Objectives: . Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model. Methods: . This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds. Results: . A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols. Conclusion . The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.

Background: Obesity is a well-known risk factor for chronic kidney disease and its progression. However, the impact of obesity on the renal function of the elderly population is uncertain. We investigated the association between obesity and renal outcomes in the elderly. Methods: We analyzed 130,504 participants from the Korean National Health Insurance Service-Senior cohort. Obesity was classified according to body mass index (BMI), sex-specific waist circumference (WC), and the presence of metabolic syndrome. The primary outcome was renal function decline, defined as a decline in the estimated glomerular filtration rate (eGFR) of at least 50% from baseline or new-onset end-stage renal disease. Results: During a follow-up period of 559,531.1 person-years (median, 4.3 years), 2,486 participants (19.0%; incidence rate of 4.44 per 1,000 person-years) showed renal function decline. A multivariate Cox proportional hazards model revealed that BMI/WC was not associated with renal function decline. However, the group with metabolic syndrome had a significantly increased risk of renal function decline compared to the group without metabolic syndrome (adjusted hazard ratio [HR], 1.24; 95% confidence interval [CI], 1.13–1.36). Compared with the non-metabolic syndrome group, the adjusted HRs (95% CI) for participants with one through five components were 0.96 (0.84–1.11), 1.10 (0.96–1.27), 1.24 (1.06–1.45), 1.37 (1.12–1.66), and 1.99 (1.42–2.79), respectively (p for trend < 0.001). Conclusion In elderly Korean adults, metabolic syndrome and the number of its components were associated with a higher risk of renal function decline, but BMI or WC was not significant.

Background: This study examines whether stronger corporate governance is associated with workplace mental health practices and whether this relationship is mediated by a structured sequence of occupational safety and health (OSH) engagement: recognition, goal-setting, and implementation. Methods: We analyzed 134 listed companies in Taiwan that published sustainability reports and received corporate governance evaluations between 2014 and 2023. Governance scores―based on shareholder rights, board functioning, transparency, and sustainability―were dichotomized into high vs. low categories. Workplace mental health practices were measured using 24 binary indicators across planning, provision, and reporting. OSH engagement was conceptualized in three stages based on Global Reporting Initiative 403 guidelines, with composite indicators derived via grouped weighted quantile sum regression. Associations were analyzed using generalized linear mixed-effects and serial mediation models. Results: Compared to companies ranked low in corporate governance, those ranked high had a higher likelihood of adopting mental health practices. OSH goal-setting and implementation showed significant positive associations, whereas recognition did not. Serial mediation analysis showed that 83% of the total effect of corporate governance on mental health practices was direct, while 17% was mediated through structured OSH engagement, primarily via implementation. Recognition showed a nonsignificant effect but initiated significant sequential pathways via goal-setting and implementation.Goal-setting functioned as a bridge within these chains. Conclusion Corporate governance plays a central role in advancing workplace mental health practices.While most effects are direct, structured OSH engagement helps translate governance priorities into sustained organizational actions that embed mental health into routine practice.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective To analyze the monitoring data of cardio-cerebrovascular diseases prevention and control system in Yichang in 2022, and to provide data support and experience for the precise prevention and treatment of cardio-cerebrovascular diseases. Methods Acute cardiovascular and cerebrovascular event data were collected from the Yichang Cardio-cerebrovascular Events Monitoring System from January 1, 2022 to December 31, 2022. Descriptive analysis was conducted for the data collected. Statistical analysis was performed using SPSS 20.0 software, and a chi-square test was used to analyze the count data. Results A total of 37,217 cases of cardio-cerebrovascular events were monitored in Yichang in 2022. The crude incidence and the standardized incidence were 983.84/100,000 and 541.55/100,000, respectively. The incidence in males was higher than females (554.93/100,000 vs 428.91/100,000，χ² =464.52，P＜0.05). The top three diseases were cerebral infarction, acute myocardial infarction, and cerebral hemorrhage. The incidence of events increased with age, and 79.80% of the cases were over 60 years old. The main onset time was from May to August. Conclusion The use of the cardio-cerebrovascular events monitoring system in Yichang and the implementation of ^“mandatory reporting card^” monitoring can timely obtain the epidemic characteristics of the diseases, provide support for the precise formulation of prevention and control strategies and measures, reduce underreporting rates, and improve the monitoring system, which is worthy of reference and promotion.

