Background: This study aims to analyze the historical trends of inflammatory bowel disease (IBD) burden in the elderly from 1990 to 2021 and forecast future trends up to 2051.Methods: Data from the Global Burden of Disease Study 2021 were utilized. Age-standardized rates (ASR) for incidence, prevalence, mortality, and disability-adjusted life years (DALYs) were calculated. Estimated annual percentage changes (EAPCs) were computed to quantify temporal trends. A Bayesian Age-Period-Cohort model was employed to project future trends.Results: From 1990 to 2021, the global number of elderly IBD increased from 573,500 to 1,278,190. The age-standardized incidence rate (ASIR) rose from 8.01 to 8.77 per 100,000, while the age-standardized prevalence rate (ASPR) slightly decreased from 118.14 to 117.29 per 100,000. Death number increased from 14,400 to 33,490, but the age-standardized mortality rate decreased from 3.21 to 2.84 per 100,000. DALYs increased from 324,100 to 683,750, with the age-standardized DALYs rate declining from 68.78 to 60.88 per 100,000. Significant geographical variations were observed, with high Socio-demographic Index regions showing the highest burden. Projections suggest that by 2051, elderly IBD prevalence number may reach 2,316,000, with ASIR and ASPR potentially rising after 2035 and 2042, respectively. Deaths and DALYs are projected to increase to 75,000 and 1,401,000 respectively, despite continued declines in ASRs.Conclusion: The absolute burden of IBD in the elderly population is projected to increase substantially by 2051, despite decreasing ASRs. These findings underscore the need for tailored healthcare strategies and resource allocation to address the growing challenge of elderly IBD globally.

Background: Human papillomavirus (HPV) is a virus primarily transmitted through sexual contact. Little is known about the association between HPV infection or immunization and the risk for rheumatoid arthritis (RA). The purpose of this study was to evaluate whether HPV infection or immunization is related to the risk for RA in adults.Methods: Data were obtained from the 2007-2016 National Health and Nutrition Examination Survey (NHANES). We developed three independent multivariate logistic regression models to evaluate the association between HPV infection or immunization and the risk for RA in adults.Results: Finally, we analyzed 15,677 and 8,944 subjects, respectively. In all models, HPV infection was positively associated with an increased prevalence of RA in adults aged 18-59 years, with the highest value of the odds ratio (OR) in model 2 (after weighting: OR 1.095, 95% CI 1.092, 1.097), whereas HPV immunization significantly reduced the prevalence of RA in adults aged 18-59 years, with the lowest OR in model C (after weighting: OR 0.477, 95% CI 0.472, 0.481). These associations persisted after correction for confounders such as age, sex, race, education level, marital status, smoking, diabetes, hypertension, hyperlipidemia, and BMI.Conclusion: In summary, our study suggests that HPV infection is positively associated with the prevalence of RA in adults, and HPV immunization can reduce the prevalence of RA in adults. However, our findings need more powerful to prove these associations through rigorously designed prospective studies.

Background: Rapidly progressive interstitial lung disease (RP-ILD) is a significant complication that determines the prognosis of dermatomyositis (DM). Early RP-ILD diagnosis can improve screening and diagnostic efficiency and provide meaningful guidance to carry out early and aggressive treatment. Methods: A retrospective screening of 284 patients with DM was performed. Clinical and laboratory characteristics of the patients were recorded. The risk factors of RP-ILD in DM patients were screened by logistic regression (LR) and machine learning methods, and the prediction models of RP-ILD were developed by machine learning methods, namely least absolute shrinkage and selection operator (LASSO), random forest (RF), and extreme gradient boosting (XGBoost). Results: According to the result of univariate LR, disease duration is a protective factor for RP-ILD, and ESR, CRP, anti-Ro-52 antibody and anti-MDA5 antibody are risk factors for RP-ILD. The top 10 important variables of the 3 machine learning models were intersected to obtain common important variables, and there were 5 common important variables, namely disease duration, LDH, CRP, anti-Ro-52 antibody and anti-MDA5 antibody. The AUC of LASSO, RF and XGBoost test set were 0.661, 0.667 and 0.867, respectively. We further validated the performance of these three models on validation set, and the results showed that, the AUC of LASSO, RF and XGBoost were 0.764, 0.727 and 0.909, respectively. Based on the results of the models, XGBoost is the optimal model in this study. Conclusion: Disease duration, LDH, CRP, anti-Ro-52 antibody and anti-MDA5 antibody are vital risk factors for RP-ILD in DM. The prediction model constructed using XGBoost can be used for risk identification and early intervention in DM patients with RP-ILD and practical application.

Background: Using machine learning based on metabolomics, this study aimed to construct an effective primary Sjogren’s syndrome (pSS) diagnostics model and reveal the potential targets and biomarkers of pSS.Methods: From a total of 39 patients with pSS and 38 healthy controls (HCs), serum specimens were collected. The samples were analyzed by ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry. Three machine learning algorithms, including the least absolute shrinkage and selection operator (LASSO), random forest (RF), and extreme gradient boosting (XGBoost), were used to build the pSS diagnosis models. Afterward, four machine learning methods were used to reduce the dimensionality of the metabolomics data. Finally, metabolites with significant differences were screened and pathway analysis was conducted.Results: The area under the curve (AUC), sensitivity, and specificity of LASSO, RF and XGBoost test set all reached 1.00. Orthogonal partial least squares discriminant analysis was used to classify the metabolomics data. By combining the results of the univariate false discovery rate and the importance of the variable in projection, we identified 21 significantly different metabolites. Using these 21 metabolites for diagnostic modeling, the AUC, sensitivity, and specificity of LASSO, RF, and XGBoost all reached 1.00. Metabolic pathway analysis revealed that these 21 metabolites are highly correlated with amino acid and lipid metabolisms. On the basis of 21 metabolites, we screened the important variables in the models. Further, five common variables were obtained by intersecting the important variables of three models. Based on these five common variables, the AUC, sensitivity, and specificity of LASSO, RF, and XGBoost all reached 1.00.2-Hydroxypalmitic acid, L-carnitine and cyclic AMP were found to be potential targets and specific biomarkers for pSS.Conclusion: The combination of machine learning and metabolomics can accurately distinguish between patients with pSS and HCs. 2-Hydroxypalmitic acid, L-carnitine and cyclic AMP were potential targets and biomarkers for pSS.

Objective: Smoking is a major risk factor for peptic ulcer disease (PUD) mortality. This study aims to analyze global trends in smoking-attributable PUD mortality from 1990 to 2021 and project future trends to 2046.Methods: Data were obtained from the Global Burden of Disease Study 2021. We calculated age-standardized mortality rates (ASMR) and estimated annual percentage changes (EAPC) for smoking-attributable PUD mortality. Bayesian Age-Period-Cohort models were used to project future trends.Results: From 1990 to 2021, global smoking-attributable PUD deaths decreased from 48,900 to 29,400, with the ASMR declining from 1.2 to 0.3 per 100,000 (EAPC: −4.25%). High-income regions showed faster declines, while some low- and middle-income countries experienced slower progress or even increases. Projections suggest a continued global decline in smoking-attributable PUD mortality to 2046, with persistent regional disparities. By 2046, the global ASMR is expected to decrease to approximately 0.1 per 100,000, with higher rates persisting in certain regions such as the Solomon Islands (3.7 per 100,000) and Cambodia (1.6 per 100,000).Conclusion: While global smoking-attributable PUD mortality has significantly decreased and is projected to continue declining, substantial regional disparities persist. These findings underscore the need for targeted tobacco control interventions, particularly in high-risk regions, to further reduce the global burden of smoking-attributable PUD mortality.