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Previous research has not investigated the persistent cutaneous immune‐related adverse events (cirAEs) related to long COVID to investigate the long‐term sequelae. This multinational study, using a propensity‐matched overlap weighting method, utilizes large national claims‐based cohorts, using ICD‐10 code diagnosis, focusing on patients aged ≥20 years from three countries: South Korean, Japanese, and the British cohorts. To estimate the risk of cirAEs in long COVID, the persistence or emergence of cirAEs occurring 4 weeks after the initial SARS‐CoV‐2 infection, we employed a Cox proportional hazard regression model. The Korean cohort (n = 5,937,373; mean age 49.2 years [SD: 13.2]), the Japanese cohort (n = 4,307,587; 42.5 years [13.6]), and the UK cohort (n = 395,435; 71.0 years [8.07]) were presented. An increased risk of cirAEs in long COVID was observed (HR, 1.10; 95% CI, 1.06–1.14) in Korean cohort, while a similar association was observed in Japanese and UK cohorts. The long‐term risk of cirAEs in long COVID was higher in more severe COVID‐19 cases (1.31; 1.22–1.39). Unlike the increased risk of cirAEs in long COVID, COVID‐19 vaccination attenuated the risk, especially with two or more doses (1.03; 0.95–1.11) or heterologous regimens (0.98; 0.76–1.27). The time attenuation effect indicated a sustained risk for up to 6 months postinfection (<3 months: 1.13 [1.07–1.19]; 3‐6 months: 1.14 [1.06‐1.22]). SARS‐CoV‐2 infection is associated with an increased risk of cirAEs in the aspect of long COVID. Vaccination might reduce this risk, highlighting the need for preventive strategies in long COVID management. [ABSTRACT FROM AUTHOR]

Diabetes is characterized by dysregulated glucose homeostasis that leads to hyperglycemia, due in part to increased hepatic glucose production (GP) and insulin resistance. Excessive levels and/or action of glucocorticoids (GCs) are associated with obesity, insulin resistance, and hyperglycemia. We aim to delineate a mechanism of GC action in the mediobasal hypothalamus (MBH) that modulates GP in normal and pre-obese rodents. Male SD rats underwent stereotaxic MBH bilateral cannulation and intravenous (iv) and intraarterial catheterization to enable simultaneous direct infusions into the MBH, iv infusions, and blood sampling, respectively. Mildly hyperinsulinemic-euglycemic clamps with tracer dilution methodology combined with MBH GC infusion ± GC receptor (GR) inhibition enables measurement of GP and utilization while assessing MBH GC interaction with its MBH receptors independent of changes in plasma insulin, glucagon, and glucose levels. MBH GC infusion potently stimulates GP and lowers the requirement for exogenous glucose infusion without altering glucose utilization. This effect is mediated via GRs since co-infusion of GR antagonist mifepristone, or a HSP90 inhibitor, negates the ability of MBH GCs to increase GP. MBH GCs similarly increased glucose excursions during iv glucose tolerance tests, which was reversed with concomitant MBH mifepristone infusion. Rats fed with high fat diet (HFD) for 3 days had altered glucose kinetics and increased basal plasma corticosterone, insulin, and blood glucose levels without changes in body weight. Chronic MBH GR inhibition with MBH GR shRNA lowered GP compared to MBH mismatch control HFD rats with MBH vehicle infusions, suggesting that blocking excessive MBH GC action resulting from HFD-feeding attenuates GP to improve glucose homeostasis. We provide novel evidence that MBH GC action modulates GP in healthy and pre-obese rats. Importantly, targeted inhibition of MBH GC action may help improve glucose regulation in obesity-related metabolic disease. Disclosure: E. Beaulieu-Bayne: None. M. Cardoso: None. H. Kim: None. S. Yang: None. J.T. Yue: None. Funding: Diabetes Canada; Natural Sciences and Engineering Research Council of Canada; Alberta Diabetes Institute; Canadian Institutes of Health Research [ABSTRACT FROM AUTHOR]

Background: Suicide is the second-leading cause of death among adolescents and is associated with clusters of suicides. Despite numerous studies on this preventable cause of death, the focus has primarily been on single nations and traditional statistical methods., Objective: This study aims to develop a predictive model for adolescent suicidal thinking using multinational data sets and machine learning (ML)., Methods: We used data from the Korea Youth Risk Behavior Web-based Survey with 566,875 adolescents aged between 13 and 18 years and conducted external validation using the Youth Risk Behavior Survey with 103,874 adolescents and Norway's University National General Survey with 19,574 adolescents. Several tree-based ML models were developed, and feature importance and Shapley additive explanations values were analyzed to identify risk factors for adolescent suicidal thinking., Results: When trained on the Korea Youth Risk Behavior Web-based Survey data from South Korea with a 95% CI, the XGBoost model reported an area under the receiver operating characteristic (AUROC) curve of 90.06% (95% CI 89.97-90.16), displaying superior performance compared to other models. For external validation using the Youth Risk Behavior Survey data from the United States and the University National General Survey from Norway, the XGBoost model achieved AUROCs of 83.09% and 81.27%, respectively. Across all data sets, XGBoost consistently outperformed the other models with the highest AUROC score, and was selected as the optimal model. In terms of predictors of suicidal thinking, feelings of sadness and despair were the most influential, accounting for 57.4% of the impact, followed by stress status at 19.8%. This was followed by age (5.7%), household income (4%), academic achievement (3.4%), sex (2.1%), and others, which contributed less than 2% each., Conclusions: This study used ML by integrating diverse data sets from 3 countries to address adolescent suicide. The findings highlight the important role of emotional health indicators in predicting suicidal thinking among adolescents. Specifically, sadness and despair were identified as the most significant predictors, followed by stressful conditions and age. These findings emphasize the critical need for early diagnosis and prevention of mental health issues during adolescence., (©Hyejun Kim, Yejun Son, Hojae Lee, Jiseung Kang, Ahmed Hammoodi, Yujin Choi, Hyeon Jin Kim, Hayeon Lee, Guillaume Fond, Laurent Boyer, Rosie Kwon, Selin Woo, Dong Keon Yon. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 17.05.2024.)