Objective To develop and evaluate a diagnostic model for autoimmune liver disease(AILD)using clinical indicators.Methods A total of 181 AILD patients(AILD group)diagnosed in the Department of Gastroenterology or Rheumatology and Immunology,the First Medical Center of Chinese PLA General Hospital,from June 2019 to February 2024,133 patients with hepatitis B virus cirrhosis(HBVC)(HBVC group),and 100 healthy individuals(HC group)were included in the study cohort for retrospective analysis.Clinical data,blood routine tests,and biochemical indicators were compared among the groups.Propensity score matching was used to balance the effects of factors such as gender and age.Multivariate logistic regression analysis was applied to identify characteristic indicators for AILD.Receiver operating characteristic(ROC)curves were used to evaluate the diagnostic efficacy of single and combined indicators,and the optimal diagnostic model for AILD was constructed.The Hosmer-Lemeshow test was performed to assess the model's goodness-of-fit,while ROC analysis was employed to evaluate the predictive validity.Additionally,an independent validation cohort,including 91 AILD patients(AILD validation group),82 HBVC patients(HBVC validation group),and 40 healthy individuals(HC validation group)who visited during the same period,was used to validate the diagnostic model.False-positive and false-negative rates were calculated to assess the diagnostic efficacy and clinical utility of the model.Results The age and the proportion of male patients in AILD and HBVC groups were higher than those in HC group,and the proportion of male patients in AILD group was higher than in HBVC group,the differences were statistically significant(P＜0.05).Prior to matching,compared with HC group,HBVC group and AILD group had significantly lower levels of hemoglobin(HB),red blood cell count(RBC),white blood cell count(WBC),platelet count(PLT),and albumin(ALB)(P＜0.05),but significantly higher levels of alanine aminotransferase(ALT),aspartate aminotransferase(AST),alkaline phosphatase(ALP),gamma-glutamyl transferase(GGT),total bilirubin(TBIL),and direct bilirubin(DBIL)(P＜0.05).Compared with HBVC group,AILD group had significantly higher levels of WBC,PLT,ALB,ALP,and GGT(P＜0.05 or P＜0.001)but significantly lower levels of TBIL and DBIL(P＜0.001).After maching,compared with HC group,AILD group still had significantly lower levels of HB,RBC,WBC,PLT,and ALB,but significantly higher levels of ALT,AST,ALP,GGT,TBIL,and DBIL(P＜0.05).Compared with HBVC group,AILD group had significantly higher levels of HB,RBC,WBC,PLT,ALB,ALT,ALP,and GGT,but significantly lower levels of DBIL(P＜0.05).ROC analysis results showed that AST,GGT,ALP,and DBIL had high predictive values for differentiating AILD from HC(AUC=0.843,0.804,0.802,0.773),while PLT,WBC,GGT,and ALP had high predictive values for differentiating AILD from HBVC(AUC=0.780,0.739,0.729,0.702).For distinguishing AILD from HC,the combined model of AST,ALP,and DBIL(Model e)had an AUC of 0.887,with a sensitivity of 82.2％,and a specificity of 94.7％.For distinguishing AILD from HBVC,the combined model of ALP,GGT,and PLT(Model D)had an AUC of 0.829,with a sensitivity of 78.5％and a specificity of 80.6％.Conclusions The combined diagnostic model based on AST,ALP,and DBIL can effectively differentiate healthy individuals without liver diseases from AILD patients,while the combined diagnostic model based on PLT,ALP,and GGT can effectively distinguish HBVC from AILD patients.

In recent years, the gut microbiota has become an integral research topic in human health owing to its impact on digestion, immunity, metabolic processes, and mental health. The possibilities of microbiome treatment have increased interest in dietary approaches, with a special focus on the intake of fermented foods. This has revived some of the most profound and practical constructs derived from food therapy in Chinese medicine (CM), where food therapy, along with fermented options, actively preserves health and prevents disease. In CM, the spleen and stomach system refers to the postnatal foundation of the body, which controls the processes of chewing, nutrient assimilation, and energy production (qi). The balance between intestinal and overall health is the foundation of psychosomatic well-being and is of utmost importance. Fermented foods can boost the spleen, alleviate stagnant food syndrome, dispel excess fluids, enhance protective functions, and strengthen the immune system. This review aimed to integrate the conceptual and clinical paradigms of CM with those of Western medicine, focusing on the role of fermented foods in gut microbiota regulation. This article discusses prominent fermented foods in CM and their classical functions, alongside the currently available peer-reviewed literature (published within the last 7 years) on their impact on gut flora and other clinical outcomes. Mechanistic considerations regarding the production of probiotics and other active metabolites, such as short-chain fatty acids, and the modulation of the intestinal barrier are discussed. This review also examines multidisciplinary approaches to dietary customs worldwide and outlines the clinical applications of these findings in the context of chronic disease management and gastrointestinal health.

