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Background: Celiac disease, a gluten-triggered autoimmune disorder, is known for its systemic inflammatory effects. Its genetic associations with type 2 inflammatory diseases like asthma, allergic rhinitis, and atopic dermatitis remain unclear, prompting this study to explore their potential genetic interplay. Methods: Utilizing two-sample Mendelian randomization (TSMR), we examined the genetic associations using 15 genetic instruments from GWAS datasets. Our analysis focused on celiac disease and its relation to asthma, allergic rhinitis, atopic dermatitis, and IgE-mediated food allergies. A power analysis was conducted to determine the study's detection capabilities, and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using various MR methods. Results: Our Mendelian randomization analysis identified statistically significant genetic associations between celiac disease and several type 2 inflammatory diseases, although these were practically insignificant. Specifically, celiac disease was associated with a slight increase in the risk of atopic dermatitis (OR = 1.037) and a minor protective effect against asthma (OR = 0.97). The link with allergic rhinitis was statistically detectable (OR = 1.002) but practically negligible. Despite robust statistical confirmation through various sensitivity analyses, all observed effects remained within the range of practical equivalence (ROPE). Conclusions: Our study identifies potential genetic associations between celiac disease and certain type 2 inflammatory diseases. However, these associations, predominantly within the ROPE range, suggest only limited clinical implications. These findings highlight the need for cautious interpretation and indicate that further exploration for clinical applications may not be warranted at this stage.
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Background: With their unmatched ability to interpret and engage with human language and context, large language models (LLMs) hint at the potential to bridge AI and human cognitive processes. This review explores the current application of LLMs, such as ChatGPT, in the field of psychiatry. Methods: We followed PRISMA guidelines and searched through PubMed, Embase, Web of Science, and Scopus, up until March 2024. Results: From 771 retrieved articles, we included 16 that directly examine LLMs' use in psychiatry. LLMs, particularly ChatGPT and GPT-4, showed diverse applications in clinical reasoning, social media, and education within psychiatry. They can assist in diagnosing mental health issues, managing depression, evaluating suicide risk, and supporting education in the field. However, our review also points out their limitations, such as difficulties with complex cases and potential underestimation of suicide risks. Conclusion: Early research in psychiatry reveals LLMs' versatile applications, from diagnostic support to educational roles. Given the rapid pace of advancement, future investigations are poised to explore the extent to which these models might redefine traditional roles in mental health care.
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BACKGROUND: Natural Language Processing (NLP) and Large Language Models (LLMs) hold largely untapped potential in infectious disease management. This review explores their current use and uncovers areas needing more attention. METHODS: This analysis followed systematic review procedures, registered with the Prospective Register of Systematic Reviews. We conducted a search across major databases including PubMed, Embase, Web of Science, and Scopus, up to December 2023, using keywords related to NLP, LLM, and infectious diseases. We also employed the Quality Assessment of Diagnostic Accuracy Studies-2 tool for evaluating the quality and robustness of the included studies. RESULTS: Our review identified 15 studies with diverse applications of NLP in infectious disease management. Notable examples include GPT-4's application in detecting urinary tract infections and BERTweet's use in Lyme Disease surveillance through social media analysis. These models demonstrated effective disease monitoring and public health tracking capabilities. However, the effectiveness varied across studies. For instance, while some NLP tools showed high accuracy in pneumonia detection and high sensitivity in identifying invasive mold diseases from medical reports, others fell short in areas like bloodstream infection management. CONCLUSIONS: This review highlights the yet-to-be-fully-realized promise of NLP and LLMs in infectious disease management. It calls for more exploration to fully harness AI's capabilities, particularly in the areas of diagnosis, surveillance, predicting disease courses, and tracking epidemiological trends.
