohort studies with long follow-ups would aid in improving prevention and management of chronic pain in populations with a migration background. In particular, they should reflect actual immigration trajectories, account for immigration factors, and have valid comparison groups in the countries of origin, transit and destination.
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