Exploring the Link Between Ankylosing Spondylitis and Inflammatory Bowel Disease: A Retrospective Cohort Study.

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.

Utilizing natural language processing and large language models in the diagnosis and prediction of infectious diseases: A systematic review.

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.

Limited Clinical Impact of Genetic Associations between Celiac Disease and Type 2 Inflammatory Diseases: Insights from Mendelian Randomization.

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.

Applications of large language models in psychiatry: a systematic review.

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.

The association between psoriasis, psoriasis severity, and inflammatory bowel disease: a population-based analysis.

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.

A comparative systematic review and meta-analysis on the diagnostic accuracy of non-invasive tests for Helicobacter pylori detection in elderly patients.

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.