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Doenças Transmissíveis , Processamento de Linguagem Natural , Humanos , Doenças Transmissíveis/diagnósticoRESUMO
BACKGROUND: Ankylosing spondylitis (AS) and inflammatory bowel disease (IBD) are chronic conditions with overlapping pathogenic mechanisms. The genetic predisposition and inflammatory pathways common to both diseases suggest a syndemic relationship. While some evidence points to a connection between the two conditions, other reports do not support this link. OBJECTIVES: To investigate the association between AS and the subsequent incidence of IBD. To identify potential risk factors and effect modifiers that contribute to this relationship. METHODS: Utilizing the Chronic Disease Registry of Clalit Health Services, we conducted a retrospective cohort study of individuals diagnosed with AS between January 2002 and December 2018. We compared these patients with age- and sex-matched controls, excluding those with a prior diagnosis of IBD. Statistical analyses included chi-square and t-tests for demographic comparisons, and Cox proportional hazards models for evaluating the risk of IBD development, with adjustments for various co-morbidities and demographic factors. RESULTS: The study included 5825 AS patients and 28,356 controls. AS patients demonstrated a significantly higher incidence of IBD with hazard ratios of 6.09 for Crohn's disease and 2.31 for ulcerative colitis, after multivariate adjustment. The overall incidence of IBD in the AS cohort was significantly higher compared to controls. CONCLUSIONS: AS patients exhibit a markedly increased risk of developing IBD. These findings advocate for heightened clinical vigilance for IBD symptoms in AS patients and suggest the need for a multidisciplinary approach to patient care. Further research into the shared pathogenic pathways is needed to develop personalized treatment strategies and improve patient management.
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Colite Ulcerativa , Doença de Crohn , Doenças Inflamatórias Intestinais , Espondilite Anquilosante , Humanos , Estudos Retrospectivos , Espondilite Anquilosante/epidemiologia , Doenças Inflamatórias Intestinais/epidemiologia , Doença de Crohn/epidemiologiaRESUMO
Background: The skin-gut axis, characterized by bidirectional communication between the skin and gut, plays a crucial role in the pathogenesis of psoriasis and inflammatory bowel diseases (IBD). Objectives: We aimed to explore the association between psoriasis and IBD and identify predictors associated with IBD development among patients with psoriasis. Design: Retrospective cohort study. Methods: A retrospective study which utilized an electronic database from the Meuhedet Health Maintenance Organization (MHMO) in Israel. Psoriasis was categorized as severe if any systemic agent or phototherapy was administered. Univariate and multivariate logistic regressions were used to identify specific predictors for IBD, with adjustments made for potential confounders. The study received approval from the Ethical Committee of the MHMO. Results: In total, 61,003 adult patients who were diagnosed with psoriasis between 2000 and 2022 were included. Among them, 1495/61,003 patients (2.4%) were diagnosed with IBD, as compared to 3834/244,012 patients (1.6%) in the non-psoriasis group [adjusted odds ratio (OR): 1.47; 95% confidence interval (CI): 1.37-1.56; p < 0.001]. Increased age (OR: 1.01; 95% CI: 1.01-1.02; p < 0.001), male gender (OR: 1.22; 95% CI: 1.03-1.45; p = 0.024), and Jewish ethnicity (OR: 2.5; 95% CI: 1.2-4.1; p < 0.001) were identified as significant risk factors for IBD. Spondyloarthropathies, including psoriatic arthritis (OR: 2.27; 95% CI: 1.86-2.77; p < 0.001) and ankylosing spondylitis (OR: 2.82; 95% CI: 1.5-5.32; p < 0.05), were associated with a higher prevalence of IBD. Furthermore, severe psoriasis was significantly associated with a higher likelihood of IBD, compared to mild psoriasis (OR: 16.03; 95% CI: 11.02-23.34; p < 0.001). Conclusion: A significant association between psoriasis and IBD was demonstrated, including its subtypes: Crohn's disease and ulcerative colitis. Moreover, such association may depend on psoriasis severity as determined by the treatment used. This association warrants further investigation and implies a potential need for closer monitoring of patients with severe psoriasis.
Association between psoriatic disease severity and risk of inflammatory bowel diseases 1- Gut and skin barrier play an integral role in psoriasis and inflammatory bowel disease (IBD) development. 2- Shared genetic and environmental factors could explain the association between both diseases. 3- We report increased association between psoriasis and IBD, a relationship that is more pronounced in patients with severe psoriasis. 4- Patients with spondyloarthritis related diseases have a stronger association with IBD.