Background/Aims: Nonalcoholic fatty liver disease (NAFLD) is a common disease with severe inflammatory processes associated with numerous gastrointestinal diseases, such as inflammatory bowel disease (IBD). Therefore, we investigated the relationship between NAFLD and IBD and the possible risk factors associated with the diagnosis of IBD. Methods: This longitudinal nationwide cohort study investigated the risk of IBD in patients with NAFLD alone. General characteristics, comorbidities, and incidence of IBD were also compared. Results: Patients diagnosed with NAFLD had a significant risk of developing IBD compared to control individuals, who were associated with a 2.245-fold risk of the diagnosis of IBD and a 2.260- and 2.231-fold of increased diagnosis of ulcerative colitis and Crohn’s disease, respectively (P< 0.001). The cumulative risk of IBD increased annually during the follow-up of patients with NAFLD (P< 0.001). Conclusions Our results emphasize that NAFLD significantly impacts its incidence in patients with NAFLD. If patients with NAFLD present with risk factors, such as diabetes mellitus and dyslipidemia, these conditions should be properly treated with regular follow-ups. Furthermore, we believe that these causes may be associated with the second peak of IBD.

Background: Barriers to treatment with intravenous thrombolysis (IVT) for patients with acute ischemic stroke (AIS) in South Korea remain incompletely characterized. We analyze a nationwide prospective cohort to determine patient-level features associated with delayed presentation and non-treatment of potential IVT-eligible patients. Methods: We identified consecutive patients with AIS from 01/2011 to 08/2023 from a multicenter and prospective acute stroke registry in Korea. Patients were defined as IVT candidates if they presented within 4.5 hours from the last known well, had no lab evidence of coagulopathy, and had National Institute of Health Stroke Scale (NIHSS) ≥ 4. Multivariable generalized linear mixed regression models were used to investigate the associations between their characteristics and the IVT candidates or the use of IVT among the candidates. Results: Among 84,103 AIS patients, 41.0% were female, with a mean age of 69 ± 13 years and presentation NIHSS of 4 [interquartile range, 1–8]. Out of these patients, 13,757 (16.4%) were eligible for IVT, of whom 8,179 (59.5%) received IVT. Female sex (adjusted risk ratio [RR], 0.90; 95% confidence interval [CI], 0.86–0.94) and lower years of education (adjusted RR, 0.90; 95% CI, 0.84–0.97 for 0–3 years, compared to ≥ 13 years) were associated with a decreased likelihood of presenting as eligible for IVT after AIS; meanwhile, young age (adjusted RR, 1.12; 95% CI, 1.01–1.24 for ≤ 44 years, compared to 75–84 years) was associated with an increased likelihood of being an IVT candidate. Among those who were eligible for IVT, only age was significantly associated with the use of IVT (adjusted RR, 1.09; 95% CI, 1.03–1.16 for age 65–74 and adjusted RR, 0.83; 95% CI, 0.76–0.90 for ≥ 85 years, respectively). Conclusion Most patients with AIS present outside IVT eligibility in South Korea, and only 60% of eligible patients were ultimately treated. We identified increased age, female sex and lower education as key features on which to focus interventions for improving IVT utilization.

Objectives: This study evaluates the efficacy of a new temporomandibular joint (TMJ) capsule suspension technique for stabilizing the TMJ after free fibular flap reconstruction of the mandibular condyle. Patients and Methods: Patients undergoing the TMJ capsule suspension technique during free fibular flap reconstruction after mandibulectomy with condylectomy (study group; n=9) were compared with a control group (n=9). Mandibular movement trajectory and surface electromyographic signals of bilateral masseters were recorded. The neocondyle–disc relationship was examined with magnetic resonance imaging (MRI) at 6 months after surgery. Results: Maximal mouth opening and bilateral marginal movement distances were comparable between the two groups (P>0.05). The asymmetry index of the condyle path length was significantly higher in controls (P=0.02). Bilateral mouth opening trajectories were symmetric in 7 patients and deviated to the affected side in 2 patients in the study group; they deviated to the affected side in all controls. The mean electromyographic values of the masseter on the affected side in resting, maximum bite, and chewing states were comparable between the two groups (P=0.13, P=0.65, and P=0.82, respectively). On MRI at 6 months, the thicknesses of the anterior, medial, and posterior bands and TMJ disc length were similar on the affected and normal sides in the study group (P=0.57, P=0.13, P=0.48, and P=0.87, respectively). Conclusion The proposed TMJ capsule suspension technique could improve postoperative TMJ structure and function after fibular free flap reconstruction following mandibulectomy with condylectomy.