2,069 research outputs found

    Latent classes of DSM-5 acute stress disorder symptoms in children after single-incident trauma: findings from an international data archive

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    Background: After a potentially traumatic event (PTE), children often show symptoms of acute stress disorder (ASD), which may evolve into posttraumatic stress (PTS) disorder. A growing body of literature has employed latent class analysis (LCA) to disentangle the complex structure underlying PTS symptomatology, distinguishing between homogeneous subgroups based on PTS presentations. So far, little is known about subgroups or classes of ASD reactions in trauma-exposed children. Objective: Our study aimed to identify latent classes of ASD symptoms in children exposed to a single-incident PTE and to identify predictors of class membership (gender, age, cultural background, parental education, trauma type, and trauma history). Method: A sample of 2287 children and adolescents (5–18 years) was derived from the Prospective studies of Acute Child Trauma and Recovery (PACT/R) Data Archive, an international archive including studies from the USA, UK, Australia, and Switzerland. LCA was used to determine distinct subgroups based on ASD symptoms. Predictors of class membership were examined using a three-step approach. Results: Our LCA yielded a three-class solution: low (42%), intermediate (43%) and high (15%) ASD symptom severity that differed in terms of impairment and number of endorsed ASD symptoms. Compared to the low symptoms class, children in the intermediate or high severity class were more likely to be of female gender, be younger of age, have parents who had not completed secondary education, and be exposed to a road traffic accident or interpersonal violence (vs. an unintentional injury). Conclusions: These findings provide new information on children at risk for ASD after single-incident trauma,

    Research priorities for progressive pulmonary fibrosis in the UK

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    Introduction Health research bodies recommend patient involvement and engagement in research and healthcare planning, although their implementation is not yet widespread. This deficiency extends to progressive pulmonary fibrosis (PPF), where crucial aspects remain unknown, including causal mechanisms, curative treatments and optimal symptom management. This study addresses these gaps by seeking stakeholders’ perspectives to guide research and treatment directions.Method A priority-setting partnership was established to explore stakeholders’ priorities in the diagnosis, treatment, management and care of PPF, including idiopathic pulmonary fibrosis which is the archetypal PPF. Stakeholders included people living with PPF, their carers, relatives and healthcare professionals involved in their management.Results Through an online open-ended survey, 2542 responses were collected from 638 stakeholders. Thematic analysis identified 48 specific research questions, which were then cross-referenced with academic literature to pinpoint research gaps. Following the evidence check, 44 unanswered questions were shortlisted by 834 stakeholders in a second online survey. Ultimately, a top 10 priority list was established through consensus.The prioritised research questions include (1) improved diagnosis accuracy and timing, (2) development of new treatments, (3) enhanced accuracy in primary care, (4) optimal timing for drug and non-drug interventions, (5) effective cough treatment, (6) early intervention for PPF, (7) improved survival rates, (8) symptom reduction, (9) impact of interventions on life expectancy and (10) new treatments with reduced side effects.Conclusion Stakeholders’ priorities can be summarised into five areas: early diagnosis, drug and non-drug treatments, survival and symptom management. Ideally, these topics should guide funding bodies and health policies

    Liver Stiffness Measurement and Biochemical Markers in Senegalese Chronic Hepatitis B Patients with Normal ALT and High Viral Load

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    Despite the high prevalence of chronic hepatitis B (CHB) in Africa, few studies have been performed among African patients. We sought to evaluate liver stiffness measurement by FibroScan® (LSM) and two biochemical scores (FibroTest®, Fibrometer®) to diagnose liver fibrosis in Senegalese CHB patients with HBV plasma DNA load ≥3.2 log(10) IU/mL and normal alanine aminotransferase (ALT) values.LSM and liver fibrosis biochemical markers were performed on 225 consecutive HBV infected Senegalese patients with high viral load. Patients with an LSM range between 7 and 13 kPa underwent liver biopsy (LB). Two experienced liver pathologists performed histological grading using Metavir and Ishak scoring.225 patients were evaluated (84% male) and LB was performed in 69 patients, showing F2 and F3 fibrosis in 17% and 10% respectively. In these patients with a 7-13 kPa range of LSM, accuracy for diagnosis of significant fibrosis according to LB was unsatisfactory for all non-invasive markers with AUROCs below 0.70. For patients with LSM values below 7 kPa, FibroTest® (FT), and Fibrometer® (FM) using the cut-offs recommended by the test promoters suggested a fibrosis in 18% of cases for FT (8% severe fibrosis) and 8% for FM. For patients with LSM values greater than 13 kPa, FT, FM suggested a possible fibrosis in 73% and 70%, respectively.In highly replicative HBV-infected African patients with normal ALT and LSM value below 13 kPa, FibroScan®, FibroTest® or Fibrometer® were unsuitable to predict the histological liver status of fibrosis

    Refined histopathological predictors of BRCA1 and BRCA2 mutation status: A large-scale analysis of breast cancer characteristics from the BCAC, CIMBA, and ENIGMA consortia

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    Introduction: The distribution of histopathological features of invasive breast tumors in BRCA1 or BRCA2 germline mutation carriers differs from that of individuals with no known mutation. Histopathological features thus have utility for mutation prediction, including statistical modeling to assess pathogenicity of BRCA1 or BRCA2 variants of uncertain clinical significance. We analyzed large pathology datasets accrued by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC) to reassess histopathological predictors of BRCA1 and BRCA2 mutation status, and provide robust likelihood ratio (LR) estimates for statistical modeling. Methods: Selection criteria for study/center inclusion were estrogen receptor (ER) status or grade data available for invasive breast cancer diagnosed younger than 70 years. The dataset included 4,477 BRCA1 mutation carriers, 2,565 BRCA2 mutation carriers, and 47,565 BCAC breast cancer cases. Country-stratified estimates of the

    Prevalence of Frailty in European Emergency Departments (FEED): an international flash mob study

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    Allele-Specific HLA Loss and Immune Escape in Lung Cancer Evolution

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    Immune evasion is a hallmark of cancer. Losing the ability to present neoantigens through human leukocyte antigen (HLA) loss may facilitate immune evasion. However, the polymorphic nature of the locus has precluded accurate HLA copy-number analysis. Here, we present loss of heterozygosity in human leukocyte antigen (LOHHLA), a computational tool to determine HLA allele-specific copy number from sequencing data. Using LOHHLA, we find that HLA LOH occurs in 40% of non-small-cell lung cancers (NSCLCs) and is associated with a high subclonal neoantigen burden, APOBEC-mediated mutagenesis, upregulation of cytolytic activity, and PD-L1 positivity. The focal nature of HLA LOH alterations, their subclonal frequencies, enrichment in metastatic sites, and occurrence as parallel events suggests that HLA LOH is an immune escape mechanism that is subject to strong microenvironmental selection pressures later in tumor evolution. Characterizing HLA LOH with LOHHLA refines neoantigen prediction and may have implications for our understanding of resistance mechanisms and immunotherapeutic approaches targeting neoantigens. Video Abstract [Figure presented] Development of the bioinformatics tool LOHHLA allows precise measurement of allele-specific HLA copy number, improves the accuracy in neoantigen prediction, and uncovers insights into how immune escape contributes to tumor evolution in non-small-cell lung cancer
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