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BACKGROUND: Coeliac disease affects approximately 1% of the global population with the diagnosis often relying on invasive and time-demanding methods. Deep learning, a powerful tool in medical science, shows potential for non-invasive, accurate coeliac disease diagnosis, though challenges remain. OBJECTIVE: This systematic review aimed to evaluate the current state of deep-learning applications in coeliac disease diagnosis and identify potential areas for future research that could enhance diagnostic accuracy, sensitivity, and specificity. METHODS: A systematic review was conducted using the following databases: PubMed, Embase, Web of Science, and Scopus. PRISMA guidelines were applied. Two independent reviewers identified research articles using deep learning for coeliac disease diagnosis and severity assessment. Only original research articles with performance metrics data were included. The quality of the diagnostic accuracy studies was assessed using the QUADAS-2 tool, categorizing studies based on risk of bias and concerns about applicability. Due to heterogeneity, a narrative synthesis was conducted to describe the applications and efficacy of the deep-learning techniques (DLT) in coeliac disease diagnosis. RESULTS: The initial search across four databases yielded 417 studies with 195 being removed due to duplicity. Finally, eight studies were found to be suitable for inclusion after rigorous evaluation. They were all published between 2017 and 2023 and focused on using DLT for coeliac disease diagnosis or assessing disease severity. Different deep-learning architectures were applied. Accuracy levels ranged from 84% to 95.94% with the GoogLeNet model achieving 100% sensitivity and specificity for video capsule endoscopy images. CONCLUSIONS: DLT hold substantial potential in coeliac disease diagnosis. They offer improved accuracy and the prospect of mitigating clinician bias. However, key challenges persist, notably the requirement for more extensive and diverse datasets, especially to detect milder forms of coeliac disease. These methods are in their nascent stages, underscoring the need of integrating multiple data sources to achieve comprehensive coeliac disease diagnosis.
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Background: Helicobacter pylori (H. pylori) infection, a type I carcinogen, affects approximately 50% of the global population, correlating with various gastric pathologies. Notably, diagnostic sensitivities of non-invasive methods, such as the stool antigen test (HpSA), Serology, and Urea Breath Test (UBT), have been suggested to be less effective in older age groups. This study systematically reviews and meta-analyzes the diagnostic accuracy of these tests within the elderly population. Methods: A comprehensive literature search was performed across multiple databases, including PubMed, Medline, and Web of Science, up to July 2023. Data were pooled and analyzed using random-effects models. Sensitivity, specificity, and Diagnostic Odds Ratios (DOR) were computed for the tests. Heterogeneity and risk of bias were assessed. Results: Eight studies involving diverse geographic locations and totaling between 46 and 1,441 participants per study were included. The pooled sensitivity and specificity for HpSA were 72.5 and 94.7%, for Serology 83.7 and 73.3%, and for UBT 96.4 and 88.3%, respectively. DOR for UBT, HpSA, and Serology were 94.5, 47.9, and 14.2, respectively. High levels of heterogeneity were observed across the studies. Conclusion: UBT and HpSA proved effective for diagnosing H. pylori in those over 60, while serology showed lower specificity. Despite methodological variations in available studies, these non-invasive tests offer reliable alternatives, especially for older patients who recently undergone endoscopy or without an indication for it, warranting consideration by healthcare practitioners.
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Background: Due to its apparent efficacy and safety, dupilumab, a monoclonal antibody that blocks Interleukin 4 (IL-4) and Interleukin 13 (IL-13), has been approved for treating T-helper 2 (Th2) disorders. However, adverse effects like local injection site reactions, conjunctivitis, headaches, and nasopharyngitis have been reported. Sex differences are known to influence both adaptive and innate immune responses and, thus, may have a bearing on the occurrence of these adverse effects. Nevertheless, the literature lacks a comprehensive exploration of this influence, a gap this study aims to bridge. Materials and Methods: A comprehensive data mining of VigiBase, the World Health Organization (WHO) global pharmacovigilance database which contains case safety reports of adverse drug reactions (ADRs) was performed to test for sex -specific safety response to dual IL4/IL13 blockade by dupilumab. The information component (IC), a measure of the disproportionality of ADR occurrence, was evaluated and compared between males and females to identify potential sexual dimorphism. Results: Of the 94,065 ADRs recorded in the WHO global pharmacovigilance database, 2,001 (57.4%) were reported among female dupilumab users, and 1,768 (50.7%) were among males. Immune/autoimmune T-helper 1 (Th1)-, innate- and T-helper 17 (Th17)-driven diseases and degenerative ones were consistently reported with a stronger association with Dupilumab in males than females. Some adverse events were more robustly associated with Dupilumab in females. Conclusion: Dupilumab has an excellent safety profile, even though some ADRs may occur. The risk is higher among male patients, further studies, including ad hoc studies, are needed to establish causality.
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BACKGROUND: The link between ankylosing spondylitis (AS) and inflammatory bowel disease (IBD) is well-established, with concurrent prevalence estimates ranging from 5-10%. However, there are still significant gaps in our understanding, and a comprehensive treatment guideline for these co-diagnosed patients has yet to be established. Our objective was to explore patterns of treatment alterations following the diagnosis of AS in patients previously diagnosed with IBD, and vice versa. Additionally, we sought to determine how these modifications influence clinical outcomes in both conditions. METHODS: This retrospective data-based cohort study included patients with coexisting IBD and AS that were diagnosed between the years 2009-2022 and were followed by the gastroenterology and the rheumatology units of the Sheba Medical Center, Israel. The data were extracted from the electronic health record and included demographic information, medication history, treatment modification at the time of second diagnosis, and the characteristics and activity of both IBD and AS at the index time and at the 3-month mark. RESULTS: The study included a total of 68 patients, with a male predominance (40 patients, 59%). The median age was 43 years (IQR 31-55) and 78% had Crohn's disease (CD). The median duration between the diagnosis of the first disease to the second one was 4 years (IQR 1-9.5). A significant proportion of patients (85%) underwent treatment modification at their second diagnosis. Out of the total cohort, 28% initiated biological therapy, 17.6% switched their biologic regimen, and 16.2% discontinued NSAIDS. Patients who underwent biologic modifications at time of the second diagnosis (the initiation/switch/augmentation of a concurrent regimen) experienced significantly higher rates of clinical improvement in either IBD or AS at the 90-day follow-up compared to patients who did not (68% vs. 32%, p = 0.004), and biologic modification was found to be an independent predictor for clinical improvement (OR 3.69, CI 1.08-12.58, p = 0.037). CONCLUSIONS: Our findings suggest that biologic therapy modification at the time of the second diagnosis was associated with a higher rate of improvement in AS/IBD at the 90-day follow-up.
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BACKGROUND: Ankylosing spondylitis (AS) is an inflammatory rheumatic disease involving the axial skeleton ultimately resulting in physical disability and psychological sequalae. The current study aims to evaluate the link between AS and psychiatric disorders, and to investigate the impact of different disease modifying drugs on such link. METHODS: A large retrospective, population-based, cross-sectional study utilizing the Clalit-Health-Service (CHS) database was conducted on 5825 AS patients and 25,984 age- and sex-matched control individuals. The prevalence of psychiatric morbidity was compared between AS patients and age- and gender-matched controls. Predictors for psychiatric disorders in AS patients were also investigated. RESULTS: The prevalence of psychiatric morbidity was higher in AS patients compared to controls (13.8 % vs. 9.8 %, p < 0.001). Similarly, major depression was positively associated with AS (OR 1.60, 95 % CI 1.43-1.79, p < 0.001), however, schizophrenia was negatively associated with AS (OR 0.60, 95 % CI 0.42-0.89, p < 0.011). Conventional DMARDs (cDMARDs) and anti-TNF used for management of AS were not shown to be predictors for psychiatric illnesses in AS patients. CONCLUSIONS: Patients with AS are at a higher risk of developing psychiatric disorders, with increased risk of depression and lower risk of schizophrenia. cDMARDs and TNF-inhibitors are not predictors of psychiatric disorders in AS patients.